Changes in a tropical marine
inshore fish community in a
macro-tidal estuary (Darwin
Harbour, Australia).
This document was prepared for the Department of Land Resource
Management. Contributing author Dr Victor Gomelyuk
© Copyright of the Northern Territory Government, 2013.
Permission to copy is granted provided the source is acknowledged.
ISBN: 978-1-74350-061-3
Further information
Contact:
Dr Victor Gomelyuk
Marine Ecosystems, Flora and Fauna Division
Dept. of Land Resource Management
564 Vanderlin Drive BERRIMAH NT 0828
Mail to:
PO Box 496, PALMERSTON, NT 0831, Australia
Ph: +61 8 8995 5024
fax +61 8 8995 5099
Cite report as:
Gomelyuk, V. (2013) Changes in a tropical marine inshore fish community in a macro-tidal
estuary (Darwin Harbour, Australia). Technical Report for Department of Land Resource
Management, Darwin.
ii
Executive summary
Assessing temporal changes and trends in fish communities can assist with management of
Darwin Harbour. The diversity and abundance of fish communities were assessed using
baited remote underwater system (BRUVS), which uses “video fishing” - recording fish
attracted to a camera by standard bait and has been shown to be an effective non-extractive
survey method. The approach is useful for long-term environment monitoring because nonimpact nature of visual surveys enables repetitive sampling at reference sites. Fish
assemblages were compared between two surveys conducted in 2011 and 2012. Overall,
annual differences were relatively small and mainly the result of re-distribution of small
school pelagic and demersal species (trevallies, threadfin breams and ponyfishes) rather
than an indication of decline in fish abundance and biodiversity in monitored parts of Darwin
Harbour. Univariate analyses (ANOVA) of mean fish abundance and the number of species
in one video sample appear to be less sensitive and provide very limited insight on the nature
of changes in monitored fish assemblages compared to multivariate indices (Permutational
multivariate analysis of variance (PERMANOVA), Analysis of Similarity (ANOSIM) and
Similarity percentages (SIMPER). Univariate indices therefore have to be used in conjunction
with multivariate indices. Further monitoring can add important information of natural
temporal variability in fish assemblages of the Harbour. This will increase ability of monitoring
to detect and identify changes in fish assemblages caused by adverse environmental and
anthropogenic factors.
3
Contents
Executive summary ................................................................................................................3
Contents .................................................................................................................................4
1.
Introduction .....................................................................................................................9
1.1
Background ..............................................................................................................9
1.2
Obstacles and difficulties in interpreting fish community data in environment health
monitoring. ........................................................................................................................10
1.3.
2.
Aims .......................................................................................................................11
Material and Methods ...................................................................................................12
2.1
Study design ..........................................................................................................12
2.2
Survey procedure ...................................................................................................16
2.3
Underwater video interrogation...............................................................................16
2.3
Data analysis ..........................................................................................................17
2.3.1
Univariate analyses.............................................................................................17
2.3.2
Multivariate analyses ..........................................................................................17
2.3.2.1
Permutational multivariate analysis of variance (PERMANOVA) .....................18
2.3.2.2
Analysis of similarity (ANOSIM) .......................................................................18
2.3.2.2
Similarity percentages (SIMPER) ....................................................................18
3. Results .............................................................................................................................20
3.1
Descriptive Results.................................................................................................20
3.2 Univariate analyses results .........................................................................................31
North-West site at Channel Island.................................................................................31
Darwin Harbour Entrance site. ......................................................................................31
Rick Mills artificial reef site. ...........................................................................................31
Bottle Washer artificial reef site. ....................................................................................32
3.3 Multivariate analyses results .......................................................................................41
North-West site at Channel Island.................................................................................41
Darwin Harbour Entrance site. ......................................................................................41
Rick Mills artificial reef site. ...........................................................................................41
Bottle Washer artificial reef site. ....................................................................................48
4.
DISCUSSION ...............................................................................................................52
5.
Acknowledgements.......................................................................................................56
6.
References ...................................................................................................................56
7.
APPENDIX ...................................................................................................................62
4
5
List of Figures
Figure 1. Location of BRUVS monitoring stations in Darwin Harbour. ...................................13
Figure 2. Mean number of species in one 1-hour BRUVS video sample in “outer” and “inner”
monitoring stations in 2011 and 2012. Error bars are standard error. Stars between bars
indicate significance level: * - p ≤ 0.05; ** - 0.05 > p > 0.01 and *** - p < 0.00 ......................21
Figure 3. Mean number of fish (MaxN) in one 1-hour BRUVS video sample in “outer” and
“inner” monitoring stations in 2011 and 2012. .......................................................................22
Figure 4. Different ecological groups of fish in 2011 video records at artificial reefs sites or
“outer” monitoring stations in Darwin Harbour. Data labels represent precents of each
ecological group of fish to total fish number. .........................................................................29
Figure 5. Different ecological groups of fish in 2012 video records at artificial reefs sites or
“outer” monitoring stations in Darwin Harbour.......................................................................29
Figure 6. Different ecological groups of fish in 2011 video records at “inner” monitoring
stations in Darwin Harbour. ..................................................................................................30
Figure 7. Different ecological groups of fish in 2012 video records at “inner” monitoring
stations in Darwin Harbour. ..................................................................................................30
Figure 8. Fish number, MaxN in BRUVS samples taken at North-West site at Channel
Island, "inner" monitoring stations in Darwin Harbour in 2011 - 2012. ...................................33
Figure 9. Fish species number, in BRUVS samples taken at North-West site at Channel
Island, "inner" monitoring stations in Darwin Harbour in 2011 - 2012. ...................................34
Figure 10. Fish number, MaxN in BRUVS samples taken at the Entrance site, "inner"
monitoring stations in Darwin Harbour in 2011 - 2012. .........................................................35
Figure 11. Fish species number in BRUVS samples taken at the Entrance site, "inner"
monitoring stations in Darwin Harbour in 2011 - 2012. .........................................................36
Figure 12. Fish number, MaxN in BRUVS samples taken at Rick Mills site, "outer" monitoring
stations in Darwin Harbour in 2011 - 2012. ...........................................................................37
Figure 13. Fish species number in BRUVS samples taken at Rick Mills artificial reef site,
"outer" monitoring stations in Darwin Harbour in 2011 - 2012. ..............................................38
Figure 14. Fish number, MaxN in BRUVS samples taken at Bottle Washer artificial reef,
"outer" monitoring stations in Darwin Harbour in 2011 - 2012. ..............................................39
Figure 15. Fish species number in BRUVS samples taken at Bottle Washer artificial reef,
"outer" monitoring stations in Darwin Harbour in 2011 - 2012. ..............................................40
List of Tables
Table 1. The list and description of 12 monitoring stations in Darwin Harbour. .....................14
6
Table 2. Fish species (sorted in accordance to their contribution to total abundance) based
on MaxN value during BRUVS survey in 2011-2012 in “inner” monitoring stations” in Darwin
Harbour. ...............................................................................................................................23
Table 3. Fish species (sorted in accordance to their contribution to total abundance) based
on MaxN value during BRUVS survey in 2011 and 2012 at Bottle Washer and Rick Mills
artificial reefs, “outer” monitoring stations. ............................................................................26
Table 4. Permutational MANOVA of Bray-Curtis similarity indices in pooled data of fish
assemblages at three monitoring stations at North-West side in Darwin Harbour, 2011-2012
comparison. ..........................................................................................................................42
Table 5. SIMPER comparison of fish assemblages composition at three BRUVS monitoring
stations (pooled data) at North-West side of Channel Island in 2011 and 2012. Cut off for low
contribution: 90.0%. Average assemblages’ dissimilarity – 81.5%. .......................................43
Table 6. Permutational MANOVA of Bray-Curtis similarity indices in pooled data of fish
assemblages at three monitoring stations at the Entrance site in Darwin Harbour, 2011-2012
comparison. ..........................................................................................................................44
Table 7. SIMPER comparison of fish assemblages composition at three BRUVS monitoring
stations (pooled data) at the Entrance site in 2011 and 2012. Cut off for low contribution:
90.0%. Average assemblages’ dissimilarity – 82.6%. ...........................................................45
Table 8. Permutational MANOVA of Bray-Curtis similarity indices in pooled data of fish
assemblages at three monitoring stations at Rick Mills artificial reef site in Darwin Harbour,
2011 - 2012 comparison. ......................................................................................................46
Table 9. SIMPER comparison of fish assemblages composition at three BRUVS monitoring
stations (pooled data) at Rick Mills artificial reef site in 2011 and 2012. Cut off for low
contribution: 90.0%. Average assemblages’ dissimilarity –67.5% .........................................47
Table 10 . Permutational MANOVA of Bray-Curtis similarity indices in pooled data of fish
assemblages at three monitoring stations at Bottle Washer artificial reef site in Darwin
Harbour, 2011-2012 comparison. .........................................................................................49
Table 11. SIMPER comparison of fish assemblages composition at three BRUVS monitoring
stations (pooled data) at Bottle Washer artificial reef site in 2011 and 2012. Cut off for low
contribution: 90.0%. Average assemblages’ dissimilarity – 78.6%. .......................................50
Table 12. Post hoc power analysis of F tests one-way ANOVA of values of mean fish species
number at .............................................................................................................................62
Table 13. Post hoc power analysis of F tests one-way ANOVA of values of mean MaxN at
North-West Channel Island site in Darwin Harbour, stations 1-NCHB, 2-NCHB and 4RCKNCH in 2011-2012. ...............................................................................................................62
7
Table 14. Post hoc power analysis of F tests one-way ANOVA of values of mean fish
species number at The Entrance site in Darwin Harbour, stations DSAC-B, 8-RCK and 6RCK in 2011-2012. ...............................................................................................................63
Table 15. Post hoc power analysis of F tests one-way ANOVA of values of mean MaxN at .63
Table 16. Post hoc power analysis of F tests one-way ANOVA of values of mean fish species
number at Rick Mills artificial reef site in Darwin Harbour, stations RM-1, RM-2 and RM-3 in
2011-2012. ...........................................................................................................................64
Table 17. Post hoc power analysis of F tests one-way ANOVA of values of MaxN at ...........64
Table 18. Post hoc power analysis of F tests one-way ANOVA of values of mean fish species
number at Bottle Washer artificial reef site in Darwin Harbour, stations BW-1, BW-2 and BW3 in 2011-2012. ....................................................................................................................65
Table 19. Post hoc power analysis of F tests one-way ANOVA of values of MaxN at Bottle
Washer artificial reef site in Darwin Harbour, stations BW-1, BW-2 and BW-3 in 2011-2012.
.............................................................................................................................................65
Table 20. ANOVA of number of fish species in one 1-hour BRUVS video sample, pooled data
.............................................................................................................................................66
Table 21. ANOVA of number of fish in one 1-hour BRUVS video sample (MaxN), pooled data
.............................................................................................................................................66
Table 22. ANOVA of mean fish number (MaxN) in BRUVS samples at three monitoring
stations .................................................................................................................................66
Table 23. ANOVA of mean fish species number (FSN) in BRUVS samples at three
monitoring ............................................................................................................................66
Table 24. ANOVA of mean fish number (MaxN) in BRUVS samples at three monitoring
stations .................................................................................................................................66
Table 25. ANOVA of mean mean fish species number (FSN) in BRUVS samples at three ...67
Table 26. ANOVA of mean fish number (MaxN) in BRUVS samples at three monitoring ......67
Table 27. ANOVA of mean mean fish species number (FSN) in BRUVS samples at three ...67
Table 28. ANOVA of mean fish number (MaxN) in BRUVS samples at three monitoring ......67
Table 29. ANOVA of mean mean fish species number (FSN) in BRUVS samples at three ...68
8
1.
1.1
Introduction
Background
The direct and indirect coupling between fish communities and human impacts on estuaries
reinforces the choice of this taxonomic group as a biological indicator that can assist in the
formulation of environmental and ecological quality objectives (Whitfield & Elliott 2002). Many
groups of organisms have been proposed and used as indicators of environmental and
ecological change (Karr et al. 1986). Fishes have been successfully used as indicators of
environmental quality changes in a wide variety of aquatic habitats (Whitfield 1996, SotoGalera et al. 1998). Many studies have looked at fish populations and communities
responses on changes in habitat structure (Roberts & Ormond 1987, Tolimieri 1995, Caley &
St. John 1996, Friedlander & Parrish 1998, Tolimieri 1998, Holbrook et al. 2000, McClanahan
& Arthur 2001, Friedlander et al. 2003).
Fishes have numerous advantages fishes as indicator organisms for environmental
monitoring programmes:

They are usually present in all aquatic systems, with the exception of highly polluted
waters;

There is extensive life-history and environmental response information available for
most species;

species are relatively easy to identify;

fish communities usually include a range of species that represent a variety of trophic
levels;

fishes are comparatively long-lived and therefore provide a long-term record of
environmental stress;

they contain many life forms and functional guilds and thus are likely to cover all
components of aquatic ecosystems affected by anthropogenic disturbance;

they are both sedentary and mobile and thus will reflect stressors within one area as
well as providing groups to give a broader assessment of effects.

they have a high public awareness value such that the general public are more likely
to relate to information about the condition of the fish community than data on
invertebrates or aquatic plants;
9

societal costs of environmental degradation, including cost-benefit analyses, are more
readily evaluated because of the economic, aesthetic and conservation values
attached to fishes (from Whitfield & Elliott 2002).
Within the last two decades fisheries and conservation agencies started to implement more
holistic approaches to the assessment and management of resources. The objective has
been to move away from single species stock assessment to ecosystem management (ESA
1998; FRCC 1998; NMFS 1999).
Using baited remote underwater system (BRUVS), which uses “video fishing” - recording fish
attracted to a camera by standard bait, has been shown to be an effective non-extractive
survey method to obtain information on a large number of species and individuals in a variety
of habitats (Cappo et al. 2003, Watson et al. 2005, Cappo et al. 2007. Dorman, Harvey et al.
2012). Evaluating studies when BRUVS technique was compared with some traditional
ichthyological methods (fish traps and trawls) indicated relatively low selectivity of BRUVS
(Cappo et al. 2004, Cappo et al. 2007) provide more accurate information on fish
assemblages in certain local habitats. BRUVS therefore appears to be an appropriate
technique for fish communities/assemblages monitoring.
1.2
Obstacles and difficulties in interpreting fish community data in environment
health monitoring.
An important problem of any environmental monitoring is the problem of variability and in
particular natural variability in time in animals and plants (Morrisey et al. 1992, Underwood
2000). Whitfield & Elliott (2002) listed several key difficulties and problems when fishes are
used as indicators of biological integrity:

the mobility of fishes on seasonal and diel time scales can lead to sampling bias;

fishes may be relatively tolerant to substances chemically harmful to other life forms;

fishes can swim away from an anthropogenic disturbance, thus avoiding localized
exposure to pollutants or adverse environmental conditions;

estuarine environments that have been physically altered by humans may still contain
diverse fish assemblages (Whitfield and Elliott 2002).
However, even in relatively pristine marine habitats fish community composition and structure
can undergo rapid substantial changes due to fish seasonal migration and movements. All
mid-water species and many bottom-dwelling species have dial, seasonal movements and
10
simply occasional movements, related to food sources re-distribution (Ommaney 1963). So,
changes in species and fish numbers do occur in fish assemblages naturally, without
anthropogenic impact and adverse environmental factors and conditions. Therefore,
assessment of the range of changes in fish assemblages in “normal” conditions, when sharp
changes in anthropogenic impact and influence of adverse environmental factors and
conditions are unlikely is essential stage of monitoring. This data is important because it can
help to differentiate “natural” variations in fish assemblages structure and changes that may
be a result of negative anthropogenic impact (for example, pollution, habitat alteration,
overfishing) and adverse environmental factors and conditions (strong storms and tropical
cyclones). Knowledge on Northern Territory marine fish assemblages’ composition, structure,
seasonal and annual changes are still limited.
1.3.
Aims
The aims of this study were:
a) to assess of natural temporal variability in fish assemblages at each of 12 monitoring
stations in Darwin Harbour by comparing samples taken in 2011 and 2012 at the same
station;
b) to find out by comparing fish assemblages within the same stations what components
(species, ecological groups) contribute the most to temporal dissimilarity between
assemblages in different years;
c) to identify what parameters of fish assemblages are the most perspective for
environmental monitoring.
11
2.
2.1
Material and Methods
Study design
The following criteria used to select stations sites for monitoring included:

Fish abundance at the station have to be sufficient (station with poor fish abundance
provides less opportunity for detecting changes if fish abundance is in decline).

Biodiversity representativeness – station should represent common and wide
distributed habitat within the Harbour – rock reefs and coral habitats, areas with deep
filter feeders.

Water clarity at the station should be similar to overage water clarity in the Harbour
and should not be less than 1.5 m to make video analysis and fish identification and
count possible. Station should not be under the direct impact of anthropogenic
disturbance (e.g. dredging, sewage outfall) in the Harbour.
In order to get representation of various habitats of the Harbour four sites were opted for
monitoring: one site to south-west of Channel Island with three monitoring stations,
representing mid-harbour and bottom part of the Harbour; one site at Harbour entrance with
three monitoring stations and two separate sites further in “outer” part of the Harbour close to
the Shoal Bay with three monitoring stations at each site.
All 12 monitoring stations were selected from 24 sites surveyed in 2011 using stratified
random design (Gomelyuk 2012). The shortest distance between two nearest monitoring
stations was 250 m. This was done to ensure video replicates were independent (i.e. to
exclude possibility of same fish to visit more than one BRUVS device during the survey).
Figure 1 represent positions of each station and Table 1 highlights some key environmental
characteristics of monitoring stations in Darwin Harbour.
12
Figure 1. Location of BRUVS monitoring stations in Darwin Harbour.
13
Table 1. The list and description of 12 monitoring stations in Darwin Harbour.
“
Station
Depth
Type of bottom habitat
Code
during
name
sampling,
m
“INNER” MONITORING STATIONS
North-West Channel Island Location
1
North Channel bank 15.0-15.7
Rocky reef with rich filter feeders
1
(sponges,
hydroids,
1-NCHB
gorgonians)
community and algae
2
4
Rock
at
North 11-12
Rocky reef with rich filter feeders
Channel
(sponges,
hydroids,
4-RCK-
gorgonians) NCHB
community and algae
3
North Channel bank 18.0-19.8
Rocky reef with rich filter feeders
2
(sponges,
hydroids,
2-NCHB
gorgonians)
community and algae
The Entrance Location
4
DSAC Barge
15-16.5
Rocky reef with rich filter feeders
(sponges,
hydroids,
DSAC-B
gorgonians)
community, hard corals and algae
5
8 Rock
13.5-17.6
Rocky reef with rich filter feeders
(sponges,
hydroids,
8-RCK
gorgonians)
community, hard corals and algae
6
6 Rock
11-12
Rocky reef with rich filter feeders
(sponges,
hydroids,
6-RCK
gorgonians)
community, hard corals and algae
“OUTER” MONITORING STATIONS
Rick Mills Artificial Reef Location
7
8
9
1st station at Rick 12-12.5
Open sandy-muddy bottom ~50 m from 1-RM
Mills artificial reef,
artificial reef culvert
2nd station at Rick 11-12.5
Open sandy-muddy bottom ~70 m from 2-RM
Mills artificial reef
artificial reef culvert
3rd station at Rick 12 -12.7
Open sandy-muddy bottom, ~520 m 3-RM
Mills artificial reef
away from artificial reef culvert
Bottle Washer Artificial Reef Location
10 1-st station at Bottle 11-12
Open sandy-muddy bottom ~20 m from 1-BW
14
Washer artificial reef
11 2-nd station at Bottle 11-12
Washer artificial reef
12 3-rd station at Bottle 10-11
Washer artificial reef
artificial reef culvert
Open sandy-muddy bottom ~570 m 2-BW
from artificial reef culvert
Open sandy-muddy bottom ~160 m 3-BW
away from artificial reef
15
2.2
Survey procedure
All surveys were conducted in May–September 2011 and September 2012 during neap tides
to avoid high tidal currents and increased water turbidity during spring tides. Surveys were
conducted in daytime (between 8:00 hours and 15:00 hours). A Global Positioning System
device was used to navigate to each station. The average accuracy of this device is ±5–7 m.
Depth was measured using the boat depth sounder. The BRUVS gear used in the survey
and the sampling procedure was described in a previous report (Gomelyuk 2013).
At each station, one of the BRUVS apparatus was deployed for video survey (Cappo et al.
2003). The BRUVS remained on the sea floor for 60 minutes, and recorded fish attracted to
the bait canister. Site name, date, the time when survey was started and finished, the depth
and BRUVS device ID number were recorded. Because of relatively large distances between
selected monitoring stations and because two BRUVS were never used at the same site,
video replicates were independent (e.g. same fish were unable to visit more than one
BRUVS during the survey). Six one-hour underwater video samples (i.e. replicates) were
taken at each of monitoring station in both years.
2.3
Underwater video interrogation
An interrogation of video was done according to Cappo et al. (2003, 2004). All 60 minutes of
video were screened and each new fish species arriving in the field of view of the camera
was recorded. Only the maximum number of individuals of each species seen together in the
field of view at one time (MaxN) was used in analyses to avoid the possibility of fish double
counting. According to previous studies (Priede & Merrett 1996; Willis & Babcock 2000
Cappo et al. 2003, 2004; 2007, 20011, Watson et al. 2005), MaxN gives a conservative
estimate of fish relative density. Images of the sea bottom were used to identify different
types of bottom cover. In Darwin Harbour this can vary from hard coral, rocks, pebbles and
gravel to sand, silted sand and silt, depending on the depth and location of survey station.
Where possible, fish were identified to species level. Atlas of Living Australia
http://biocache.ala.org.au database was used as a main source of information on the
previous records of fish species in Darwin Harbour and Northern Territory waters.
International Code of Zoological Nomenclature (1999) and the list of standardised Australian
fish names http://www.marine.csiro.au/caab/namelist.htm was used in this report. ”Checklist
16
of Darwin Harbour fishes” (Larson 1997) and Atlas of Living Australia
http://biocache.ala.org.au/occurrences/search?taxa were used in this study.
2.3
Data analysis
2.3.1 Univariate analyses
Univariate statistics and descriptive statistics were completed with SYSTAT 13 software ®
(2009 SYSTAT Software Inc., Point Richmond, CA, USA). Analysis of variance (ANOVA)
was used to compare temporal differences (i.e., between 2011 and 2012 samples) in the
total abundance of fish (MaxN) and species richness (fish species number found in each 1hour sample, FSN). Data were examined for normality and homogeneity of variances using
Kolmogorov-Smirnov test (Lilliefors) and Levene's test. In order to decrease possibility of
Type I error one fixed factor (factor-different monitoring stations in 2011-2012) was used.
Significance level was set at p = 0.05. Pooled data for all “Inner” monitoring stations in 2011
was then compared with 2012 data. Then the data for “outer” stations in 2011 and 2012 was
compared. Tukey’s multiple comparison tests (HSD) was used for pairwise comparison
between data in 2011 and 2012. A power achieved in F-test and t-test in pairwise
comparisons was calculated using G*Power v. 3.1.7 software (Faul et al. 2007, Erdfelder,
Lang, & Buchner 2007). Post hoc analysis of achieved power has revealed low (less than
0.8) power values in 60% of all 48 cases of pairwise comparison of FSN in sample and MaxN
of single monitoring stations. This result indicated that the probability of incorrectly rejecting
the null hypothesis “no difference” between 2011 and 2012 is high. Nevertheless, the power
of F-test in one-way ANOVA of sets of pooled data from all three monitoring stations at each
site was sufficient in all 4 comparisons (Table 12-19, Appendix). Therefore, further data
analyses and discussion was focused on comparison monitoring sites rather than single
stations.
2.3.2 Multivariate analyses
Descriptive multivariate analyses were calculated with Statistical package PRIMER 6.0 &
PERMANOVA + for PRIMER ® (2012 PRIMER-E Ltd., Plymouth, UK, Clarke & Warwick
1994; Anderson, Gorley and Clarke 2008).
17
2.3.2.1
Permutational multivariate analysis of variance (PERMANOVA)
PERMANOVA is a program for testing the simultaneous response of one or more variables
to one or more factors in an ANOVA experimental design on the basis of any distance
measure, using permutation methods. First, the program calculates the distances between
each pair of observation units (sampling units) to obtain a distance matrix. It then calculates
the test-statistics from this according to the relevant experimental design. (Anderson 2001).
One fixed factor (locations=different monitoring stations in 2011-2012) design was used in
this analysis. As ANOVA, PERMANOVA comparison of 2011-2012 data was done for sites
with pooled data from three monitoring stations at each site. Power of analysis was
calculated using Pillai - O'Brien-Shieh algorithm (Erdfelder, Lang, & Buchner 2007). Manova
test statistic known as “Pillai’s trace” was calculated during canonical analysis of principal
coordinates (CAP), PERMANOVA + Primer package (Anderson et al. 2008). Power values
>0.85 were achieved in all 4 comparisons (Appendix, Table 12-19).
2.3.2.2
Analysis of similarity (ANOSIM)
The Bray-Curtis similarity matrix was then used to calculate the ANOSIM (analysis of
similarity) which depends on the relative order (i.e., ranking) of the similarity coefficients in
the Bray-Curtis similarity matrix, rather than their absolute values. The ANOSIM was used to
determine whether the fish assemblages differed statistically between years. The ANOSIM
test statistic, R, is based on the ratio of the between-group to within-group similarity ranking.
Pair wise comparison tests are also calculated which generate an R value and a significance
(p) value for each possible pair of comparisons. Generally, the value of R ≥ 0.75 indicates
well separated communities, 0.75 > R ≥ 0.5 - overlapping but different communities, 0.5 > R
≥ 0.25 - overlapping but somewhat different and R <0.25 indicates insufficiently different
communities (Clarke and Gorley 2001). ANOSIM was done using pooled data of each of
three monitoring stations at each site.
2.3.2.2
Similarity percentages (SIMPER)
Similarity percentages (SIMPER) were used to examine similarity within the groups (pooled
samples collected at three monitoring stations within each site) and to inspect that species
contributed to any observed differences between fish assemblages in 2011 and 2012.
18
19
3. Results
3.1
Descriptive Results
A total of 3,589 fish from 100 different species was recorded at the 12 monitoring stations in
2011 and 2012 surveys. Fish assemblages parameters differed between sites and areas:
mean fish species number in one video sample was almost twice higher at the “outer”
monitoring stations with high level of significance (Appendix, Table 20). Mean number of fish
(MaxN) in one video sample was almost twice times higher at the “outer” monitoring stations
than at “inner” stations on high level of significance (Appendix, Table 21). While no changes
were found in mean fish number at “inner” stations, at “outer” stations this index in 2011 was
significantly higher comparing to 2012 (Figure 3). This was due to the decrease in numbers
of school pelagic trevally, Yellowstripe Scad, Selaroides leptolepis. This fish as well as
Fringefin Trevally (Pantolabus radiatus ) and Northwest Threadfin Bream (Pentapodus
porosus) dominated video samples and had the highest occurrence at “outer” monitoring
stations in 2011 (Tables 2).
In 2012, Yellowstripe Scad was recorded only sporadically at some stations (see occurrence
percent, Table 2). Both in 2011 and in 2012 four fishes - pelagic school species Yellowstripe
Scad and Fringefin Trevally together with demersal (free-swimming near the bottom)
Northwest Threadfin Bream and demersal school Whipfin Ponyfish (Equulites leuciscus)
were the most abundant in fish assemblages in “outer” Darwin Harbour, comprising more
than 50% of all recorded fish (Tables 2, Figures 4). However, in 2012 a notable decrease in
number of fish belonging to these ecological groups has been recorded within this site, while
the proportion of open bottom areas demersal fish increased (Figure 5, Table 2).
20
Figure 2. Mean number of species in one 1-hour BRUVS video sample in “outer” and “inner”
monitoring stations in 2011 and 2012. Error bars are standard error. Stars between bars
indicate significance level: * - p ≤ 0.05; ** - 0.05 > p > 0.01 and ***
- p < 0.00
21
Figure 3. Mean number of fish (MaxN) in one 1-hour BRUVS video sample in “outer” and
“inner” monitoring stations in 2011 and 2012.
22
Table 2. Fish species (sorted in accordance to their contribution to total abundance) based on
MaxN value during BRUVS survey in 2011-2012 in “inner” monitoring stations” in Darwin
Harbour.
Abundance, %1
Species
Years 2011
Occurrence, %2
2012
2011 2012
Pantolabus radiatus
20.1
11.7
25.0
36.1
Pentapodus porosus
11.2
16.1
50.0
55.6
Equulites leuciscus
11
17.8
50.0
33.3
Selaroides leptolepis
8.9
0.7
22.2
8.3
Zabidius novemaculeatus
6.1
0.2
16.7
2.8
Lutjanus carponotatus
-
4.4
-
33.3
Choerodon cephalotes
3.7
-
25.0
-
Caranx sp
3.6
5.5
13.9
30.6
Paramonacanthus choirocephalus
3.1
0.2
27.8
2.8
Choerodon sp.
-
3.1
-
13.9
Lutjanus gibbus
-
2.9
-
19.4
Nemipterus sp.
-
2.9
-
11.1
Upeneus tragula
2.5
-
2.8
-
Carcharhinus dussumieri
2.1
1.1
27.8
11.1
Nemipterus nematopus
-
2.0
-
25
Choerodon vitta
1.8
2.0
22.2
8.3
Scomberomorus queenslandicus
1.8
-
27.8
-
Lutjanus russelli
1.7
-
11.1
-
Choerodon schoenleinii
1.7
-
16.7
-
Echeneis naucrates
1.5
0.2
16.7
2.8
Lethrinus atkinsoni
1.5
0.9
5.6
11.1
Goby
1.4
0.9
33.3
5.6
Lagocephalus sceleratus
1.4
-
19.4
-
Carangoides hedlandensis
0.1
1.3
5.6
8.3
Cephalopholis boenak
-
1.1
-
5.6
Carcharhinus dussumieri
-
1.1
-
11.1
Sillago sp.
1.2
-
25.0
-
Chelmon müelleri
1.2
3.5
5.6
33.3
Flounder
1.2
-
16.7
-
Leiognathus sp.
-
1.1
-
8.3
23
Chiloscyllium punctatum
-
1.1
-
13.9
Gymnocranius elongatus
1
2.0
11.1
19.4
Lutjanus erythropterus
0.9
-
2.8
-
Chaetodontoplus duboulayi
0.9
1.5
16.7
13.9
Sphaeramia orbicularis
-
0.9
-
8.3
Lethrinus atkinsoni
-
0.9
-
11.1
Monacanthus chinensis
0.8
0.2
13.9
2.8
Sphyraena jello
0.7
0.2
8.3
2.8
Choerodon cyanodus
0.7
3.3
8.3
41.7
Hemiscyllium trispeculare
-
0.7
-
8.3
Gnathanodon speciosus
0.5
-
5.6
-
Nemipterus hexodon
0.5
-
16.7
-
Diagramma labiosum
0.5
-
2.8
-
Plectropomus laevis
-
0.4
-
5.6
Negaprion acutidens
0.4
-
11.1
-
Neotrygon kuhlii
0.4
-
11.1
-
Diploprion bifasciatum
-
0.4
-
5.6
Lagocephalus sp.
0.4
-
11.1
-
Sillago sihama
-
0.4
-
2.8
Aetobatus narinari
-
0.4
-
5.6
Galeocerdo cuvier
-
0.4
-
5.6
Carcharhinus melanopterus
0.3
1.3
8.3
13.9
Rhynchobatus djiddensis
0.3
0.2
11.1
2.8
Himantura jenkinsii
0.3
-
2.8
-
Ulua aurochs
0.3
-
5.6
-
Nemipterus sp.
0.3
-
2.8
-
Siganus sp.
0.3
-
2.8
-
Nebrius ferrugineus
0.2
-
8.3
-
Carcharhinus sp.
0.2
-
8.3
-
Sphyrna mocarran
0.2
0.2
5.6
2.8
Cephalopholis boenak
0.2
1.1
2.8
5.6
Cephalopholis sp.
-
0.2
-
2.8
Sphyraena obtusata
0.2
-
5.6
-
Scorpaenopsis sp.
-
0.2
-
2.8
Sphyraena jello
-
0.2
-
2.8
Plectorhinchus gibbosus
-
0.2
-
2.8
24
Lethrinus nebulosus
-
0.2
-
2.8
Sphyraena sp.
0.1
0.2
2.8
2.8
Siganus fuscescens
0.2
-
8.3
-
Epinephelus coioides
0.2
2.6
2.8
25.0
Zabidius novemaculeatus
-
0.2
-
2.8
Seriolina nigrofasciata
0.1
-
2.8
-
Scomberomorus sp.
0.1
-
2.8
-
Opistognatus sp.
-
0.2
-
2.8
Scarus ghobban
-
0.2
-
2.8
Acanthurus grammoptilus
-
0.4
-
5.6
1
Species abundance are expressed as a fraction of certain fish species to total number of
fish recorded during survey; 2 Species occurrence represents the percent of certain species
presence in all samples made in the area. Species contributed to ≥ 90% of total abundance
are given in bold.
25
Table 3. Fish species (sorted in accordance to their contribution to total abundance) based on
MaxN value during BRUVS survey in 2011 and 2012 at Bottle Washer and Rick Mills artificial
reefs, “outer” monitoring stations.
Species
Abundance, %
Years 2011
Occurrence, %
2012
2011
2012
Selaroides leptolepis
24.9
8.9
91.8
22.2
Pantolabus radiatus
16.1
20.1
75.5
25.0
Pentapodus porosus
14.5
11.2
91.8
50.0
Zabidius novemaculeatus
5.7
6.1
36.7
16.7
Equulites leuciscus
5.5
11.0
55.1
50.0
Terapon theraps
3.4
-
24.5
-
Scomberomorus sp.
2.4
0.1
59.2
2.8
Caranx sp
1.8
3.6
20.4
13.9
Carangoides sp.
1.6
0.1
38.8
5.6
Nemipterus sp.
1.6
0.3
20.4
2.8
Ambassis sp.
1.4
-
2.0
-
Lethrinus sp.
1.3
-
30.6
-
Upeneus tragula
1.2
2.5
24.5
2.8
Sillago sp.
-
1.2
-
25.0
Chaetodontoplus duboulayi
0.9
0.9
18.4
16.7
Sillago sihama
0.8
-
22.4
-
Chelmon müelleri
0.8
1.2
16.3
5.6
Seriolina nigrofasciata
0.7
0.1
20.4
2.8
Lutjanus erythropterus
0.7
0.9
10.2
2.8
Gymnocranius elongatus
0.7
1.0
26.5
11.1
Choerodon cyanodus
0.7
0.7
16.3
8.3
Flounder
0.7
1.2
26.5
16.7
Alectis ciliaris
0.7
-
18.4
-
Gnathanodon speciosus
0.6
0.5
12.2
5.6
Choerodon sp.
0.6
-
20.4
-
Monacanthus chinensis
0.6
0.8
20.4
13.9
Sphyraena jello
0.6
0.7
16.3
8.3
Carcharhinus dussumieri
0.5
2.1
12.2
27.8
Choerodon cephalotes
0.5
3.7
16.3
25.0
Choerodon vitta
0.5
1.8
10.2
22.2
Paramonacanthus choirocephalus
0.5
3.1
18.4
27.8
Herklotsichthys lippa
0.5
-
8.2
26
Echeneis naucrates
0.5
1.5
12.2
16.7
Lethrinus nebulosus
0.5
-
6.1
-
Carcharhinus sp.
0.4
0.2
12.2
8.3
Scolopsis sp.
0.4
-
8.2
-
Lethrinus atkinsoni
0.4
1.5
6.1
5.6
Lagocephalus sceleratus
0.4
1.4
8.2
19.4
Negaprion acutidens
-
0.4
-
11.1
Neotrygon kuhlii
-
0.4
-
11.1
Lagocephalus sp.
-
0.4
-
11.1
Carcharhinus dussumieri
-
0.3
-
8.3
Lutjanus carponotatus
0.3
-
8.2
-
Himantura uarnak
0.3
-
10.2
-
Nemipterus hexodon
0.3
0.5
10.2
16.7
Goby
0.3
1.4
10.2
33.3
Ulua aurochs
-
0.3
Siganus sp.
0.3
0.3
4.1
2.8
Rhynchobatus djiddensis
-
0.3
-
11.1
Himantura jenkinsii
-
0.3
-
2.8
Scomberomorus queenslandicus
0.3
1.8
8.2
27.8
Epinephelus lanceolatus
0.2
-
8.2
-
Carangoides caeruleopinnatus
0.2
-
2.0
-
Cephalopholis boenak
0.2
0.2
4.1
2.8
Siganus fuscescens
-
0.2
-
8.3
Diagramma labiosum
0.2
0.5
6.1
2.8
Nebrius ferrugineus
-
0.2
-
8.3
Choerodon schoenleinii
0.2
1.7
2.0
16.7
Sphyrna mocarran
0.1
0.2
4.1
5.6
Gymnothorax longinquus
0.1
-
4.1
-
Epinephelus coioides
0.1
0.1
4.1
2.8
Lutjanus russelli
0.1
1.7
2.0
11.1
Nemipterus nematopus
0.1
-
2.0
-
Paramonacanthus filicauda
0.1
-
2.0
-
Chiloscyllium punctatum
0.1
-
2.0
-
Carcharhinus sorrah
0.1
-
2.0
-
Galeocerdo cuvier
0.1
-
2.0
-
Psammoperca waigiensis
0.1
-
2.0
-
5.6
27
Pomadasys maculatus
0.1
-
2.0
-
Sphyraena obtusata
0.1
0.2
2.0
5.6
Sphyraena sp.
0.1
0.1
2.0
2.8
Carangoides hedlandensis
-
0.1
-
5.6
Anacanthus barbatus
0.1
-
2.0
-
Paramonacanthus sp.
0.1
-
2.0
-
Lagocephalus lunaris
0.1
-
2.0
-
28
1.3
3.2
Pelagic and demersal
school fish species
28.4
Open bottom benthic
fish species
Reef fish species
67.2
Sharks
Figure 4. Different ecological groups of fish in 2011 video records at artificial reefs sites or
“outer” monitoring stations in Darwin Harbour. Data labels represent precents of each
ecological group of fish to total fish number.
5
3.4
Pelagic and demersal
school fish species
41.5
Open bottom benthic
fish species
Reef fish species
50.1
Sharks
Figure 5. Different ecological groups of fish in 2012 video records at artificial reefs sites or
“outer” monitoring stations in Darwin Harbour.
29
2.9
26.6
33.3
Pelagic and demersal
school fish species
Open bottom benthic
fish species
Reef fish species
Sharks
37.2
Figure 6. Different ecological groups of fish in 2011 video records at “inner” monitoring
stations in Darwin Harbour.
4.8
Pelagic and demersal
school fish species
19
38.9
Open bottom benthic
fish species
Reef fish species
Sharks
37.3
Figure 7. Different ecological groups of fish in 2012 video records at “inner” monitoring
stations in Darwin Harbour.
30
The same pelagic and demersal school fish species were also abundant at “inner” Harbour
monitoring stations, however reef fishes - Blue Tuskfish (Choerodon cyanodus) Stripey
Snapper (Lutjanus carponotatus), Scribbled Angelfish, (Chaetodontoplus duboulayi) and
Müller's Coralfish (Chelmon müelleri) and others hard substrate associated species play a
substantial role in shaping fish assemblages in “inner” part of the Harbour (Tables 3, Figures
6, 7). Non-school demersal, reef and benthic fish species prevailed in assemblages at “inner”
Harbour monitoring stations both 2011 and 2012 (Figures 4, 5).
3.2 Univariate analyses results
North-West site at Channel Island.
Statistically significant differences were found in 2011 and 2012 comparison in mean fish
number in one sample (MaxN) within pooled data from three monitoring stations at this site (p
< 0.001, one way ANOVA) (Appendix, Table 22).There were some increase in fish
abundance in 2012 (Figure 8). No difference was found between 2011 and 2012 at this site
in fish species number, FSN (Figure 9, Appendix, Table 23).
Darwin Harbour Entrance site.
ANOVA found significant difference in mean fish abundance (MaxN) comparison of data for
2011-2012 (Table 24, Appendix). However, this difference reflects variation in MaxN between
the different stations at the site. No statistically significant differences were found between
2011 and 2012 (Figure 10). Similarly, while mean fish species number varied between
different stations within the site, however no statistically significant differences were found in
2011-2012 comparison (Figure 11, Appendix, Table 25).
Rick Mills artificial reef site.
Some increase in in MaxN was found at this site in 2011-2012 comparison, differences
statistically significant (p < 0.018, one way ANOVA) (Figure 12, Appendix, Table 26).
Contrary to the mean fish abundance, some decrease in mean number of fish species was
recorded at this site site in 2012 (p < 0.001, one way ANOVA) (Figure 13, Appendix, Table
27).
31
Bottle Washer artificial reef site.
A notable decrease in MaxN value was found in 2012 in interannual ANOVA comparison,
differences significant, p = 0.001 (Figure 14, Appendix, Table 28). Although ANOVA also
found significant differences in mean fish species number comparison of samples taken at
this site (p = 0.018, Apendix, Table 29), this difference reflects spatial variability between
monitoring sites rather than interannual changes (Figure 16).
32
Figure 8. Fish number, MaxN in BRUVS samples taken at North-West site at Channel Island,
"inner" monitoring stations in Darwin Harbour in 2011 - 2012.
33
Figure 9. Fish species number, in BRUVS samples taken at North-West site at Channel Island,
"inner" monitoring stations in Darwin Harbour in 2011 - 2012.
34
Figure 10. Fish number, MaxN in BRUVS samples taken at the Entrance site, "inner" monitoring
stations in Darwin Harbour in 2011 - 2012.
35
Figure 11. Fish species number in BRUVS samples taken at the Entrance site, "inner"
monitoring stations in Darwin Harbour in 2011 - 2012.
36
Figure 12. Fish number, MaxN in BRUVS samples taken at Rick Mills site, "outer" monitoring
stations in Darwin Harbour in 2011 - 2012.
37
Figure 13. Fish species number in BRUVS samples taken at Rick Mills artificial reef site, "outer"
monitoring stations in Darwin Harbour in 2011 - 2012.
38
Figure 14. Fish number, MaxN in BRUVS samples taken at Bottle Washer artificial reef, "outer"
monitoring stations in Darwin Harbour in 2011 - 2012.
39
Figure 15. Fish species number in BRUVS samples taken at Bottle Washer artificial reef,
"outer" monitoring stations in Darwin Harbour in 2011 - 2012.
40
3.3 Multivariate analyses results
North-West site at Channel Island.
Significant difference in fish assemblages compositions based on Bray-Curtis similarity was
found during Permutation MANOVA comparison of samplings done in 2011 and in 2012,
(Table 4). However, Global R calculated during ANOSIM was 0.202 at significance level of
p=0.01. This indicates insufficient differences in community composition in 2011 and 2012.
SIMPER analysis showed that major contributors (60.8%) to changes in fish assemblages
compositions at this site in 2011-2012 were six fish species – bottom school ponyfish
Leiognathus sp. and Northwest Threadfin Bream Pentapodus porosus, pelagic trevally
Caranx sp. and Fringefin Trevally Pantolabus radiates. Only two reef fish - Stripey Snapper
Lutjanus carponatus and Blue Tuskfish Choerodon cyanodus were in this contributors group
(Table 5).
Darwin Harbour Entrance site.
Permutation MANOVA comparison of Bray-Curtis similarity index of fish assemblages at at
the Entrance site in 2011 and 2012 found difference of high significance level (Table 6). Yet
again ANOSIM Global R value was relatively low – 0.172, p = 0.07 denoting minor
differences in community composition between 2011 and 2012. According to SIMPER
analysis, 6 species contributed to ~50% of differences in community composition and
structure between 2011 and 2012. These species were school bottom Northwest Threadfin
Bream Pentapodus porosus and ponyfish Leiognathus sp., pelagic Fringefin Trevally
Pantolabus radiatus and reef species Restripe Tuskfish Choerodon vitta, Stripey Snapper
Lutjanus carponatus and Blue Tuskfish Choerodon cyanodus (Table 7).
Rick Mills artificial reef site.
Permutation MANOVA indicated that the difference in Bray-Curtis similarity index between
BRUVS samples collected at three monitoring stations at this site in 2011 and 2012 was
statistically highly significant (Table 8).
41
Table 4. Permutational MANOVA of Bray-Curtis similarity indices in pooled data of fish
assemblages at three monitoring stations at North-West side in Darwin Harbour, 2011-2012
comparison.
Source
df
Stations*Year 1
34
Res
Total
35
SS
11619
MS
Pseudo-F
11619
3.7465
1.0544∙E5
3101.2
P(perm) Unique permutations, N
0.004
999
1.1706∙E5
42
Table 5. SIMPER comparison of fish assemblages composition at three BRUVS monitoring
stations (pooled data) at North-West side of Channel Island in 2011 and 2012. Cut off for low
contribution: 90.0%. Average assemblages’ dissimilarity – 81.5%.
Years
2012
Abundance,
N
3.39
2011
Abundance,
N
0.33
Caranx sp.
1.39
1.28
9.41
11.49
Pantolabus radiatus
2.22
0.06
8.70
10.63
Pentapodus porosus
1.28
0.78
7.13
8.72
Lutjanus carponotatus
0.78
0.89
6.20
7.57
Choerodon cyanodus
0.44
1.39
5.95
7.27
Lutjanus gibbus
0.72
0.11
4.92
6.01
Chelmon müelleri
0.39
0.94
4.90
5.98
Epinephelus coioides
0.44
0.72
4.80
5.87
Chaetodontoplus duboulayi
0.06
0.89
4.64
5.67
Sphaeramia orbicularis
0.22
0.17
1.75
2.14
Chiloscyllium punctatum
0.22
0.11
1.70
2.08
Plectorhinchus gibbosus
0.06
0.22
1.18
1.44
Species
Leiognathus sp.
Dissimilarity,
%
12.44
Contribution,
%
15.20
43
Table 6. Permutational MANOVA of Bray-Curtis similarity indices in pooled data of fish
assemblages at three monitoring stations at the Entrance site in Darwin Harbour, 2011-2012
comparison.
Source
df
Stations*Year 1
SS
11619
MS
Pseudo-F
11619
3.7465
Res
34
1.0544∙E5
3101.2
Total
35
1.1706∙E5
P(perm) Unique permutations, N
0.004
999
44
Table 7. SIMPER comparison of fish assemblages composition at three BRUVS monitoring
stations (pooled data) at the Entrance site in 2011 and 2012. Cut off for low contribution: 90.0%.
Average assemblages’ dissimilarity – 82.6%.
Years
2012
2011
Species
Pentapodus porosus
Abundance,
N
3.39
Abundance,
N
1.56
Leiognathus sp.
1.33
1.83
7.98
9.65
Pantolabus radiatus
0.72
2.67
7.01
8.49
Choerodon vitta
1.22
0.17
5.27
6.38
Lutjanus carponotatus
0.39
0.89
4.09
4.94
Choerodon cyanodus
0.78
0.78
3.99
4.83
Nemipterus sp.
0.17
0.89
3.71
4.48
Chaetodontoplus duboulayi
0.5
0.72
3.52
4.26
Chelmon müelleri
0.28
0.5
2.67
3.23
Choerodon cephalotes
0.28
0.44
2.34
2.83
0
0.5
2.08
2.52
Carcharhinus dussumieri
0.28
0.5
2.04
2.47
Acanthurus grammoptilus
0.33
0.17
1.8
2.18
Epinephelus coioides
0.28
0.33
1.74
2.1
Nemipterus nematopus
0.39
0.11
1.74
2.1
0
0.28
1.61
1.94
Lethrinus atkinsoni
0.11
0.33
1.48
1.79
Cephalopholis boenak
0.28
0.17
1.44
1.75
Plectropomus maculatus
0.11
0.22
1.25
1.51
Pomacanthus sexstriatus
0
0.28
1.1
1.33
0.33
0
1.07
1.3
0
0.28
1.04
1.26
Hemiscyllium trispeculare
0.17
0
0.92
1.12
Gymnocranius elongatus
0.17
0.06
0.71
0.86
Carangoides caeruleopinnatus
0
0.17
0.68
0.83
Plectorhinchus gibbosus
0
0.17
0.66
0.8
Lethrinus laticaudis
Choerodon sp.
Carangoides hedlandensis
Lutjanus vitta
Dissimilarity,
%
12.6
Contribution,
%
15.24
45
Table 8. Permutational MANOVA of Bray-Curtis similarity indices in pooled data of fish
assemblages at three monitoring stations at Rick Mills artificial reef site in Darwin Harbour,
2011 - 2012 comparison.
Source
df
Stations*Year 1
SS
9266.1
MS
Pseudo-F
9266.1
4.7329
Res
34
66566
1957.8
Total
35
75832
P(perm) Unique permutations, N
0.001
998
46
Table 9. SIMPER comparison of fish assemblages composition at three BRUVS monitoring
stations (pooled data) at Rick Mills artificial reef site in 2011 and 2012. Cut off for low
contribution: 90.0%. Average assemblages’ dissimilarity –67.5%
Years
2012
2011
Species
Pantolabus radiatus
Abundance,
N
9.83
Abundance
,N
11.83
Dissimilarity,
%
15.21
Contribution,
%
22.51
Selaroides leptolepis
3.5
10.33
9.73
14.41
Pentapodus porosus
2.33
6.89
7.1
10.51
Zabidius novemaculeatus
2
2.33
4.3
6.36
Caranx sp.
1.5
1.39
3.14
4.65
Upeneus tragula
1.33
0.83
2.42
3.58
Scomberomorus queenslandicus
0.39
1.44
1.78
2.64
Choerodon cephalotes
1.22
0.56
1.34
1.98
Lutjanus erythropterus
0.5
0.61
1.28
1.9
Lethrinus atkinsoni
0.72
0.28
1.26
1.86
Leiognathus sp.
0
0.67
1.23
1.81
Chelmon müelleri
0.5
0.5
1.06
1.58
Carangoides sp.
0
0.67
1
1.49
Lethrinus sp.
0
0.72
0.89
1.32
Gymnocranius elongatus
0.39
0.39
0.87
1.28
Scolopsis sp.
0
0.5
0.84
1.24
Chaetodontoplus duboulayi
0.17
0.44
0.84
1.24
Carcharhinus dussumieri
0.5
0.17
0.83
1.23
Sphyraena jello
0.28
0.5
0.77
1.14
Lutjanus russelli
0.61
0
0.73
1.08
Flounder
0.28
0.28
0.68
1.01
Paramonacanthus choirocephalus
0.33
0.28
0.67
0.99
Choerodon vitta
0.44
0.11
0.64
0.95
Nemipterus sp.
0.17
0.28
0.62
0.91
Echeneis naucrates
0.22
0.28
0.59
0.88
Diagramma labiosum
0.28
0.17
0.52
0.77
Siganus fuscescens
0.17
0.28
0.5
0.74
47
The Global R value in ANOSIM was low – 0.223, p = 0.01, suggesting only a slight difference
in comparing fish assemblages. SIMPER analysis results showed that changes in abundance
of just five fish species of all 29 recorded at Rick Mills artificial site contributed to 58.5% of
dissimilarity between assemblages of 2011 and 2012. These fish were pelagic school
Fringefin Trevally Pantolabus radiates, Yellowstripe Scad Selaroides leptolepis, trevally
Caranx sp. and Shortfin Batfish Zabidius novemaculeatus, Bottom Northern Treadfin Bream
was also in this the most contributing group (Table 9).
Bottle Washer artificial reef site.
According to Permutation MANOVA, were was a significant difference in Bray-Curtis
similarity index between samples collected at Bottle Washer artificial reef site in 2011 and
2012 (Table 10). ANOSIM Global R calculated for this site was 0.375, p = 0.01. Such value of
sample statistic indicates “overlapping but somewhat different communities” (Clarke and
Gorley 2001) at this site in 2011 and 2012. SIMPER analysis showed that the leading role in
contribution to 52.6% of dissimilarity between fish assemblages 2011 and 2012 was played
by only 5 species - pelagic school species - Yellowstripe Scad Selaroides leptolepis,
Fringefin Trevally Pantolabus radiates and Shortfin Batfish Zabidius novemaculeatus,
followed by bottom ponyfish Leiognathus sp. and Northern Treadfin Bream Pentapodus
porosus (Table 11).
48
Table 10 . Permutational MANOVA of Bray-Curtis similarity indices in pooled data of fish
assemblages at three monitoring stations at Bottle Washer artificial reef site in Darwin Harbour,
2011-2012 comparison.
Source
df
Stations*Year 1
SS
15596
MS
Pseudo-F
15596
6.4447
Res
34
82276
2419.9
Total
35
97872
P(perm) Unique permutations, N
0.001
997
49
Table 11. SIMPER comparison of fish assemblages composition at three BRUVS monitoring
stations (pooled data) at Bottle Washer artificial reef site in 2011 and 2012. Cut off for low
contribution: 90.0%. Average assemblages’ dissimilarity – 78.6%.
Years
2012
2011
Species
Selaroides leptolepis
Abundance,
N
1.22
Abundance
,N
11.68
Dissimilarity,
%
17.67
Contribution,
%
22.47
Leiognathus sp.
0
3.98
6.76
8.6
Pentapodus porosus
3.61
4.03
6.75
8.59
Zabidius novemaculeatus
1.22
3.92
6.52
8.29
Pantolabus radiatus
0.83
2.22
3.64
4.63
Paramonacanthus choirocephalus
1.33
0.19
2.83
3.6
Lagocephalus sceleratus
0.67
0.46
1.75
2.22
Caranx sp.
0.39
0.71
1.56
1.99
Choerodon cephalotes
0.72
0.22
1.47
1.87
Choerodon vitta
0.5
0.33
1.43
1.82
Choerodon schoenleinii
0.72
0.06
1.41
1.8
Carcharhinus dussumieri
0.61
0.28
1.3
1.65
Goby
0.67
0.33
1.28
1.63
Echeneis naucrates
0.56
0.33
1.27
1.62
Sillago sp.
0.56
0.19
1.25
1.59
Ambassis sp.
0
1.39
1.18
1.5
Scomberomorus queenslandicus
0.61
0.61
1.16
1.48
Nemipterus hexodon
0.28
0.5
1.09
1.38
Chaetodontoplus duboulayi
0.33
0.33
0.98
1.25
Seriolina nigrofasciata
0
0.54
0.97
1.24
Gnathanodon speciosus
0.22
0.36
0.94
1.19
Choerodon cyanodus
0.17
0.44
0.9
1.15
Flounder
0.33
0.25
0.82
1.04
Monacanthus chinensis
0.39
0.17
0.81
1.02
Anacanthus barbatus
0
0.25
0.79
1
Nemipterus sp.
0
0.34
0.7
0.9
Sillago sihama
0
0.42
0.67
0.85
Carangoides sp.
0
0.42
0.66
0.84
Gymnocranius elongatus
0.17
0.31
0.65
0.83
Lutjanus russelli
0.28
0.11
0.62
0.78
50
Chelmon müelleri
0.11
0.28
0.54
0.69
Carangoides hedlandensis
0.06
0.33
0.54
0.69
51
4.
DISCUSSION
Comparing results of different analyses in 2011 and 2012 BRUVS survey in Darwin Harbour
has enabled a conclusion that observed temporal changes in abundance of some fish
species in monitored fish assemblages were mainly related to variations in amounts of two
ecological groups of fish: a) pelagic school and non-school fast moving fish and b) demersal
open bottom fish. These groups dominated both reefs and open bottom areas at monitoring
sites. Pelagic fishes are represented in Darwin Harbour by several species of trevallies,
scads and School Mackerel; demersal open bottom fishes include threadfin breams and
ponyfishes. Both groups were particularly abundant at “outer” part of the Harbour where open
bottom habitat (sand, silted sand and silt with very scarce rocks, algae and macro
epibenthos) dominated. Open bottom is a habitat providing limited protection from predators.
Small and medium size fishes that live here are school species, those coordinated manner of
swimming provide relative protections from solitary predators, enhance foraging success,
reproductive advances, helping to navigate in diel movements and seasonal migrations
(Breder 1967, Radakov 1973, Shaw 1978, Parrish, Viscedo, & Grunbaum 2002, Steele &
Anderson 2006, Travers et al. 2010). Other fishes inhabiting open bottom areas are large
mid-water, demersal or benthic predators – trevallies, mackerels, sharks and rays. Most open
bottom inhabitants are nomadic or have large home ranges and are constantly roving
through habitat searching for food sources: phyto- and zooplankton, bottom epibenthos or
fish for predatory species. After food resources in local area have depleted fish are moving
away. Changes in fish species richness, population density biomass are common, therefore
fish communities in open bottom areas are very dynamic (Hubbs 1974, Yazhi 1982, Ambrose
& Meffert 1999, Letourneur et al. 2001, Allen et al. 2006). Our underwater video observations
confirmed that fish abundance at monitoring station could change dramatically within several
minutes because of arrival or departure of the school of trevally or scad.
Variability in fish numbers is not restricted to open bottom areas. More short, but regular
movement are typical for some residents of rocky reefs utilising open bottom areas and sea
grass beds attracted by food sources available here (Hobson 1972, Robblee & Zieman 1984,
Gomelyuk et al. 1985, Hobson & Chess 1986, Lowry & Suthers 1998, Unsworth et al. 2007,
Chateau & Wantiez 2009).
There is also another important basis for natural variations in small and medium size school
fish abundance. Majority of them are very fast growing and short living and their population
numbers are prone to frequent and wide fluctuations in their numbers - “waves of life”, typical
52
for organisms with r-strategy (Chetverikov 1915, Timofeev-Resovskii 1958, Pianka 1970,
McFarlane & Beamish 2001). In a review done on life history traits and population regulation
in marine fishes Kawasaki (1980, 1983) suggested that the grouping of life history traits of
marine fishes is more complex than the traditional r and K strategists concept developed for
terrestrial animals (MacArthur & Wilson 1967). A quantitative approach to develop grouping
of life history strategies in fishes lead to identifying next three endpoint strategies: (1) small,
rapidly maturing, short-lived fishes (opportunistic strategists); (2) larger, highly fecund fishes
with longer life spans (periodic strategists); and (3) fishes of intermediate size that often
exhibit parental investment and produce fewer, larger offspring (equilibrium strategists)
(Winemiller & Rose 1992, McCann & Shuter 1997, King & McFarlane 2003).
Small school pelagic trevallies and benthic threadfin breams and ponyfishes dominated fish
assemblages at both “outer” and “inner” monitoring stations, reef and open bottom habitats
belongs to “opportunistic strategists”. Such species have a shorter generation time, fast rate
of population growth, despite low individual fecundity (King & MacFarlane 2003).
“Opportunistic strategists” occupy habitats with a high degree of variability of biotic and
abiotic factors, but potentially, with large food resources (epibenthos, zooplankton).
Therefore, their population responses tend to be large in amplitude and species grouped
according to this life history strategy have been classified as having either cyclical, irregular
or spasmodic population patterns (Caddy & Gulland 1983; Kawasaki 1983; Spencer & Collie
1997). This may result in quick and frequent changes in fish abundance, increasing variability
in structure and composition of fish assemblages at open bottom areas. Our data supporting
this assumption: notable changes in assemblages both at open sandy/silty bottom at “outer”
and “inner” part of the Harbour were due to “opportunistic strategists” - small school
trevallies, scads, threadfin breams and pony fishes.
Still, because opportunistic strategists are abundant and common species, they are
significant part of in inshore ecosystems, playing an important role in food-web as consumers
and as a forage fish for predatory fish and dolphins (Parra & Jedensjö 2013). Interpretation of
results of monitoring when these species is intricate: on the one hand, there is no need for
the immediate alarm if temporal decline in these species was recorded. On the other hand, a
persistent decline in such species for several years may be an indicator of possible serious
changes in ecosystem leading to an “cascading reaction” in the future, and therefore should
not be taken lightly. Because of relatively high population numbers, data “opportunistic
strategists” can be analysed using powerful statistical tools.
53
Contrary to the above group, “periodic strategists” are medium to large size slow-growing,
long-lived species. They have a lower degree of variability in abundance and have been
classified as having a steady-state population pattern (Caddy & Gulland 1983, King &
MacFarlane 2003). In Darwin Harbour this group is represented by snappers (family
Lutjanidae), gropers (family Serranidae) and mackerels (Scombridae). Longevity (i.e. lifespan
greater than 20 years) benefits these species by ensuring a relatively long reproductive
cycle, which minimizes the risk that periods of unfavourable environmental conditions that will
result in the loss of a stock (Edwards 1984, Leaman & Beamish 1984, Ralston 1987),
Newman et al. 2000). Skates and larger sharks belong to “equilibrium strategists” (King &
MacFarlane 2003). Both “periodic” and “equilibrium strategists” require very careful
monitoring. Despite of their protection from the loss of stocks during the period of
unfavourable environmental conditions, their recruitment is not constant and they are very
vulnerable to anthropogenic impact – from fishing pressure to habitat loss (King &
MacFarlane 2003). Unfortunately, these species have relatively low numbers in collected
data for a robust statistical analysis.
A usefulness of different indices and statistical analyses method for fish biodiversity
monitoring.
Different statistical analyses produce a range of metrics that may indicate different
significance level of a test. In order to understand what indices identify a meaningful and
significant change for monitoring, it is important to differentiate between statistical
significance and biological significance. Statistical significance relies on probability and is
influenced by sample size. Thus, even trivial changes (from a biological perspective) can be
judged to be statistically significant if the sample size is large enough. Therefore, it is
important to be able to identify something biologically significant that represents a major shift
in fish abundance, assemblage structure and biodiversity. A statistical significant change is
not always biologically significant, but a biologically significant change must also be
statistically significant. Eventually, the power of a statistical comparison is the ability to detect
a biologically meaningful change (Fairweather 1991).
Ecological monitoring data is collected from small area, only miniscule fraction of entire area
of population distribution. Interpretation of the results should be able to discriminate between
“a genuine” fish decline and changes caused by fish re-distribution during diel and seasonal
movement, ontogenetic habitat shift (Allen, Pondella II and Horn 2006), local elimination of
the portion of population by predators, die off of some individuals of short-living species. The
later changes are common in “opportunistic strategists” populations (Lowe-McConnell 1987,
King & MacFarlane 2003), particularly in high mobile species like school trevallies, scads,
54
and ponyfishes. Quite often, such changes within a single monitoring station are local
phenomenon, not based on (and not reflecting) significant changes in entire population.
Decrease in abundance of “opportunistic strategists” may lead to notable changes in fish
assemblage composition and structure at some monitoring. However, if “periodic” and
“equilibrium” strategists have not been affected and if such changes were recorded only at
the limited number of monitoring stations chances what adverse factor are operating in the
environment are low. Contrary, acute or chronic increase of adverse factors, both
environmental and anthropogenic generally can affect sensitive species from opportunistic,
periodic and equilibrium strategists. The impact can manifest themselves in different ways,
from elimination of sedentary species due to the habitat degradation and loss to mobile
species move from unfavourably altered environment (Leach et al. 1977, Jeff et al. 2001,
Launois et al. 2011). The important task of discrimination between these two types of
changes is difficult (Whitfield & Elliott 2002). This task become particularly challenging if
information on life history and “natural” variability of monitored object is absent or very limited
and this is exactly the case for fish assemblages in Northern Australia.
There were no major disagreements in results of employed different types of statistical
analysis. However, univariate analysis appears to be less sensitive and has provided very
limited insight on what actually caused changes in monitored fish assemblages because only
one dependent variable being analysed. Multivariate analyses applied to the same set of
data were more sensitive and informative, enabling to find that species contributed to
detected changes in monitored assemblages. Thus, relying solely on univariate analysis may
lead to making type II error while an entire relying on results of multivariate analysis based on
assessment of dissimilarity between assemblages may lead to type I error in fish
assemblages monitoring. Therefore, the result, of different types of comparison can be
interpreted only in conjunction.
Changes in fish assemblages at monitoring station in Darwin Harbour in 2011-2012.
There were no major noticeable changes in environmental and anthropogenic adverse
factors in monitored parts Darwin Harbour environment in 2011-2012 (Darwin Harbour
Region Report Cards 2011, 2012). Therefore, it appears, that observed annual differences in
fish communities are the result of fish re-distribution rather than a result of decline in fish
abundance and biodiversity. Small school pelagic and demersal species that belong to
“opportunistic strategists” group (trevallies, threadfin breams and ponyfishes) are major
contributors to fish assemblage variability. Natural fluctuations in their abundance can cause
swift and often unpredictable changes in fish assemblages structure and abundance. Indeed,
55
these fluctuations should not be assumed as an “information noise” and therefore excluded
from monitoring. BRUVS monitoring stations in Darwin Harbour cover a substantial area;
thus, it is possible to distinguish between genuine changes in these species abundance and
their re-distribution. Further monitoring can provide an important information on temporal and
spatial variability in these fishes abundance and natural variations in local fish assemblages.
Cooperatively with other types of monitoring (water quality, etc.) obtained information can be
used as an important indicator for assessment of changes resulted from anthropogenic
pressure on Darwin Harbour ecosystems.
5.
Acknowledgements
Many people contributed to making this study possible. Larrakia Rangers, Yolande Alley and
Yolande Alley participated in a boat trips and have helped with all their effort and enthusiasm.
Robyn Henderson from Water Resources was very helpful in coordinating our cooperation
with Larrakia Rangers. Division Department of Resources – Fisheries provided the boat.
Nathan Crofts, Wayne Baldwin and Poncie Kurnoth from Department of Resources –
Fisheries were boat skippers and their contribution was invaluable for safe marine operation
and data collection. Daniel Low Choy provided logistic support. I am particularly thankful to
Tony Griffiths who provided extensive editions and comments to the draft.
6.
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7.
APPENDIX
Table 12. Post hoc power analysis of F tests one-way ANOVA of values of mean fish species
number at
North-West Channel Island site in Darwin Harbour, stations 1-NCHB, 2-NCHB and 4RCK-NCH in
2011-2012.
Input
Effect size f
0.515
α err prob
0.050
Total sample size
36
Output
Number of groups
6
Noncentrality parameter λ
29.554
Critical F
2.534
Numerator df
5
Denominator df
30
Achieved power (1-β err prob)
0.964
Table 13. Post hoc power analysis of F tests one-way ANOVA of values of mean MaxN at NorthWest Channel Island site in Darwin Harbour, stations 1-NCHB, 2-NCHB and 4RCK-NCH in 20112012.
Input
Effect size f
1.141
α err prob
0.05
Total sample size
36
Output
Number of groups
6
Noncentrality parameter λ
46.899
Critical F
2.533
Numerator df
5
Denominator df
30
Power (1-β err prob)
0.999
62
Table 14. Post hoc power analysis of F tests one-way ANOVA of values of mean fish species
number at The Entrance site in Darwin Harbour, stations DSAC-B, 8-RCK and 6-RCK in 20112012.
Input
Effect size f
0.715
α err prob
0.05
Total sample size
36
Output
Number of groups
6
Noncentrality parameter λ
18.427
Critical F
2.534
Numerator df
5
Denominator df
30
Power (1-β err prob)
0.875
Table 15. Post hoc power analysis of F tests one-way ANOVA of values of mean MaxN at
The Entrance site in Darwin Harbour, stations DSAC-B, 8-RCK and 6-RCK in 2011-2012.
Input
Effect size f
0.993
α err prob
0.05
Total sample size
36
Output
Number of groups
6
Noncentrality parameter λ
29.588
Critical F
2.620
Numerator df
5
Denominator df
30
Power (1-β err prob)
0.978
63
Table 16. Post hoc power analysis of F tests one-way ANOVA of values of mean fish species
number at Rick Mills artificial reef site in Darwin Harbour, stations RM-1, RM-2 and RM-3 in
2011-2012.
Input
Effect size f
0.867
α err prob
0.05
Total sample size
36
Output
Number of groups
6
Noncentrality parameter λ
27.065
Critical F
2.533
Numerator df
5
Denominator df
30
Power (1-β err prob)
0.973
Table 17. Post hoc power analysis of F tests one-way ANOVA of values of MaxN at
Rick Mills artificial reef site in Darwin Harbour, stations RM-1, RM-2 and RM-3 in 2011-2012.
Input
Effect size f
0.8152
α err prob
0.05
Total sample size
36
Output
Number of groups
6
Noncentrality parameter λ
23.926
Critical F
2.533
Numerator df
5
Denominator df
30
Power (1-β err prob)
0.951
64
Table 18. Post hoc power analysis of F tests one-way ANOVA of values of mean fish species
number at Bottle Washer artificial reef site in Darwin Harbour, stations BW-1, BW-2 and BW-3 in
2011-2012.
Input
Effect size f
0.740
α err prob
0.05
Total sample size
36
Output
Number of groups
6
Noncentrality parameter λ
19.733
Critical F
2.533
Numerator df
5
Denominator df
30
Power (1-β err prob)
0.899
Table 19. Post hoc power analysis of F tests one-way ANOVA of values of MaxN at Bottle
Washer artificial reef site in Darwin Harbour, stations BW-1, BW-2 and BW-3 in 2011-2012.
Input
Effect size f
0.815
α err prob
0.05
Total sample size
36
Output
Number of groups
6
Noncentrality parameter λ
23.926
Critical F
2.533
Numerator df
5
Denominator df
30
Power (1-β err prob)
0.951
65
Table 20. ANOVA of number of fish species in one 1-hour BRUVS video sample, pooled data
of 12 monitoring stations in Darwin Harbour in 2011-2011.
Source
Outer-Inner stations*Years
Error
Type III SS
866.805
1,136.035
df
3
152
Mean Squares
288.035
7.474
F-Ratio
38.659
p-Value
0.000
Table 21. ANOVA of number of fish in one 1-hour BRUVS video sample (MaxN), pooled data
of 12 monitoring stations in Darwin Harbour in 2011-2011.
Source
Outer-Inner stations*Years
Error
Type III SS
16,655.660
33,871.333
df
3
152
Mean Squares
5,551.887
222.838
F-Ratio
24.914
p-Value
0.000
Table 22. ANOVA of mean fish number (MaxN) in BRUVS samples at three monitoring stations
at North-West site of Channel Island in Darwin Harbour in 2011-2012.
Source
Stations *Years
Error
Type III SS
2,103.000
1,971.000
df
11
60
Mean Squares
191.182
32.850
F-Ratio
5.820
p0.000
Value
Table 23. ANOVA of mean fish species number (FSN) in BRUVS samples at three monitoring
stations at North-West site of Channel Island in Darwin Harbour in 2011-2012.
Source
Stations *Years
Error
Type III SS
25.139
95.833
df
5
30
Mean Squares
5.028
3.194
F-Ratio
1.574
p0.198
Value
Table 24. ANOVA of mean fish number (MaxN) in BRUVS samples at three monitoring stations
at Entrance site, Darwin Harbour in 2011-2012.
Source
Stations *Years
Type III SS
1,112.472
df
5
Mean Squares
222.494
F-Ratio
5.042
p0.002
Value
66
Error
1,323.833
30
44.128
Table 25. ANOVA of mean mean fish species number (FSN) in BRUVS samples at three
monitoring stations at the Entrance site, Darwin Harbour in 2011-2012.
Source
Stations
Error
*Years
Type III SS
71.889
138.333
df
5
30
Mean Squares
14.378
4.611
F-Ratio
3.118
p0.022
Value
Table 26. ANOVA of mean fish number (MaxN) in BRUVS samples at three monitoring
stations at Rick Mills artificial reef site, Darwin Harbour in 2011-2012.
Source
Stations
Error
*Years
Type III SS
5,700.250
10,516.500
df
5
30
Mean Squares
1,140.050
350.550
F-Ratio
3.252
p-Value
0.018
Table 27. ANOVA of mean mean fish species number (FSN) in BRUVS samples at three
monitoring stations at Rick Mills artificial reef site,Darwin Harbour in 2011-2012.
Source
Stations
Error
*Years
Type III SS
176.472
202.500
df
5
30
Mean Squares
35.294
6.750
F-Ratio
5.229
p-Value
0.001
Table 28. ANOVA of mean fish number (MaxN) in BRUVS samples at three monitoring
stations at Bottle Washer artificial reef site, Darwin Harbour in 2011-2012.
Source
Stations
Error
*Years
Type III SS
8,075.793
5,972.688
df
5
30
Mean Squares
1,615.159
199.090
F-Ratio
8.113
p-Value
0.001
67
Table 29. ANOVA of mean mean fish species number (FSN) in BRUVS samples at three
monitoring stations at Bottle Washer artificial reef site,Darwin Harbour in 2011-2012.
Source
Stations
Error
*Years
Type III SS
264.333
486.667
df
5
30
Mean Squares
52.867
16.222
F-Ratio
3.259
p-Value
0.018
68