The use of butterflyfish (Chaetodontidae) species richness as a

Transcription

AQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS
Aquatic Conserv: Mar. Freshw. Ecosyst. 15: S127–S141 (2005)
Published online in Wiley InterScience
(www.interscience.wiley.com). DOI: 10.1002/aqc.692
The use of butterflyfish (Chaetodontidae) species richness
as a proxy of total species richness of reef fish assemblages
in the Western and Central Pacific
M. KULBICKI* and Y. M. BOZEC
IRD } Universite´ de Perpignan, 66860 Perpignan, France
ABSTRACT
1. A new use of butterflyfishes (Chaetodontidae) is proposed for monitoring programmes, based
on the relationship existing between the total species richness of reef fish assemblages and the species
richness of butterflyfishes. These two variables are highly correlated and it is possible under certain
circumstances to predict the total species richness of a reef fish assemblage from the butterflyfish
species richness.
2. In the present study, the effects on this relationship of three regions (Tuamotu, Tonga, New
Caledonia), eight islands, two reef types (barrier and fringing reefs) and coral cover were investigated
based on 544 transects. The effect of time was also tested based on 108 transects (12 stations 9
trimesters).
3. Coral cover had no statistically significant effect on the relationship; both slope and intercept of
the relationship varied with region.
4. Islands were a significant factor in Tonga and New Caledonia, but not in Tuamotu.
5. On fringing reefs the correlations were higher and the linear regressions had flatter slopes and
lower intercepts than on barrier reefs, while the correlations between total species richness and
butterflyfish species richness were not influenced by time over a 30-month period.
6. The potential applications of this relationship for monitoring programmes are discussed on the
basis of these results and on a power analysis relating butterflyfish diversity and the correlation level
of this relationship.
Copyright # 2005 John Wiley & Sons, Ltd.
KEY WORDS:
species richness; monitoring; Chaetodontidae; Pacific; coral reef
INTRODUCTION
Chaetodontidae (butterflyfishes) are probably the most extensively sampled reef fish family in the IndoPacific to date. The purposes of these studies range from biological (diet and behaviour mainly) (e.g.
Harmelin-Vivien and Bouchon-Navaro, 1983; Sano et al., 1984; Bouchon-Navaro, 1986; Findley and
*Correspondence to: M. Kulbicki, IRD } Université de Perpignan, 66860 Perpignan, France. E-mail: [email protected]
S128
M. KULBICKI AND Y.M. BOZEC
Findley, 1989, 2001; Harmelin-Vivien, 1989; Motta, 1989; Roberts and Ormond, 1992; Cox, 1994;
Chabanet et al., 1997; Lewis, 1998), to ecological (especially relationships between butterflyfishes and their
environment) (e.g. Bell et al., 1985; Sano et al., 1987; Bouchon-Navaro and Bouchon, 1989; Fowler, 1990;
Roberts et al., 1992; Cadoret et al., 1999), or biogeographical (Blum, 1989; Findley and Findley, 2001).
Butterflyfishes are also an increasing part of reef monitoring programmes at the national (e.g. Great Barrier
Reef Marine Park Authority and Australian Institute of Marine Sciences monitoring programmes in
Australia), regional (e.g. PROCFISH programme by South Pacific Commission) and international (e.g.
Global Coral Reef Monitoring Network) levels. It has also been proposed that butterflyfishes might be used
to monitor the ecological status of coral reefs (Reese, 1981; Bouchon-Navaro et al., 1985; Hourigan et al.,
1988; Roberts et al., 1988; White, 1988; Crosby and Reese, 1996; Erdman, 1997; Öhman et al., 1998; Khalaf
and Crosby, 2005; Temraz and Abou Zaid, 2005; Samways, 2005). Most of the interest in these fish stems
from: (1) their relationship with coral, as a number of these species are coral-dependent; (2) the ease of
identification; (3) the ease of censusing; and (4) their very wide geographical range. Despite the fact that
their relationship to coral has been rather well studied (e.g. Reese, 1977, 1981; Bell and Galzin, 1984; Bell
et al., 1985; Roberts et al., 1988; White, 1988; Cadoret et al., 1995, 1999; Öhman et al., 1998; Findley and
Findley, 2001), the use of these fish in general reef monitoring is often ill-defined and their use for reef
ecological monitoring is open to debate (Erdman, 1997; Öhman et al., 1998). For these reasons it is
important to explore new applications for using these fishes.
Bell and Galzin (1984) found that several fish families, including butterflyfishes, as well as entire reef fish
assemblages showed positive correlations with coral cover. Since there were good correlations between total
reef fish species richness (SR) and coral cover and similar correlations between butterflyfish SR and coral
cover, there should be links between total reef fish SR and butterflyfish SR. If such relationships exist and
are highly significant, then butterflyfish SR could be used as a proxy of total reef fish SR. If this hypothesis
proves to be correct under a wide enough range of circumstances, then the use of butterflyfishes might
expand to include the spatial comparison of reef fish assemblages, monitoring of a reef over time, wider
biogeographical studies, and a wider range of ecological studies than those for which they are currently
used.
To demonstrate that butterflyfish SR may in some circumstances be used as a proxy of total reef fish
assemblage SR, this paper has four goals:
1. To demonstrate that the relationship between total reef fish SR and butterflyfish SR is highly significant
and that the confidence intervals are sufficiently narrow to enable useful predictions of total reef fish SR
from observed butterflyfish SR.
2. To analyse the variations of this relationship at various spatial scales. Kulbicki et al. (2005) show that
the relative importance of butterflyfishes to the total reef fish species pool is a function of the total
number of species, so that the higher the number of species known on an island, the lower is the
proportion of butterflyfishes. In addition these authors found that the biological and ecological
characteristics of the butterflyfish regional species pool and of the butterflyfishes observed on a given
island may not correspond. These findings suggest that the relationship between total reef assemblage
SR and butterflyfish SR may be a function of the region, island and biotope.
3. To test whether the relationship between total reef fish assemblage SR and butterflyfish SR is sensitive to
the level of coral cover. Since coral cover is known to influence both total reef assemblage SR and
butterflyfish SR (Reese, 1981; Harmelin-Vivien and Bouchon-Navaro, 1983; Bell and Galzin, 1984;
Bouchon-Navaro and Bouchon, 1989; Chabanet et al., 1997; Cadoret et al., 1999; Jones et al., 2004), and
because several species of butterflyfishes are obligate coral feeders with their diversity linked to coral
cover, it will be useful to test whether the ratio of Nchaet species of butterflyfishes to Ntot species for the
entire reef fish assemblage in an area with low coral cover is the same as in an area with a high
coral cover.
BUTTERFLYFISH SPECIES RICHNESS IN WESTERN AND CENTRAL PACIFIC
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4. To analyse whether time variations are important, and in particular, whether they are more important
than spatial ones. In order to be useful in monitoring programmes, this relationship has to be stable
through time for a given area.
Finally the conditions and limits of use of these first findings and the circumstances in which these
relationships were found to be of interest for developing proxies of total reef fish assemblages, will be
discussed.
METHODS
The data analysed in this study came from various experiments conducted across the Pacific using the same
sampling procedures. Three regions were visited } Tuamotu (French Polynesia), Tonga, and New
Caledonia. They are at least 2000 km distant from one another and have decreasing numbers for total
species numbers (Table 1). Several islands were sampled within each of these regions. All the data analysed
came from Underwater Visual Censuses (UVC) transects. These transects were 50 m long and placed in
such a way that the habitat covered was as homogeneous as possible. For each transect the following
parameters were recorded: biotope (fringing or barrier reef), coral cover (as percentage of bottom cover),
number of butterflyfish species (butterflyfish SR), and number of all other fish species which could be
observed (total SR).
The sampling design is given in Table 2. All transects were included in one general linear model (GLM)
model:
SRtotal ¼ X þ C þ F þ X F þ e
Table 1. Total reef fish diversity and butterflyfish diversity of the three regions studied
Number of species
New Caledonia
to Tonga: 2000 km
to Tuamotu: 5000 km
Tonga to
New Caledonia: 2000 km
to Tuamotu: 3000 km
Tuamotu to
New Caledonia: 5000 km
to Tonga: 3000 km
Total
Chaetodontidae
% Chaetodontidae
1545
32
2.07
834
29
3.48
544
26
4.78
Table 2. Number of transects according to reef type (fringing or
barrier), region (New Caledonia, Tonga or Tuamotu) and islands
Fringing
Barrier
New Caledonia
Main Island
Uvea Atoll
88
0
69
96
Tonga
Tongatapu
Hapai
Vavau
5
15
23
22
19
11
Tuamotu
Kauehi
Marokau
Nihiru
0
0
0
64
64
68
Total
131
Total
253
95
196
413
544
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where X is butterflyfish SR, C is coral cover and F is the factor which characterizes the transect; F will be
expressed as Region Island Reef-type with Reef-type crossed with Island and Region, whereas Island is
nested in Region.
If X is significant then total SR and butterflyfish SR are linked by a linear relationship; and if F is
significant then the intercept of at least two combinations of the factors making F are significantly different;
and if X F is significant then the slope of at least two combinations of the factors making F are
significantly different.
To test the separate effects of region and reef type on the relationship between total SR and butterflyfish
SR a covariance analysis restricted to Tonga (all islands) and New Caledonia (Main Island only) was
conducted according to the model:
SRtotal ¼ SRbutterflyfish þ Region þ Reef-type þ Region Reef-type þ e
The effects of time variations were tested only for the fringing reefs of New Caledonia’s largest island.
This analysis was performed on 12 stations (S) in which reef fish assemblages were sampled every three
months over a period of 30 months, with one sampling period skipped due to bad weather conditions
ð12 9 ¼ 108 transectsÞ. Coral cover was not included in this analysis as this variable did not change
significantly within stations over the time period tested. The effect of time was tested in two steps. First,
whether there was a relationship between total SR and butterflyfish SR for all stations and within stations
through time. The covariance model was:
SRtotal ¼ X þ S þ X S þ e
Second, if time changed this general relationship by applying a second model:
SRtotal ¼ X þ T þ X T þ e
in which T is the trimester.
RESULTS
Spatial comparisons
The simple correlation between total reef fish SR and butterflyfish SR was highly significant (r2 ¼ 0:61 for
N ¼ 534, p5108 ). The correlations between total SR (r2 ¼ 0:107, p5104 ) with coral cover and
butterflyfish SR (r2 ¼ 0:23, p5104 ) with coral cover were also highly significant, but less so. A multiple
regression relating total reef fish SR to both butterflyfish SR and coral, however, indicates that coral cover
was not a significant factor once butterflyfish SR is taken into account. (total r2 ¼ 0:61; Fcoral ¼ 3:7,
pcoral ¼ 0:06; FSRbutterflyfish ¼ 697, pSRbutterflyfish 5108 ).
These correlations do not take into account the fact that several factors play a significant role as
indicated by the result of the GLM (1) in Table 3. This model confirms the highly significant correlation
between total SR and butterflyfish SR and the nonsignificant role of coral cover once butterflyfish SR was
taken into account. In addition, it shows that region, island and reef type play significant roles in these
relationships. Each factor was examined separately and then the various interactions by a covariance
analysis and graphically.
First, each region yielded a significantly different slope and intercept (Figure 1), with Tonga having the
highest values and Tuamotu the lowest. In order to avoid differences between regions due to unequal
proportions of each reef type within each region, only barrier reefs were considered for this figure (as they
were common to all three regions), but similar findings were found also for fringing reefs between Tonga
and New Caledonia (Table 4).
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Table 3. Major results of the model (1) relating total SR to butterflyfish SR and coral cover according to region, island and reef type.
: 0:05 > p > 0:001; : 0:001 > p > 0:0001; : p50:0001
Intercept
Butterflyfish SR
Coral cover
Region : Tonga
Region : Tuamotu
Island : Hapai
Island : Kauehi
Island : Marokau
Island : Ouvea
Island : Tongatapu
Reef : fringing
Region : Tonga: Reef : fringing
Island : Hapai : Reef : fringing
Island : Tongatapu : Reef : fringing
Estimate
Standard-error
t-value
40.113
2.96
0.0124
7.86
24.25
2.52
1.30
1.069
5.62
15.32
20.94
12.19
3.75
22.24
1.84
0.17
0.034
3.52
2.12
4.091
1.924
1.937
1.840
3.98
1.86
4.40
5.45
6.63
21.7
17.2
0.36
2.23
11.4
0.61
0.67
0.55
3.05
3.84
11.2
2.769
0.688
3.350
***
***
*
***
**
***
***
**
***
120
100
All Species
80
60
40
New Caledonia
Tonga
20
Tuamotu
0
0
5
10
15
20
Number of Butterflyfish Species
Figure 1. Relationship between total SR and butterflyfish SR for the barrier reefs of the three regions, without taking island into
account. Each point represents a transect. ‘All Species’: all observed species with butterflyfishes excluded. The plain line is for
New Caledonia, the dashed line for Tonga and the dotted line for Tuamotu.
The analysis of the effect of reef types indicated that this factor has a very significant effect on the
relationship between total SR and butterflyfish SR (Tables 3 and 4). This effect was not the same between
regions and between islands (Table 3). Differences between regions (Table 5) were examined using a
covariance analysis limited to Tonga and New Caledonia where both reef types were sampled. The
covariance analysis confirmed the highly significant differences between regions for this factor. Differences
within regions were also significant (Table 5) as illustrated by Figure 2. Within Tonga there were significant
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Table 4. Major parameters of the regressions within cells of model (1) which make a significant contribution to the model (e.g. the
islands from Tuamotu are not given separately as they are not significantly different from one another). N: number of transects;
r=correlation coefficient; p=probability of accepting H0 (there is no linear relationship between total SR and butterflyfish SR)
Region
Island
New Caledonia
Reef-type
Ouvea
Main Island
Main Island
Hapai
Vavau
Vavau
Tongatapu
All
Tonga
Tuamotu
N
Barrier
Barrier
Fringing
Fringing
Fringing
Barrier
Barrier
Barrier reef
r
96
69
88
15
23
11
22
189
p
6
0.52
0.35
0.87
0.75
0.75
0.74
0.74
0.68
510
0.0035
5106
0.0011
0.000 04
0.0097
0.000 69
5106
Intercept
Slope
40.49
51.75
13.49
34.11
28.96
40.91
37.95
14.30
2.22
1.53
3.97
4.79
4.27
3.98
2.39
3.60
Table 5. Covariance analysis restricted to Tonga (all islands) and New Caledonia (Main Island only) testing the
differences in the relationship between total SR and butterflyfish SR according to region and reef type, the model
used being: SRtotal ¼ SRbutterflyfish þ Region þ Reef-type þ Region Reef-typeþe
Intercept
Butterflyfish SR
Region
Reef-type
Region*Reef-type
Error
Degrees of
freedom
Estimates
F
Probability (>|t|)
1
1
1
1
1
343
36.08
2.860 61
7.191 17
4.512 39
4.387 64
489
216
81.4
31.5
30.5
5106
5106
5106
5106
5106
Tonga
New Caledonia
120
120
100
80
80
All Species
All Species
100
60
60
40
40
Barrier
Fringing
20
20
Barrier
Fringing
0
0
0
5
10
15
Number of Butterflyfish species
20
0
5
10
15
20
Figure 2. Relationship between total SR and butterflyfish SR for the two reef types according to region. Slopes and intercepts are
significantly different in each case. Each point represents a transect. ‘All Species’: all observed species with butterflyfishes excluded. The
dashed lines correspond to fringing reefs, the plain lines to barrier reefs.
differences for this relationship between and within islands as well (Table 3; Figure 3) according to reef
type.
Within each region, islands were not necessarily a significant factor. In particular, in Tuamotu, the three
islands sampled showed no difference in either slope or intercept (Tables 3 and 4), whereas in Tonga and
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Hapai
120
120
100
100
80
80
All Species
All Species
Vavau
60
40
Barrier
40
Barrier
Fringing
Fringing
20
60
20
0
0
0
5
10
0
15
5
10
15
Figure 3. Relationship between total SR and butterflyfish SR for the two reef types according to island in Tonga. Slope and intercept
are significantly different for Hapai, only the intercept is significantly different for Vavau. Each point represents a transect. ‘All
Species’: all observed species with butterflyfishes excluded. The dashed lines correspond to fringing reefs, the plain lines to barrier reefs.
Tonga
120
100
100
80
80
All Species
All Species
New Caledonia
120
60
60
40
40
Hapai
20
Vavau
20
Ouvea
Tongatapu
Main Island
0
0
0
5
10
15
20
0
5
10
15
20
Figure 4. Relationship between total SR and butterflyfish SR for different islands within a region, reef type being restricted here to
barrier reefs. Slopes and intercepts are significantly different between Ouvea and Main Island; intercepts are different between Hapai
and Vavau or Tongatapu, whereas slopes are different between Tongatapu and Vavau. Each point represents a transect. ‘All Species’:
all observed species with butterflyfishes excluded. The dashed lines correspond to either ‘Main Island’ or Vavau, the plain lines to either
Ouvea or Hapai and the dotted line to Tongatapu.
New Caledonia, there were differences (Tables 3 and 4). In order to illustrate such differences between
islands within a region, the reef type has to be similar; e.g. for barrier reefs within New Caledonia and
Tonga (Figure 4). In particular, the relationships were different for each island.
The general model indicated that reef type is an extremely significant factor (Tables 3 and 4), but did not
make it possible to say how fringing and barrier reef stations are different in their intercepts and slopes as
this factor interacts with region and island. Comparison of the slopes and intercepts of each significant cell
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Fringing
120
100
100
80
80
All Species
All Species
Barrier
120
60
40
y = 2.05 x + 45.61
R = 0.46
20
0
60
40
y = 4.47 x + 17.33
R = 0.77
20
0
0
5
10
15
20
0
5
10
15
20
Figure 5. Relationship between total SR and butterflyfish SR for the two reef types, without taking into account region or island. Each
point represents a transect. ‘All Species’: all observed species with butterflyfishes excluded.
(Table 4) suggests that the intercepts are higher and slopes more gentle for barrier reefs than for fringing
reefs. Grouping all barrier reef stations versus all fringing reef stations (without taking into account region
or island) confirms this trend (Figure 5), with the relationship more significant for fringing reefs than for
barrier reefs.
Temporal comparisons
The analysis of time series data was a two-step process. First, significance of the relationship between total
SR and butterflyfish SR was determined using model (2). This analysis indicated that the relationship
between total SR and butterflyfish SR was highly significant when all transects were considered and that
there were significant differences between stations for this relationship (Table 6). Second, the influence of
time on this relationship was tested and no significant global effect was found (Table 7). On a case by case
basis, there was a significant effect of trimester seven; i.e. the slope or intercept of the relationship between
total SR and butterflyfish SR did not change from one trimester to the next (Figure 6; Table 7), except for
trimester seven. The exception represented by the trimester 7 was linked to the recruitment of many small
reef species during that period (March).
Power analysis
In order to give an indication of the predictive potential of the relationships between total SR and
butterflyfish SR, a power analysis was performed on the data from Tonga and New Caledonia (Figure 7).
For Tonga the power was lower than for New Caledonia, but this was related to the sampling effort which
was nearly three times larger for New Caledonia. The top curves (Figure 7(a)) give the variations in
predicted number of species. It shows in particular that the predicted range for the fringing reefs of New
Caledonia was narrower than for the barrier reefs in that region, but it is the opposite for Tonga. However,
these top curves do not take into account the number of observed butterflyfishes. Indeed, if the number of
butterflyfish species is low, and even if the confidence interval is narrow, it may represent a sizeable amount
of the total SR. This is illustrated by the bottom power curves (Figure 7(b)), with a somewhat
counterintuitive result. The power for the New Caledonian fringing reefs was lower than for the barrier
reefs of that region, despite a much better correlation between total SR and butterflyfish SR (Table 4). This
drop in power was linked to the low numbers of butterflyfish species observed on these fringing reefs (5.8
species on average) compared to barrier reefs (7.7 for Ouvea, 8.2 for the Main Island). For Tonga the best
S135
Table 6. Covariance analysis of model (2) testing the effect of stations on the relationship between total SR and
butterflyfish SR
Degrees of
freedom
Intercept
Butterflyfish SR
Station
1
1
11
Estimates
37.02
1.024
MS
F
Probability (>|t|)
6921
276
564.3
174.9
6.98
14.26
5106
0.0096
5106
0.000 37
5106
0.34
0.41
0.029
5106
0.000 043
0.91
0.0068
0.22
0.000 001
7.49
18.81
2.09
1.62
4.49
13.09
8.82
0.22
7.91
2.49
11.78
Error
95
39.556
Table 7. Covariance analysis of model (3) testing the effect of time (trimesters) on the relationship between total
SR and butterflyfish SR
Degrees of
freedom
Intercept
Butterflyfish SR
Trimester
1
1
8
Estimates
MS
F
Probability (>|t|)
25.2
2.69
10 088
6 738
146
112.4
75.0
1.62
5106
5106
0.12
0.067
0.90
0.22
0.24
0.38
0.67
0.0084
0.76
4.7
0.30
3.1
3.04
2.24
1.06
6.94
0.76
Error
98
89.75
power curve in species number (Figure 7(a)) was for the barrier reef which also has the highest diversity of
butterflyfishes (8.9 species on average, versus 6.3 to 7.9 for fringing reefs). Therefore the order of the power
curves for Tonga stays the same for the two types of curves (Figures 7(a) and (b)).
DISCUSSION
Butterflyfishes, especially coral feeding species, have been repeatedly proposed as indicators of the
ecological status of coral reefs (Reese, 1981; Hourigan et al., 1988; Crosby and Reese, 1996; Crosby and
Reese, 2005; Khalaf and Crosby, 2005; Temraz and Abou Zaid, 2005; Samways, 2005). They have a
number of qualities essential to indicators for management purposes } they are easy to recognize, they are
S136
90
80
60
9 2
10
6
50
8
7
4
3
5 1
40
30
9
10
70
12
11
2
7
1
12
9
6
3
3
5
8 4
10
12
11
7
2
11
8
6
4
1
5
20
10
0
2
4
6
8
10
12
14
16 0
2
4
TRIMESTRE: 1
6
8
10
12
14
16 0
2
4
TRIMESTRE: 2
6
8
10
12
14
16
TRIMESTRE: 3
90
All Species
80
70
2
60
10
5 1 7
50
40
12
30
8
6
3 8
9
4
5
11
4
11
7 1
6
12
9
10
6
3
2
10
12
1
2
9
4
5
8
3
7
11
20
10
0
2
4
6
8
10
12
14
16 0
2
4
TRIMESTRE: 4
90
8
10
12
14
16 0
2
4
TRIMESTRE: 5
6
8
10
12
14
16
TRIMESTRE: 6
2
80
6
9
70
50
12
7
2
12 11
30
5
7
3
5
4
1 7
11
12
9
6
10
8 3
1
10
4
2
6 9
3
10 4
8
11
1 5
60
40
6
8
20
10
0
2
4
6
8
10
12
14
TRIMESTRE: 7
16 0
2
4
6
8
10
12
14
TRIMESTRE: 8
16 0
2
4
6
8
10
12
14
16
TRIMESTRE: 9
Figure 6. Relationship between total SR and butterflyfish SR for 12 fringing reef stations in New Caledonia (the numbers on the charts
represent the stations identification numbers), each station being sampled every trimester over 30 months (nine replicates). Trimester 7
has a significantly higher intercept than the other trimesters (Table 7).
easy to detect and census, they are site attached, and they are probably long-lived (for example, Chaetodon
larvatus could reach 14 years according to Zekeria (2003)). The use of these fishes as indicators of the
ecological status of reefs is, however, a source of debate (Erdman, 1997; Öhman et al., 1998). These fishes
are currently sampled in a number of monitoring programmes (Kulbicki et al., 2005), but so far, there is no
specific use for the data collected. In most instances, butterflyfish diversity or abundance is correlated with
coral cover or diversity. However, these programmes as well as a large number of other field works have
generated a wealth of data on their distribution (e.g. Bouchon-Navaro, 1981; Bell et al., 1985; Findley and
Findley, 1989, 2001; Fowler, 1990; Roberts et al., 1992; Cadoret et al., 1995, 1999), behaviour (e.g.
Bouchon-Navaro, 1986; Driscoll and Driscoll, 1988; Roberts and Ormond, 1992; Cox, 1994) and
relationship with environmental variables (e.g. Bell and Galzin, 1984; Bouchon-Navaro et al., 1985;
Jennings et al., 1996; Chabanet et al., 1997; Öhman et al., 1998; Zekeria, 2003). The present study shows
that these fishes may, in a number of circumstances, be good proxies of the species richness of the entire fish
assemblage. Total species richness has a number of uses in ecology, e.g. exploring issues related to the
resistance, resilience and stability of communities (Peterson et al., 1998) diversity–biomass relationships
and production potential (Kulbicki et al., 2004), biogeography (Hillebrand and Blenckner, 2002). Our
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50
50
NEW CALEDONIA
40
Hapai-Fringing
Ouvea
Delta Total SR
Delta Total SR
TONGA
45
40
Barrier
30
Main Island
Fringing
20
35
30
Vavau-Fringing
25
Tongatapu-Barrier
20
15
10
10
5
0
0
5
10
(a)
15
20
25
30
35
40
0
45
5
10
Probability level (x100)
15
20
30
35
40
45
80
80
TONGA
NEW CALEDONIA
70
70
60
60
Delta SR Total as %
Delta Total SR as %
25
Probability Level (x100)
Barrier
50
Main Island
Fringing
40
30
Ouvea
20
Hapai-Fringing
50
Vavau-Fringing
40
30
20
Tongatapu-Barrier
10
10
0
5
10
(b)
15
20
25
30
Probality Level (x100)
35
40
45
0
5
10
15
20
25
30
35
40
45
Probability Level (x 100)
Figure 7. Power analysis indicating for New Caledonia and Tonga the expected variations in predicted values of total SR from
butterflyfish SR for increasing probability levels (probability of rejecting H0 that the confidence interval based on the predicted
value contains the true value). The y-axis represents the width of the confidence interval for the predicted values for the mean
observed butterflyfish SR. Top graphs, indicate results as number of species; the lower graphs indicate results as a percentage of the
mean total SR.
discussion focuses on the quality and limits of butterflyfishes as such proxies, recalls the precautions
necessary in using butterflyfishes for this purpose, and examines some potential applications.
Large-scale factors
Total reef fish SR is highly correlated to butterflyfish, however, this correlation varies according to many
factors, in particular, region, island, and reef type. This strongly suggests that these factors should be taken
into account for any use of this relationship. In particular, it will be especially important not to compare
heterogeneous areas using the same relationship as this could lead to serious errors. To illustrate this, a new
observation of seven butterflyfish species on a transect results in a prediction of 48 reef fish species on that
transect for the fringing reefs of New Caledonia, but 69 species on the barrier reefs of the same island.
Another important point is that this relationship will be best used in areas where the observed number of
butterflyfish species is high, since it is at the highest densities that the power of this relationship is best. Also,
regional diversity is not necessarily a good predictor of local diversity, as indicated by Findley and Findley
S138
(2001) and by Kulbicki et al. (2005), therefore countries with high regional diversities of butterflyfishes such
as Indonesia, the Philippines (Findley and Findley, 2001) or New Caledonia (Kulbicki et al., 2005) may not
have the highest observed local butterflyfish diversities, and therefore the relationship between total SR and
butterflyfish SR in these places may have a lower power than would may be expected by just considering
regional diversity. Similarly, within a country, this relationship will be best used in biotopes with high
butterflyfish diversities, e.g. on barrier reefs rather than on fringing reefs.
It is notable that some factors are influential but not others. Regional differences could stem from the
relationships existing between meta-communities and local communities (Hillebrand and Blenckner, 2002),
the SR of local communities usually being well correlated at the level of the meta-community. Table 1 and
Kulbicki et al. (2005) indicate that the relative importance of butterflyfishes to the regional metacommunity varies according to the region. It would be interesting to test whether the effect of the region on
the total SR – butterflyfish SR relationship could be predicted to some extent from the number of species
found within the region. It could be expected that the larger the relative contribution of butterflyfishes to
regional diversity, the steeper will be the slope of the relationship between total SR and butterflyfish SR, as
confirmed by this present study, with Tuamotu having the steepest slope and New Caledonia the flattest
(Table 4). Additional regions, however, would ideally need to be tested to validate such an hypothesis.
Differences between islands may be expected as the diversity of the reef fish meta-community at the island
level is a function of factors such as island size, island type or the connectivity with other islands (Bellwood
and Hughes, 2001; Kulbicki et al., 2004). The role of these factors on the relationship between total SR and
butterflyfish SR could be tested and even probably be predicted from a statistical model; however, as for the
effect of regions, this would require more islands than have been tested so far. The effect of reef type was
significant in the two cases where it could be tested formally, New Caledonia and Tonga (Table 3). Fringing
reefs offered steeper slopes, lower intercepts and stronger correlations than barrier reefs. In both cases
(Tonga and New Caledonia), the number of known species was higher on barrier reefs than fringing ones.
Therefore, flatter slopes and lower intercepts on fringing reefs would be expected. As only the intercept
agrees with what is expected, other factors have to come into play in this relationship. One possible
explanation for the steeper-than-expected slope and the stronger correlation on fringing reefs could be a
higher habitat diversity or heterogeneity on fringing reefs than on barrier reefs (this is at present being
tested by satellite image analysis).
Coral cover and time
In contrast, two factors, time and coral cover were not found to be significant in the relationship between
total SR and butterflyfish SR. This suggests that comparisons of within-an-area transects with different
coral covers are valid, and since this relationship seems stable through time (at least at the scale tested), it
could be of some assistance in programmes intended for monitoring changes of species diversity of reef fish
communities.
Most studies show that coral is a significant factor for both total SR and butterflyfish SR (Reese, 1981;
Harmelin-Vivien and Bouchon-Naarro 1983; Bell and Galzin, 1984; Bouchon-Navaro and Bouchon, 1989;
Chabanet et al., 1997; Cadoret et al., 1999). One would expect butterflyfishes to be relatively more diverse in
coral rich areas, as in the Pacific a large number of them are coral feeders (Kulbicki et al., 2005) whereas
only a low number of other reef fish species are directly linked to coral for food. Consequently, coral cover
should influence the ratio between butterflyfish SR and total SR. The lack of effect, therefore, of coral cover
on the relationship between total SR and butterflyfish SR seems at first surprising (Table 3).
A potential explanation is that coral cover plays globally a similar role for butterflyfish species and other
species and is probably more important as providing shelter than as a direct or indirect food source. There
is no direct evidence for this, but Jones et al. (2004) demonstrated that coral-associated and non-associated
fish changed in a similar manner in reef areas where coral cover was affected.
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The lack of effect of time on the relationship between total SR and butterflyfish SR suggests that over the
timescale of the study (30 months), the number of butterflyfish species and total reef species varied in the
same way with either both butterflyfishes and total reef fish following similar pulses in SR (except for
trimester 7), or neither of them changing during this time period. This means also that the relative
detectability of butterflyfish species and other species on these reefs remained the same. This is important,
as many factors play on fish detectability (Kulbicki, 1998), in particular turbidity. This latter factor
changed, often drastically, from one sampling to the next owing to storms, calm weather or nutrient inputs
(and consequent algae development). This lack of time effect suggests that the relationship between total SR
and butterflyfish SR is very robust.
Applications
The potential uses of this relationship between total SR and butterflyfish SR are numerous. Being able to
recognize with a high degree of confidence all the fish species visible on a reef requires long training, as the
number of species involved is usually very high (often several hundred on a single reef). In contrast,
recognizing and counting butterflyfishes can be learned in a relatively short time. Therefore, the use of
butterflyfishes for getting a proxy of the SR of the total fish assemblage could be very important for a
number of monitoring programmes, in particular those which rely on volunteers or personnel who only
dive occasionally. Total SR is useful to numerous ecological models as it is an important component of
ecological parameters such as stability, resilience and resistance of communities to perturbations (Peterson
et al., 1998). Therefore being able to get some estimate of this total SR, or at least some relative measure,
can be very valuable. The power analysis indicates, however, that even under the best conditions the total
SR estimates obtained from butterflyfish SR should be considered more as an indicator than a precise
measure of total SR. Thus, if an acceptable confidence interval on predictive values of total SR is one of less
than 20% of the estimated total SR (i.e. if the estimated total SR was 60 species, the confidence interval
would cover from 48 to 72 species), the best probability of achieving this in the present study is 0.25 (i.e.
25% chance that the confidence interval does not include the true value of total SR). Therefore unless the
correlation between total SR and butterflyfish SR is exceptional, it would be unwise to expect estimates of
total SR which could be used directly in ecological models. The usefulness of this relationship is probably
highest in studies where relative values are sufficient.
Among the possible applications in this perspective, this technique may increase the power of spatial or
temporal surveys. Reef fishes have very patchy distributions and diversity may change rather drastically
within a reef over short distances. Counting all the fish species requires not only a high degree of expertise
but is also time-consuming and only a restricted number of stations can usually be sampled. Butterflyfish
counts are easy and fast and can be done by people with little training, thus allowing much higher spatial
(or temporal) coverage during a survey. The values of these butterflyfish counts could be inserted into
models as complementary data to complete counts and thus increase at little cost the power of the models.
Another possible use is in looking at butterflyfish historical data; there are many monitoring programmes
that have incidentally accumulated butterflyfish data. Once the relationship between total SR and
butterflyfish SR for an area is established, these data could be useful to give a general indication of the
spatial or temporal trends in total SR. Ecological and biogeographical applications of this type of datamining exercise could also be worth considering.
The impact of fishing on the relationship between total SR and butterflyfish SR needs to be considered.
In most of their geographical range, butterflyfishes are not targeted by fishermen; there are, however,
exceptions, in particular in southeast Asia where they are caught both for food and for the aquarium fish
trade. As long as fishing habits remain the same within any area, there are few reasons for this relationship
to change. The introduction of new fishing practices or a drastic increase in fishing effort with a shift of
target species, however, would certainly result in a change of this relationship. The same would probably be
S140
true for other types of perturbations such as pollution. This may narrow the range of uses of this
relationship and accentuates the need for good baseline studies.
In the present study, the total SR was taken to be all fish species that could be visually identified along the
transect. For most studies and monitoring programmes which use ‘total’ species counts, this ‘total’ is
represented by a restricted list of families and genera. This approach is dictated by the fact that many
species are very difficult to count, usually because of their behaviour (nocturnal, pelagic or cryptic species in
particular). This should be kept in mind if in the future one wishes to use ‘total’ SR to butterflyfish SR
relationships from different data sources.
The concept of using butterflyfishes to estimate other parameters of the reef fish assemblage needs to be
refined and further tested. It may also be the source of other applications. In particular, analyses currently
in progress suggest that much better correlations can be found if, instead of total SR, the relationship
between butterflyfish SR and some specific groups of fish, such as territorial and sedentary species, or
herbivorous ones, is used. Similarly, taking into account the behaviour, size or diet of butterflyfishes may
assist in improving the predictions of total SR. The combined use of butterflyfish SR and abundance is also
promising for proxies of total reef fish density and biomass estimates.
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The use of butterflyfish (Chaetodontidae) species richness as a

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