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Three lines of evidence to link outbreaks of the crown-of-
thorns seastar Acanthaster planci to the release of larval food
limitation
K. E. Fabricius
1
*, K. Okaji
2
, G. De’ath
1
1 Australian Institute of Marine Science, PMB No. 3, Townsville MC, Qld 4810, Australia.
2 Coralquest Inc., Asahicho 1-34-10, Atsugi, Kanagawa 243-0014, Japan
* Corresponding author: k.fabricius@aims.gov.au , phone: +61-747534412, fax +61-747725852.
Running title: A. planci outbreaks and phytoplankton
Key words: Crown-of-thorns starfish, seastar, trophic limitation, Great Barrier Reef, Acanthaster planci,
eutrophication, phytoplankton, chlorophyll.
Abstract
Population outbreaks of the coral-eating crown-of-thorns seastar, Acanthaster planci, continue to kill
more coral on Indo-Pacific coral reefs than other disturbances, but the causes of these outbreaks have
not been resolved. In this study we combine (1) results from laboratory experiments where larvae were
reared on natural phytoplankton, (2) large-scale and long-term field data of river floods, chlorophyll
concentrations and A. planci outbreaks on the Great Barrier Reef (GBR), and (3) results from A. planci
– coral population model simulations that investigated the relationship between the frequency of
outbreaks and larval food availability. The experiments show that the odds of A. planci larvae
completing development increases ~8-fold with every doubling of chlorophyll concentrations up to 3
µg L
-1
. Field data and the population model show that river floods and regional differences in
phytoplankton availability are strongly related to spatial and temporal patterns in A. planci outbreaks
on the GBR. The model also shows that, given plausible historic increases in river nutrient loads over
the last 200 years, the frequency of A. planci outbreaks on the GBR has likely increased from one in
50 – 80 years to one every 15 years, and that current coral cover of reefs in the central GBR may be 30
– 40% of its potential value. This study adds new and strong empirical support to the hypothesis that
primary A. planci outbreaks are predominantly controlled by phytoplankton availability.
Introduction
On most Indo-Pacific coral reefs, including the Great Barrier Reef (GBR), coral cover has
been declining at rates of 0.2 – 1.5% per year since the 1960s (Bruno and Selig 2007). To
date, predation of coral by crown-of-thorns seastar (Acanthaster planci) accounts for a large
proportion of the observed decline in coral cover on the GBR. Between 1985 and 1997,
population outbreak of A. planci were observed on ~32% of monitored reefs on the GBR,
with their coral cover averaging 9% one year after the outbreak, compared with a mean of
28% coral cover on reefs that had not experienced an outbreak in the same period (Lourey et
al. 2000). These figures suggest a GBR-wide reduction in coral cover of 0.5% yr
-1
due to A.
planci alone in this 12 years period. Population outbreaks of A. planci, i.e., the sudden
emergence of a large population after a period of relative rarity (Moran 1986), were first
recorded throughout the Indo-Pacific in the 1960s. The abrupt population increase by orders
of magnitude from a small parent population is called a ‘primary outbreak’ (Birkeland and
Lucas 1990), and questions concerning the cause(s) of such primary outbreaks, and whether
or not human activities have changed their frequency, have to date remained unresolved. In
contrast, secondary outbreaks are simply the consequence of the large numbers of gametes
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
2
produced upstream by a primary outbreak or another secondary outbreak population. Such
secondary outbreaks have been reconstructed using hydrodynamic models (Moran 1986;
Dight et al. 1990).
There are many hypotheses that relate to the control of A. planci populations (reviewed in
Birkeland and Lucas 1990; Brodie et al. 2005). Echinoderms that release large numbers of
planktotrophic larvae such as A. planci have a propensity to population fluctuations (Uthicke
et al. 2009), and some primary A. planci outbreaks have been recorded even on coral reefs
that remained relatively unaltered by human activities (Birkeland 1982, Birkeland and Lucas
1990). However, the observed widespread decline in coral cover since the 1960s suggest that
the recently observed frequency of primary outbreaks of once in ~15-years is unsustainable
(Seymour and Bradbury 1999). Even before mass bleaching started to inflict additional
mortality, most reefs were estimated to take 10 – 25 years for full recovery of coral cover,
with 25% of reefs showing no signs of recovery from A. planci coral mortality (Lourey et al.
2000). Two hypotheses that specifically address the apparent increase in the frequency of
primary outbreaks have been widely debated. They are: (1) the ‘terrestrial runoff hypothesis’
aka ‘larval starvation hypothesis’ that argues that nutrient limited survival of the pelagic
planktotrophic larvae of A. planci controls population outbreaks (Birkeland 1982; Lucas
1982; Brodie et al. 2005), and (2) the ‘predator removal hypothesis’, which postulates that
more juveniles survive to maturity due to the removal of fish predators through human
exploitation (reviewed in Birkeland and Lucas 1990). Both hypotheses are based more on
circumstantial than empirical support.
The terrestrial runoff hypothesis has strong correlative evidence (reviewed in Brodie et al.
2005). More outbreaks occur on reefs near high Pacific islands or continental coasts from
which terrestrial runoff occurs, compared to low atoll islands without terrestrial runoff, and
most outbreaks follow large or drought-breaking floods that carry high nutrient and sediment
loads (Birkeland 1982). The apparent increase in A. planci outbreak frequencies is attributed
to increased nutrient levels resulting from the terrestrial runoff of fertilizers, sewage and
eroding soils, as recorded throughout the Indo-Pacific in modern times (Brodie et al. 2005).
The planktotrophic larvae of A. planci feed on nano- and microphytoplankton (>3 µm cells)
(Okaji et al. 1997) that multiply at high nutrient levels. Earlier feeding experiments with
cultured microalgae showed that larval development was optimal at 2 – 6.5 µg L
-1
chlorophyll, while few larvae completed their development at <0.6 µg L
-1
chlorophyll (Lucas
1982). However, the types of cultured microalgae also determined the developmental success
of A. planci larvae (Lucas 1982), limiting inferences from these experiments about larval
development in natural phytoplankton communities.
The predator removal hypothesis states that seastar populations are largely controlled by
predation, and that increased human exploitation of fish predators has resulted in increased
numbers of seastars surviving to maturity (McCallum 1987). Dulvy et al. (2004) have
suggested a relationship between A. planci outbreaks and human population density (but not
fish predator densities) on 7 of 13 investigated reefs in Fiji, and Sweatman (2008) has shown
a relationship between reef protection status and A. planci outbreaks on pairs of reefs open
and closed to fishing in the GBR. However, the more commonly fished large predatory fish
don’t usually prey upon A. planci (Sweatman 1995) and to date, no fish predator has been
identified that can effectively regulate A. planci populations, although predation on juveniles
undoubtedly occurs (Keesing et al. 1996). It is argued (but difficult to show empirically) that
the removal of large predators may (1) suppress prey switching behavior, i.e., the fewer large
predatory fish stop eating the less preferred A. planci, and/or (2) have caused some complex
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
3
trophic cascades, eventually resulting in fewer bottom-dwelling invertebrates that eat juvenile
seastar (Keesing et al. 1996; Sweatman 2008).
In this study we re-examine the contribution of terrestrial runoff to limiting the frequency of
primary outbreaks, by combining new empirical evidence from A. planci larval feeding
experiments, large-scale and long-term river flood and chlorophyll monitoring data for the
GBR, and model-based simulations of the population dynamics of A. planci and its main
drivers. Extensive long-term and large-scale coral reef, water quality and river monitoring
data are now available for the GBR (Brodie et al. 2007; Sweatman et al. 2008), thereby
providing a new opportunity to resolve the A. planci issue that affects the health of many
Indo-Pacific coral reefs.
Methods
Laboratory Experiments
Eight separate laboratory experiments were used to quantify rates of development and
survival of larvae reared at different concentrations of natural phytoplankton as detailed in
Okaji (1996). Seawater was collected from the ocean and filtered through a 25 µm mesh to
remove large zooplankton and detrital matter. This coarsely filtered seawater was used to
create fresh batches daily of the following treatments:
(a) 0.45-FSW: filtration through a 0.45 µm GF/B filter;
(b) 2-FSW: filtration through a 2 µm polycarbonate membrane filter;
(c) 25-FSW: no further treatment of the coarsely filtered seawater;
(d) NES: nutrient-enriched seawater: 2 ml of Guillard’s f/2 nutrient solution (Guillard 1975)
were added to 20 L of freshly collected and coarsely filtered seawater. This nutrient-
enriched seawater was incubated in a 500 L water bath outdoors without shading for 2
days prior to use to develop the phytoplankton communities. Nutrient enrichment
increased the concentration of eukaryotic phytoplankton cells and the concentration of
chlorophyll on average 20-fold in NES compared with 25-FSW, while the concentration
of cyanobacteria cells increased to a lesser extent (2- to 3-fold, Table 1).
The treatment levels of the 8 experiments are listed in Table 1. Each treatment was done in
triplicates for Experiments 1 to 6, and in duplicates for Experiments 7 and 8. Experiments 1,
2, 5 and 6 were conducted at Lizard Island Research Station in the northern Great Barrier
Reef (GBR), which is surrounded by clear offshore waters. Experiments 3 and 4 were
conducted at the University of the Ryukyus (Okinawa, Japan), using water sampled from the
front of Chatan Reef, Okinawa, from often clear coastal waters. Experiments 7 and 8 were
conducted at the Australian Institute of Marine Science (central GBR), with the often turbid
coastal seawater collected off Cape Bowling Green once a week and stored outdoors in
aerated 500 L tanks. For Experiments 1 to 4, duplicate seawater samples were taken from
each container every day, and for Experiments 5 and 6 every second day. The chlorophyll a
concentration of these samples was determined using fluorometry, and the densities of
eukaryotic algal and cyanobacteria cells were counted with an epifluorescence microscope
(Table 1). In Experiments 7 and 8, chlorophyll a of the NES was determined fluorometrically
before use, and NES was diluted with 0.45-FSW to obtain the final chlorophyll
concentrations. The use of total chlorophyll a concentrations overestimates food availability
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
4
Table 1: Mean percentage of surviving A. planci larvae that completed their development (late
brachiolarian stage or metamorphosed to juveniles) at age 22 days, in treatments with
contrasting concentrations of natural phytoplankton. Treatments: 0.45-FSW, 2-FSE, and 25
FSE = seawater filtered using 0.45, 2 and 25 µm filters, respectively; NES = nutrient enriched
seawater.
Experi-
ment
Treatment
Chl. a
(µg L
-1
± SD)
Eukaryote density
(10
3
mL
-1
± SD)
Cyanobacteria
density
(10
3
mL
-1
± SD)
Completion
(% of survivors ±
SD)
1
0.45-FSW
0.07 ± 0.03
(not detected)
25 ± 16
0 ± 0
1
2-FSW
0.17 ± 0.10
0.004 ± 0.006
55 ± 36
0 ± 0
1
25-FSW
0.40 ± 0.20
0.214 ± 0.112
65 ± 36
0 ± 0
2
0.45-FSW
0.08 ± 0.03
(not detected)
31 ± 16
0 ± 0
2
2-FSW
0.25 ± 0.11
0.004 ± 0.004
75 ± 34
0 ± 0
2
25-FSW
0.52 ± 0.21
0.234 ± 0.086
83 ± 30
0 ± 0
3
2-FSW
0.08 ± 0.03
0.163 ± 0.125
6.4 ± 5.9
0 ± 0
3
25-FSW
0.29 ± 0.10
0.437 ± 0.222
7.1 ± 6.1
18.7 ± 8.5
4
25-FSW
0.28 ± 0.08
0.385 ± 0.178
6.7 ± 5.1
0 ± 0
5
2-FSW
0.19 ± 0.10
0.004 ± 0.002
56 ± 40
0 ± 0
5
25-FSW
0.28 ± 0.10
0.207 ± 0.077
62 ± 41
88.3 ± 8.6
5
50% NES
2.91 ± 1.35
2.435 ± 0.564
142 ± 90
100 ± 0
5
100% NES
5.25 ± 2.32
4.441 ± 0.989
202 ± 157
100 ± 0
6
2-FSW
0.19 ± 0.10
0.004 ± 0.002
56 ± 40
0 ± 0
6
25-FSW
0.28 ± 0.10
0.207 ± 0.077
62 ± 41
97.2 ± 1.7
6
50% NES
2.91 ± 1.35
2.435 ± 0.564
142 ± 90
99 ± 0.7
6
NES
5.25 ± 2.32
4.441 ± 0.989
202 ± 157
100 ± 0
7
NES
0.10
0 ± 0
7
NES
0.20
0 ± 0
7
NES
0.40
0 ± 0
7
NES
0.80
32.2 ± 0.5
7
NES
1.60
50.2 ± 26.6
8
NES
0.01
0 ± 0
8
NES
0.25
0 ± 0
8
NES
0.50
6.8 ± 0.9
8
NES
0.75
38.6 ± 4.1
8
NES
1.00
61.6 ± 4.4
for A. planci, because the contribution of nano- and microphytoplankton, the preferred food of
A. planci larvae, is typically <50% of chlorophyll a in Indo-Pacific waters (Charpy and
Blanchot 1999; Crosbie and Furnas 2001). The rest is picoplankton (<3 µm cells) that
constitutes <10% of the diet of A. planci larvae (Okaji et al. 1997). However, the use of
natural phytoplankton communities in our experiments, in which the relative contribution of
nano- and microphytoplankton to chlorophyll reflects that found in the field, enabled us to
relate the experimental results to the GBR long-term chlorophyll data.
Batches of A. planci larvae were reared in the laboratory (Okaji 1996). Actively swimming
and healthy early bipinnaria larvae with fully developed alimentary canal were collected 2
days after the in vitro fertilization of gametes, and 100 larvae (150 larvae in Experiments 7
and 8) were added to each treatment chamber (1 litre volume for Experiments 1 and 2; 2 litres
for all others), which were gently aerated and kept in the temperature range 26.5 – 29C.
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
5
Larvae were sieved with a 60 µm mesh and transferred to a clean set of containers of freshly
prepared seawater every day. Every second to forth day, larvae were individually examined
under a dissecting microscope, and their developmental stages recorded following Lucas
(1982). For Experiments 7 and 8 the body lengths of 10 to 20 randomly selected larvae per
chamber were measured along their longest axes every fourth day with an ocular micrometer.
When the first larvae reached brachiolaria stage, aeration was reduced and a few small chips
of crustose coralline algae were introduced as settlement substratum. These chips were
checked daily in order to count metamorphosing larvae and settled juveniles.
The diameters of juvenile seastar after completion of metamorphosis were measured with an
ocular micrometer in Experiment 5. The rate of successful completion of development was
defined as the proportion of surviving larvae that were either in late brachiolaria or juvenile
stages after 22 days. These two stages were combined since late brachiolaria larvae are
competent to metamorphose to juveniles. Absolute survivorship was not analyzed because
abnormal or regressed larvae can remain alive for extended periods of time without any
prospect of further development (‘living ghosts’), and there were no rigorous criteria to
distinguish these from healthy larvae. Clearly regressed or abnormal larvae were scored as
bipinnaria.
For the statistical analyses, the results of all 8 experiments were combined (Table 1). The
relationship between rate of successful completion of development after 22 days and
chlorophyll concentration was analyzed using a generalized linear mixed model; a logistic
regression model where the response was the proportion of successful developmental
completion. Two severe outliers (88% and 97% survivorship in E5, 25-FSW and E6, 25-
FSW; Table 1) were excluded from the final model. Runs in Experiment 2 that were
terminated after 18 days due to a lack of development in all treatments were scored as ‘zero
completion’. All analyses were done using the statistical software package R (R Development
Core Team 2009).
GBR Flood History and Chlorophyll Data
Data of the cumulative discharge volumes of the Burdekin River since 1922 and the five
largest Wet Tropics rivers (Herbert, Tully, Johnstone, Russell and Barron Rivers, latitude
16.5 – 18.5S) were obtained from the Queensland Department of Environment and
Resource Management, and the values for the Burdekin River plotted for each ‘water year’
(1
st
October – 30
th
September). The Burdekin River is the largest river entering into the GBR
lagoon, and the most important factor determining inter-annual variability in flood plumes,
since the annual discharge from its dry subtropical catchment varies by two orders of
magnitude between its wettest and driest years (long-term annual mean discharge: 8.5 km
3
yr
-
1
; CV = 106% of annual mean). In contrast, discharges from the many annually flooding
rivers in Wet Tropics catchments, which jointly supply ~40% of the total annual runoff to the
GBR (Furnas 2003), vary less between years (CV = 34 – 37% of annual means for Tully,
Johnstone and Russell River, and 75 – 76% for the Herbert and Barron Rivers). Continuous
monitoring of the Burdekin River started in 1922, and of the Wet Tropics Rivers between
1967 and 1983.
Data of summer chlorophyll a concentrations were extracted from the GBR long-term
Chlorophyll Monitoring Program Data Base, which has sampled chlorophyll concentrations
along fixed transects across the continental shelf monthly since 1993 (Brodie et al. 2007).
Most A. planci on the GBR spawn in December to January (Lucas 1973; Babcock and Mundy
1992). Under experimental conditions, the duration of the pelagic larval phase is 12 to 22 days
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
6
for well-fed larvae (Birkeland and Lucas 1990), and >50 days for larvae reared in filtered
seawater (Lucas 1982). Thus chlorophyll records from November to March were used to
quantify long-term average summer values for the far northern (FN, 12.0 – 15.0S) and
central/northern regions (CN, 15.1 – 19.2S). The data from each region were further split
into the inner <25 km of the shelf (containing inshore and midshelf reefs in CN and FN) and
outer locations, as most small to medium-sized river flood plumes remain within the inner 25
km of the shelf and travel along the coast towards the north due to the prevailing
hydrodynamic patterns and Coriolis forcing (King et al. 2001; Devlin and Brodie 2005).
Differences in the probabilities of larvae completing their development were then calculated
for FN and CN based on the estimated differences in larval survival rates for given
chlorophyll levels using the response curve from the laboratory experiments and long-term
average chlorophyll concentrations in the GBR.
The A. planci – Coral Simulation Model
The model was used to simulate spatial-temporal distributions of A. planci on the GBR. By
varying the drivers and parameters of the model, running various scenarios and conducting
sensitivity analyses, we investigated the temporal dynamics and the spatial patterns of the
outbreaks. The simulation model comprised four linked sub-models:
(1) The A. planci model: This is an age-structured meta-population model with two juvenile
and six adult stages, each of one year duration. Life history parameters included age-
dependent size, rates of survival across age cohorts, age-dependent fertility and feeding rates
on corals (Table 2; Moran 1986; Birkeland and Lucas 1990; Scandol 1993).
(2) The coral model: The parameters included the rates of growth of coral as the prey of
juvenile and adult A. planci (Scandol 1993; Sweatman et al. 2001; Wolanski and De’ath
2005).
(3) The chlorophyll model: The spatial-temporal variation in chlorophyll was based on data
from the GBR Long-Term Chlorophyll Monitoring Program (Brodie et al. 2007). Compared
to long-term change, temporal variation was large on seasonal and short time scales. Both
observed chlorophyll data (i.e., field observations) as well as simulated data including
gradients and spikes originating from floods were used in the model.
(4) The connectivity model: The connectivity of a reef to other reefs determines its capacity
to provide larvae to itself (i.e., to self-seed), to other reefs (i.e., be a source), and to receive
larvae from other reefs (i.e., be a sink). Hydrodynamic models provided estimates of the self-
seeding, source and sink levels for 321 reefs in the central and northern GBR (James et al.
2002).
A justifiable criticism of population modeling is that, given enough parameters, one can
reproduce most observed data. We have safeguarded against this problem by (1) focusing on
relative not absolute effects (determining the ratios and 90% confidence ranges of values for
A. planci and corals for FN and CN), and (2) using sensitivity analyses: The robustness of the
model assumptions were tested by adding various levels of stochastic noise to any of the A.
planci and coral life history variables, and by varying many of the model parameters within
reasonable ranges (e.g., variations in the rates of coral replenishment and consumption, and
juvenile and adult survival and fecundity). The models and all analyses of outputs were
programmed in the statistical software package R (R Development Core Team 2009).
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
7
Results
a) Laboratory experiments
The laboratory experiments, in which freshly hatched A. planci larvae were reared in seawater
at 0.01 to 5.25 µg L
-1
chlorophyll a, showed that the proportion of larvae completing their
development increased rapidly with increasing natural phytoplankton concentration (Fig. 1).
At 0.01 – 0.25 µg L
-1
chlorophyll, few larvae developed from the bipinnaria to early
brachiolaria stage, none developed beyond the early brachiolaria stage, and most regressed at
days 10 to 14. The odds of completion of development increased by a factor 8.3 (95% CI =
4.7, 17.7) for each doubling of concentrations of chlorophyll (Fig. 2a, Table 1). At low to
moderate chlorophyll concentrations (<0.5 µg L
-1
), this was equivalent to increasing the
probability of completing development by a factor 7 – 8 for each doubling of chlorophyll. At
higher concentrations, the rate of increase in the probability of completion slowed, and
plateaued at >3 µg L
-1
where completion was certain.
Figure 1: Developmental success of A. planci larvae that were exposed to different phytoplankton concentrations
in 8 experiments (E1 – E8). Larval developmental stages: white = bipinnaria, wide diagonal hatch= early
brachiolaria, narrow diagonal hatch = mid brachiolaria, grey shade = late brachiolaria, black = metamorphosed
juvenile seastar. The latter two stages together were scored as ‘completed development’. Abbreviations: 0.45-
FSW, 2-FSE and 25 FSE = seawater filtered using 0.45, 2 and 25 µm filters; NES = nutrient enriched seawater.
Growth rates, developmental speed and final body sizes of the larvae and early seastar also
depended on the availability of phytoplankton. Larvae reared at ≥0.8 µg L
-1
chlorophyll
reached the maximum observed size of 1.2 – 1.3 mm at 17 to 20 days of age, suggesting
growth was not food limited (Fig. 2b). At <0.5 µg L
-1
chlorophyll, larvae initially grew from
0.8 to 1.0 mm but growth arrested after days 12 to 15 (Fig. 3). The time for 50% of surviving
larvae to complete development decreased from 41 to 14 days when chlorophyll increased
from 0.5 to >2 µg L
-1
(not shown). Similarly, larvae that developed at 0.28 µg L
-1
chlorophyll
metamorphosed into seastars with significantly smaller mean diameter (0.44 mm, SE = 0.07
mm) than larvae reared at 2.9 or 5.2 µg L
-1
chlorophyll (0.66 mm, SE = 0.05 mm; 0.64 mm,
SE = 0.09 mm).
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
8
Combining the data on rates of developmental completion and growth suggests the following
chlorophyll thresholds. At <0.25 µg L
-1
(<220 eukaryotic cells m L
-1
; Table 1), a negligible
proportion of larvae complete development, suggesting starvation. At 0.25 – 0.8 µg L
-1
(220 –
670 eukaryotic cells mL
-1
) this proportion is moderate, but development is slow and body
sizes of larvae and juveniles remain small, suggesting severe food limitation. Finally, at >2 µg
L
-1
(>1700 eukaryotic cells mL
-1
) larval developmental success is high, developmental speed
is fast, and both larvae and juveniles grow to their maximum observed size, suggesting release
from trophic limitation.
Figure 2: (a) Relationship between chlorophyll a concentration and the proportion of A. planci larvae completing
their development. (b) Body length of A. planci larvae at 17-20 days of age. Each point represents the mean
results of duplicate or triplicate deployments per treatment. Black lines are model fits, the thin black lines are 2
SE of the mean.
Figure 3: Patterns of growth of A. planci larvae at increasing concentrations of chlorophyll a (Experiments 7 and
8). Shrinkage observable around days 16 to 20 reflects contraction for metamorphosis.
b) Temporal and spatial correlations between chlorophyll availability and A. planci
primary outbreaks
The patterns in Burdekin River discharges showed strong temporal and spatial agreement with
the timing and location of primary outbreaks of A. planci in the GBR. On the GBR, primary
outbreaks were first observed at 16.75S in 1962 and 1979, and between 14.7 – 16.1S in
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
9
1993/94 (Moran et al. 1992; Miller 2002; Sweatman 2008). The three largest recorded floods
of the Burdekin River yielded freshwater discharges of 28, 54 and 40 km
3
in 1958, 1974 and
1991 (Fig. 4). In 1974, all Wet Tropics rivers except the Herbert also produced >90
th
percentile floods, and in 1991, the Herbert and Barron produced >90
th
percentile floods and
the other three rivers were above median levels. Therefore, the 1979 and 1994 outbreaks
occurred three to five years after the two wettest years on record. The 1962 outbreak is
difficult to interpret since the 1958 flood occurred in February-March and hence may have
been too late in the season to feed A. planci larvae, and because few data exist from the Wet
Tropics rivers. A large flood also occurred very early in the 1950/51wet season, but no A.
planci data exist from that period (Fig. 4). The region north of Latitude 16.75S is the only
section of the whole GBR where the dense matrix of large mid- and outer-shelf reefs such as
Green Island frequently encounters river plumes (Fig. 5; Devlin and Brodie 2005; Brodie et
al. 2005).
Figure 4: Cumulative discharge volumes of the
Burdekin River into the GBR for each year since
1922. Red lines indicate the three large floods that
preceded the three recorded primary outbreaks of A.
planci in 1966, 1979 and 1994. The dark grey line
shows an early large flood in 1951, but no data exist
from that period. The blue lines show the large 2008
and 2009 Burdekin floods, potentially predicting the
onset of a fourth primary outbreak.
A satellite image from a moderate flood event on the central and northern GBR (Fig. 5)
illustrates: (1) the Burdekin plume extending >200 km to the north where it merges with the
plumes from the Herbert and many Wet Tropics rivers; (2) the plumes intersect mid-and
outer-shelf reefs around latitude 16 – 17S due to offshore diversion by the Cape Grafton
headland and a narrow continental shelf; and (3) the plume waters do not intersect with any
large reefs elsewhere as the remaining reef tract is too far offshore and all inshore reefs are
very small.
Strong regional differences in the long-term average summer chlorophyll concentrations are
also apparent on the GBR. Along the inner 25 km of the GBR, chlorophyll values were on
average twice as high in the central/northern GBR (CN) compared to the far northern GBR
(FN) (0.54 vs 0.26 µg L
-1
). Assuming our experimental results were indicative of food
limitation in the field, this ~2-fold difference in chlorophyll concentrations between CN and
FN would translate into a ~8-fold higher rate of successful larval development in the former.
Additionally, levels of chlorophyll exceeding 0.5 µg L
-1
occur for ~37% of summer values in
the inner CN, compared to 5.7 – 6.4% in the remaining sectors.
A re-analysis of AIMS Long-Term Monitoring Program data (Sweatman et al. 2008) of A.
planci outbreaks and coral cover shows that in the period 1985 – 2007, 12.9% ± 1.7% (SE) of
reefs in CN were in a state of ‘active or incipient outbreak’ at anyone time, and coral cover
averaged 16.5% ± 0.8%. In contrast, in FN only 5.5% ± 0.01% of reefs had A. planci
outbreaks, no outbreak waves have been observed, and coral cover averaged 28.0% ± 1.0%.
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
10
c) A. planci – coral spatial-temporal simulation model
We used the A. planci – coral spatial-temporal simulation model to investigate and quantify
the relationships between inshore chlorophyll, seastar populations and coral cover (Figs. 6 and
7, Table 2). The two principal drivers of the A. planci populations were both food-resource
related, and comprised:
(1) The concentration of chlorophyll in the water column which determines the
probability of A. planci larvae to survive until settlement and metamorphosis;
(2) The availability of hard coral for consumption by the juvenile and adult A. planci.
The former is governed by the empirical relationship between larval survival and
concentrations of chlorophyll in the water (Fig. 6a – c). At low levels of chlorophyll the larval
survival was low and thus A. planci populations remained low and coral cover was high.
Conversely, at high levels of chlorophyll the abundant larvae led to large populations of A.
planci adults that can deplete the hard coral cover within a few years.
Table 2: Model parameters for the A. planci - coral simulation model. The values were based on Scandol (1993).
The temporal dynamics and patterns of the model results were relatively insensitive to variation of these
parameters. Abbreviations: J1, J2: juveniles aged 1 and 2 years, A1 – A5: adults aged 3 to 7 years.
Life Stage
Survival
Fecundity
Coral consumed
J1
0.02
0
0.01
J2
0.1
0.1
1.3
A1
0.25
0.3
3.7
A2
0.5
0.5
7.3
A3
0.6
0.7
11
A4
0.6
0.7
11
A5
0.6
0.7
11
Figure 5: Satellite image of the central GBR
(Modis, 10
th
February 2007), also showing the
locations of the mouths of the main rivers, and
towns (filled square). All inshore reefs, and the mid-
and outer-shelf reefs north of latitude 17S (the
presumed location of source reefs for primary A.
planci outbreaks on the GBR, red box) are
inundated by flood waters from the merged plumes
of several rivers, while the remaining mid- and
outer-shelf reefs are not intercepted by the flood
plumes during this moderate flood event.
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
11
Figure 6: Relationship of Acanthaster planci population dynamics and chlorophyll in the Great Barrier Reef
(GBR) off the NE of Australia. (a) Map of the GBR. (b). Long-term average chlorophyll concentrations in the
GBR in the far northern (FN, blue) and central/northern (CN, red) region, monitored near-monthly since 1992.
Applying the results from the laboratory experiments (c) showed that the odds for survival of A. planci larvae
was ~8-fold higher at chlorophyll levels found in CN compared with FN. Simulations of A. planci and coral
population dynamics show that in FN (d), outbreaks occur at 50 – 80 year intervals and coral cover recovers
between outbreaks (Table 4). In CN (e), outbreaks occur at 15 year intervals and corals only recover to 30-40%
of potentially obtainable values. These data form the basis to model the transition (f) in chlorophyll, A. planci
and coral cover in CN from pre-European (blue) to contemporary levels (red).
The model was used to compare the CN and FN regions using observed water quality data to
drive the populations (Fig. 6 d - f). Averaged over many generations, with distributions of
chlorophyll concentrations reflecting those in the CN inshore region (Table 3, mean
chlorophyll = 0.54 µg L
-1
), the model population formed outbreaks at 12 – 15 year intervals,
consistent with present-day outbreak frequencies and intensities in CN (Fig. 6e, Table 4).
Coral recovery between outbreaks remained incomplete, with coral cover averaging 20 – 28%
of typical maximum values. At the chlorophyll distributions recorded in the FN (mean
chlorophyll = 0.26 µg L
-1
), adult and juvenile seastar densities were 0.04 - 0.25 and 0.25 -
0.63 of CN densities respectively, outbreaks occurred only once in 50 – 80 years, and coral
cover recovered to 75 – 90% of typical maximum values between outbreaks (Fig. 6d, Table
4). Taking the relatively pristine FN as reflective of conditions ~150 years ago, a potential
transition from pristine to contemporary outbreak conditions in CN becomes apparent,
demonstrating increasing outbreak frequencies and progressively declining coral cover (Fig.
6f).
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
12
Table 3: Summer chlorophyll a concentrations on the inner (<25 km off the coast) and outer section of the
continental shelf in the far northern (FN, latitude 12 – 15.0S) and central/northern (CN, latitude 15.1 - 19.2S)
regions of the Great Barrier Reef (Brodie et al. 2007). N = number of samples. Shown are means, medians, and
the percentage of water samples with chlorophyll concentrations below 0.25 µg L
-1
and exceeding 0.5 and 0.8 µg
L
-1
.
Shelf
Region
N
Mean
(µg L
-1
± SE)
Median
(µg L
-1
)
<0.25
µg L
-1
(%)
>0.5
µg L
-1
(%)
>0.8
µg L
-1
(%)
Inner 25 km
FN
104
0.26 ± 0.01
0.25
50.0
5.8
0.0
CN
619
0.54 ± 0.02
0.38
32.0
37.0
17.8
Offshore
FN
235
0.27 ± 0.01
0.25
49.4
6.4
0.004
CN
352
0.24 ± 0.01
0.19
63.9
5.7
2.8
The model was also used to investigate the characteristics of A. planci, coral cover and the
outbreak frequencies and intensities (Fig. 7a-f). In terms of the model, outbreaks were defined
as events that reduced the coral cover to <2% and lead to mass mortality of seastars. The age
structure of the A. planci populations changed with increasing chlorophyll levels (Fig. 7a-c).
As chlorophyll increased, population sizes increased, and the age structure shifted to
relatively more young seastars. Outbreaks only occurred at chlorophyll levels above ~0.25 µg
L
-1
and seastar populations were <10% of their maximum levels (Fig 7d). At chlorophyll
levels >0.5 µg L
-1
coral cover declined by 75% of the initial cover and was dominated by
young corals with slower growth rates, the rate of growth in the coral population slowed, and
less coral was consumed (Fig. 7e - f). The maximum frequency of the outbreak waves was
one cycle per 10 – 15 years, and was controlled by the rate of coral recovery, with slower
rates resulting in lower outbreak frequencies.
Table 4. Results of simulation runs of the single-reef A. planci – coral simulation model (Fig. 6). The far
northern region (FN, latitude 12.0 – 15.0S) has little agriculture and a low human population density, whereas
the central/northern GBR (CN, latitude 15.1 – 19.2S) experiences elevated nutrient loads from rivers. Ratios
between the two contrasting regions rather than absolute values and sensitivity analyses were used to overcome
the effects of model assumptions.
CN
(Figs. 6b, e)
FN
(Figs. 6b, d)
CN/FN
Adult A. planci (mean
relative density)
40 – 63
16 – 25
1.8 – 3.2
Juvenile A. planci
(mean relative density)
4,000 – 10,000
400 – 1,000
6 – 15
Coral Cover (mean %
of typical maximum)
20 – 28
75 – 90
0.25 – 0.35
Interval between
outbreaks (yrs)
12 – 15
50 – 80
0.13 – 0.22
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
13
Figure 7. Simulation results from the population model shows the averaged effects of varying levels of mean
chlorophyll on relative population sizes of (a) larvae, (b) juveniles and (c) adults, and on (d) the frequency of
seastar outbreaks, (e) the percent of coral eaten and (f) coral cover. Results are averages over model runs
spanning 200 years and excluding a 20-years ‘burn-in’ period.
Finally the data on reef connectivity and their source, sink and self-seeding levels were related
to seastar population and outbreak intensities. We found that:
(1) Patterns of inter-reef connectivity had far less effect on the large-scale wave-like patterns
of secondary outbreaks than differences in chlorophyll concentrations. Provided there is at
least a low level of connectivity amongst reefs, further increases in the strength of
connectivity had little effect on the outbreak patterns.
(2) At the scale of individual reefs, the risk of a reef having a severe A. planci outbreak
increased with its capacity to retain larvae through self-seeding and acting as a sink, and
decreased with its capacity to reduce larvae by acting as a source. Thus, reefs that were
the origin of outbreaks needed not outbreak themselves, and hence reefs where primary
outbreaks are first observed may not be the source of the outbreak. Furthermore, reefs that
were predominantly sources of larvae (i.e., had low larval retention) were four times less
likely to outbreak than reefs that retained more of their larvae.
Discussion
Identifying the causes of ecological patterns and distinguishing anthropogenic changes from
natural dynamics is exceedingly complex, but synthesis of information from various sources
such as experiments, field surveys, long term monitoring and simulation models can form a
basis for attribution of causality (Fabricius and De'ath 2004). Using this approach, our study
adds new and strong support to the hypothesis that food availability controls primary
outbreaks of A. planci by enhancing the survival of larvae. It is important to differentiate
between the different processes that govern population dynamics on the three reef ‘types’
(source reefs, primary outbreak reefs, and secondary outbreak reefs). Primary outbreaks can
arise from small populations living on source reefs that encounter highly productive waters
during spawning times. Hydrodynamics dictate that source reefs may be located either
upstream of the primary outbreak reefs, or become primary outbreak themselves reefs through
self-seeding. However both source and primary outbreak reefs are likely to experience
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
14
seasonal phytoplankton blooms as the larvae together with the phytoplankton move with the
currents. Following these primary outbreaks, secondary outbreaks are then observed on
individual reefs in downstream progressing waves (Moran 1986; Moran et al. 1992,
Sweatman et al. 2008) that can be reconstructed using hydrodynamic models (Dight et al.
1990, our A. planci model). Primary outbreaks therefore develop from a small source
population of starfish, with each mature starfish producing an extremely large number of
offspring due to the release of larval food limitation. In contrast, secondary outbreaks
comprise a large population of mature starfish and hence can sustain outbreaks in conditions
where larval survival is relatively low.
Our larval feeding experiments showed a strong and non-linear (logistic) dose-response
relationship between the availability of natural eukaryotic phytoplankton and larval
development success. By using unfiltered natural seawater, the larvae in our experiments
grew in conditions where both phytoplankton food and potential planktonic predator
communities underwent natural successions in response to nutrient availability. We
demonstrated larval food availability to be a strong driver, with low chlorophyll leading to a
low rate of developmental completion, a prolonged pelagic phase of the larvae and small sizes
of the post-metamorphosis juveniles, likely leading to higher pre- and post-settlement
mortality (Allison 1994). The role of larval food limitation to echinoderm population
dynamics in the field is also corroborated by the observation that only echinoderm groups
with planktotrophic larvae have the propensity to exhibit boom and bust population dynamics,
while echinoderms with non-feeding (lecitotrophic) larvae have more stable populations
(Uthicke et al. 2009).
Identifying the origin of A. planci primary outbreaks is key to successful management of the
GBR. The first two outbreaks were first detected at Green Island off Cairns (Moran et al.
1992), a major tourist destination that was more frequently visited than many other reefs near-
by. The third outbreak was first reported from Lizard Island in October 1993 and 10-11
months later from 7 other reefs in the Cairns and Lizard Island regions (16013C, Evening
Reef, Swinger, Startle, Mackay, North Direction and Macgillivray Reefs), with a number of
additional reefs having A. planci densities only slightly below outbreak threshold levels in
1994 (LTMP data, not shown). The multiple outbreak locations, and the multiple A. planci
size classes (including juveniles) observed at Lizard Island in 1996 (Pratchett 2005) suggested
a gradual population build-up in the whole region through several successful spawning events
in prior years, indicating that not only the large 1991 flood but also conditions in following
years provided conditions suitable for high recruitment success. Floods have reached or
crossed this part of the shelf in 1991, 1994, 1995 and 1996 (Devlin and Brodie 2005),
retention times of flood materials on the continental shelf may be long (Luick et al. 2007), and
chlorophyll levels frequently exceed 0.5 and even 0.8 µg L
-1
(Table 3). The weak and
bidirectional currents may further increase the vulnerability of reefs in this region to develop
outbreaks due to their relatively high rates of larval retention and self-seeding (James et al.
2002).
Long-term average chlorophyll values on the inner 25 km were twice as high in CN compared
to FN. As offshore chlorophyll values were similar in both regions, it is unlikely that the high
CN chlorophyll values were attributable to latitude or upwelling (Brodie et al. 2007). In CN,
present river loads of nutrients and sediments are estimated to be 2 – 10 fold higher than
before western colonization in ~1860, while river loads in the sparsely inhabited FN are
considered largely unaltered (McKergow et al. 2005). As rivers are the main source of new
nutrients to GBR inshore waters, regional differences in chlorophyll have been attributed to
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
15
differences in river nutrient loads, reflecting past and present terrestrial runoff (Devlin and
Brodie 2005; Brodie et al. 2007), although an explicit link between increasing river loads and
changes to inshore water quality on the GBR has not been established.
The fact that primary A. planci outbreaks occurred on locations where floods intercepted large
reefs on the GBR three to five years earlier, shows that not only long-term chlorophyll
concentrations but also large floods are a strong driver for A. planci primary outbreaks, in
agreement with previous findings (Birkeland 1982, Brodie et al. 2005). Flood plume models
(King et al. 2001) showed that the 1974 and 1991 floods reduced salinity for >60 days during
the time when A. planci larvae are pelagic. Due to the high incidence of cloud cover during
and after rain events, few satellite images are available to track the spread of flood plumes.
However, Devlin and Brodie (2005) used aerial surveys to show a spreading of plumes into
the main reef matrix, similar to the patterns shown in Fig. 5, after cyclones in 1996 and 1999,
and to an even greater extent in 1994. These river floods are the largest source of new
nutrients for the inshore GBR, and trigger phytoplankton blooms that average 2 µg L
-1
chlorophyll and at times exceed 4 µg L
-1
(Devlin and Brodie 2005). The application of
experimental findings to field settings necessitates caution. Bearing this in mind, if we take
the experimentally observed rates of change as indicative of the relative differences in
developmental rates in the field, the odds of successful development of A. planci larvae could
be up to ~60-fold higher during floods with 2.0 µg L
-1
chlorophyll compared to the long-term
average of 0.54 µg L
-1
for the central/northern GBR.
In combination, the three components of this study, together with previous evidence
(Birkeland 1982; Brodie et al. 2005), strongly support the assertion that removal of larval
food limitation causes primary population outbreaks of A. planci on the GBR. In contrast to
the parsimonious explanation of food limited control of A. planci populations, explanations of
population control by predators rely on complex arguments (Birkeland and Lucas 1990). To
date, there is no empirical evidence to support these arguments. Unlike water quality,
predation pressure does not fluctuate widely on short time scales, hence it remains unclear
how a chronic release from predation would occasionally lead to sudden increases in
population densities. However the reported correlation between reef protection status and A.
planci outbreaks on a subset of GBR reefs (Sweatman 2008) suggests that both hypotheses
may not necessarily be exclusive, and that predation may play some additive role in
determining the propensity of individual reefs to be afflicted by A. planci outbreaks.
Coastal GBR water quality is considered amenable to benefit from improved land
management (Haynes et al. 2007) due to the dominant role of the rivers in providing new
nutrients to the inshore GBR, and the potentially long residency times of these newly
imported materials (Luick et al. 2007). Large and early river floods from the Burdekin and
Wet Tropics rivers occurred again in January 2008 and 2009 (Fig. 4), potentially providing
conditions to trigger a new A. planci primary outbreak wave that may again kill a significant
proportion of GBR corals. Our study suggests that reductions in phytoplankton biomass to
summer values of <0.5 µg L
-1
(De'ath and Fabricius 2010) through better land management
could reduce the frequency of primary A. planci outbreaks. Legislation and incentives have
now been put in place to reduce river discharges of nutrients, sediments and pesticides from
agricultural areas. However until a reduction in nutrient levels is achieved, two additional
precautionary management measures should aim to maintain very low A. planci densities in
the high-risk area (the midshelf reefs and hard bottom inter-reefal areas that are directly
intercepted by floods). These are: (a) large permanent fishing closures in the high-risk area,
allowing fish populations to reach carrying capacity to safeguard against cascading changes in
Coral Reefs (2010): Volume 29, pp 593-605: A. planci outbreaks and phytoplankton
16
food webs, and (b) potentially some targeted efforts by divers, especially in the years
following large floods, to remove some of the A. planci before they start to aggregate and
spawn, This three-pronged approach constitutes the best presently available strategy to slow
or reverse the loss of coral cover throughout the whole central and southern GBR, at a time
where rising seawater temperatures exert increasing pressure on coral reefs, and increasing
climatic instability may increase the frequency of extreme floods.
Acknowledgments
Many thanks to the GBR Long-Term Chlorophyll Monitoring Program for the chlorophyll data, to the AIMS
Long-Term Monitoring Program for coral cover and A. planci field distribution data, to J. Scandol for
compilation of the A. planci life history data, and to M. Slivkoff for the processing of the Modis satellite image.
KO conducted the laboratory experiments, and GD developed the coral – A. planci simulation model. We
gratefully acknowledge support for the experimental study by T. Ayukai and J. Lucas. We thank J. Caley, B.
Schaffelke, S. Uthicke and H. Sweatman for constructive comments on earlier versions of the manuscript, and J.
Brodie, K. Day and E. Wolanski for sharing ideas. The study was funded by the Marine and Tropical Sciences
Research Facility (MTSRF) and the Australian Institute of Marine Science, with the experimental study being
funded by the Great Barrier Reef Marine Park Authority and James Cook University.
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