Download TEAM 2 QUEST 06 PAPER

Coral and algal community composition among
depths at Ke’ei: Does the intermediate
disturbance hypothesis apply?
Final Report
QUEST 2006
Team 2
Staff Advisor: Jen Smith
Team Leader: Elizabeth Murphy
Team members:
Nathan Olson
Andrea Rivera
Jason Trimble
May 26, 2006
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Abstract
During the Quantitative Underwater Ecological Survey Techniques (QUEST)
field school offered through the University of Hawaii at Hilo held at Ke’ei, we found
the Intermediate Disturbance Hypothesis (Hughes and Connell 1999) to be supported
through the analysis of coral and algal species composition. Wave action is a physical
disturbance that presumeably varies among depths at Ke’ei. Wave action is likely to
be highest on the reef flat (15 ft), lowest at 40 ft., and intermediate at 25 ft. Using
data collected by the benthic grid survey method, we calculated species richness and
the Shannon-Wiener Index to measure diversity. Both species richness and the
Shannon-Wiener Index were statistically analysed to test for differences among
isobaths (15ft, 25ft, and 40ft.). No statistically significant difference was observed,
but an apparent trend emerged. We conducted power tests to determine appropriate
sample sizes (about 100 quadrats) for future studies. We also compared percent cover
of the three most abundant groups surveyed (Porites lobata, Porites compressa, and
turf algae) among isobaths. Results from the analysis of variance (ANOVA)
supported the Intermediate Disturbance Hypothesis. Turf algae dominated on the reef
flat and P. compressa dominated at 40ft., but P. lobata, P. compressa, and turf algae
abundances were fairly even at 25ft. Upon analysis of the overall data collected, we
concluded that future studies collecting a larger number of samples at more depths is
needed to statistically support the Intermediate Disturbance Hypothesis with regard to
benthic cover in Ke’ei.
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1. Introduction
The Hawaiian archipelago is one of the most isolated island chains in the
world and is widely recognized for its vast marine diversity. Coral reef ecosystems
are characterized by extremely high autotrophic and heterotrophic production,
supporting the existence of a dense and diverse community of fish and benthos
(Surokin 1989). It is important to study reefs before and after disturbances, such as
hurricanes and excessive wave action, to further understand the natural and ecological
phase shifts within the systems. In addition, as coastal development and
anthropogenic stresses continue to increase, nutrient loading affects re-colonization,
recruitment, and phase shifts from coral to algal dominated reefs. We based our
hypotheses on the Intermediate Disturbance Hypothesis, which predicts that species
diversity is greatest in areas where the frequency of disturbance is neither too low nor
too great (Hughes & Connell 1999). Our focus was physical disturbance, wave action
in particular, which presumably decreases with depth along the reef. We predicted
that the highest number of species, including corals and algae, is highest in mid
isobaths, where wave action is neither intense nor absent. These zone placements can
vary depending on location, therefore it is important to investigate the phenomenon
locally.
According to coral reef zonation, shallower depths may have a greater
abundance of larger, more rugged corals such as Porites lobata due to their higher
tolerance of wave action. At the same time, deeper depths may have a greater
abundance of columnar corals such as Porites compressa, due to their rapid growth
and subsequent domination in calmer waters. Our overall question was: how does
percent benthic cover and species diversity in Ke’ei vary among depths of 15 ft., 25
ft., and 40 ft. isobaths? Our null hypotheses were: (1) algal species diversity is
3
similar among depths, (2) coral species diversity is similar among depths, and (3)
dominant coral and algal percent cover is similar among depths.
Our study site was in the Kealakekua Bay Marine Life Conservation District, a
recently established Fish Replenishment Area that protects fish from aquarium
collectors on the West side of Hawaii.
During the Qualitative Underwater and
Ecological Surveying Techniques (QUEST) course offered through the University of
Hawaii at Hilo, students learned techniques to monitor coral reef ecosystems while
using SCUBA. We choose the benthic grid method to analyze our data because it was
more comprehensive than point intercept in terms of species diversity and more
accurate than photo quad in terms of species identification. Photographic processing
also tended to under represent less abundant and rare species. Within this report we
included all analyzed data, as well as descriptions of all methods learned and used
during QUEST and any observations made by our team members.
2. Materials & Methods
2.1 Research Site
All data were collected using SCUBA at Ke’ei beach in Kealakekua Bay, on
the Big Island of Hawaii (Figure 1). A base line transect was laid from the reef flat
to the 40 ft. isobath. From the baseline, transects were laid along replicate isobaths:
40’ isobath (19º 27’ 46.6”, 155º 55’ 35.7”), 25’ isobath (19º 27’ 45.2”, 155º 55’
35.0”), outer reef flat (19º 27’ 44.4”, 155º 55’ 34.6”) and inner reef flat (19º 27’
44.0”, 55º 55’ 34.5”). All transect lines used were 50 m long, except for when noted.
2.2 Water Quality and Rugosity
a. Sample Collection
4
Our team collected water quality and rugosity data together at the 25 ft.
isobath along a 50 m transect. We collected water from near the reef surface in 500
mL dark Nalgene bottles to measure chlorophyll a concentration, temperature, and
salinity. We also collected water in 60 mL syringes to measure nutrients (nitrate and
silicate) concentrations. We took samples at 10 m intervals along the transect.
b. Nutrient Analysis
We primed each syringe three times, and then attached a piece of acrylic
tubing to collect water from within the reef structure. We filtered 13 mL of water
from each syringe through a pre-combusted GF/F 25 mm glass fiber filter into a 15
mL centrifuge tube that was placed on ice and taken to the quantitative analysis lab at
the University of Hawaii at Hilo for analysis of nutrient concentrations.
c. Temperatuure, Salinity, and Chlorophyll a Analysis
We measured temperature and salinity immediately after surfacing using a
YSI model 85. From each Nalgene bottle sample, we filtered 50 mL of water through
a 25 mm glass fiber filter. This was repeated twice for each sample. Then, we
immersed each filter in a test tube with acetone. After four hours on ice in the dark
we centrifuged the test tubes for seven minutes. Next, we measured chlorophyll a
concentration using a Turner florometer.
d. Rugosity
We measured rugosity using a 1 cm link size brass chain laid along the
transect line. We attached a float at five meter intervals along the chain and recorded
the corresponding length along the transect.
5
2.3 Mobile Invertebrates
Our team surveyed mobile invertebrates at the 40 ft. isobath along a 50 m
transect.
We placed a 0.25 m2 quadrat every three meters and quantified all
invertebrates, excluding coral species, present within it. We also estimated percent
substrate cover for each quadrat.
2.4 Percent Benthic Cover
a. Point Intercept
Our team used point intercept to measure percent cover at the outer reef flat
along a 50 m transect. We placed 0.25 m2 quadrats at 14 pre-selected random points
along the transect.
Each quadrat contained 25 points where we identified and
recorded the benthic species. From this data, we calculated the percent benthic cover.
b. Grid Quad
Our team used the grid method to measure percent cover at the 25 ft. isobath
along a 50 m transect. We placed 0.25 m2 quadrats at 14 pre-selected random points
along the transect. To simplify abundance estimates, percent cover was estimated in
each of the four quadrants for each quadrat. From this data, we calculated percent
benthic cover.
c. Photo Quad
Our team used photo quad to measure percent cover along 50 m transects at
the 40 ft. isobath (using flash) and the 25 ft. isobath (using white balance). For each
photographic survey dive, a 0.25 m2 quadrat was placed at 12 pre-selected random
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points along the transect. We took digital photographs of each quadrat placement. At
the 40’ isobath, we used a Sony Cybershot 4.0 megapixle digital camera; and at the
25’ isobath we used a Sony Cybershot 7.2 megapixle digital camera. We modified
the pictures using Adobe Photoshop 6.01, and then we conducted point grid analysis
using Photogrid 1.0 Beta. From this data, we calculated percent benthic cover.
2.5 Fish Species Abundance
a. Strip Survey Transect (SST)
Our team conducted a strip survey transect (SST) at the inner reef flat along
two 25 m transects. We laid a sixty foot transect and conducted surveys from: 1) 0 m
to 25 m, and 2) 35 m to 60 m. Buddy pairs were aligned on either side of the transect
and quantified all fish species within a 2 m wide by 4 m high area from either side of
the line.
b. Circular Plot (C-Plot)
Our team conducted two circular plots (C-Plots) at the 40 ft. isobath. Buddy
pairs were aligned vertically and back-to-back while each buddy surveyed half of a 10
m wide by 4 m high cylinder around himself/herself. A transect line and flagging
tape was used to mark the area. Fish species present were recorded for five minutes;
and then abundance of the fishes present in the first five minutes was tallied during
the second five minutes.
QUESTION SPECIFIC:
2.6 Species Diversity
a. Species Richness
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We analyzed species richness was by compiling data from the grid quad
method of determining percent cover. The total number of species was counted in
each quadrat to determine species richness. There were 27 samples on the 25 ft.
isobath, and 32 on both the reef flat and 40 ft. isobath.
b. Shannon-Wiener Index Formula
The Shannon-Wiener index formula takes into account both the number of
species and their relative abundance. The Shannon-Wiener index formula
is H '   Pi * log( Pi ) . Using the computer program PRIMER 5.0, we entered the
data from the benthic grid method into this formula to calculate diversity at each
isobath.
c. Individual Species Percent Cover Among Depths
We individually analyzed the data for the three most abundant benthic groups
at Ke’ei: Porites lobata, Porites compressa, and turf algae. Using the data from the
benthic grid method, we calculated and compared the means from each isobath.
d. Statistical Analysis
MINITAB 14 was used for all statistical tests. Bartlett’s and Levene’s tests
were used to test for equal variances. By comparing the results of the two tests we
were able to infer normality. We then used a One-Way Analysis of Variance
(ANOVA) test to compare mean species richness, Shannon-Wiener Indices, and
percent cover among depths. If the data were different, then a Tukey’s comparison’s
test was performed to further explain the difference. If the data were not determined
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to be different, then we performed a power analysis to determine the probability of a
type II error and how many more samples would be needed for powerful future study.
3. Results
3.1 Water Quality and Rugosity
a. Nutrient analysis
Nitrate concentrations at 15 ft and 40 ft in Ke’ei were statistically similar
(Figure 2). Compared to the other isobaths, the 25 ft transect had a higher
concentration of nitrate and a lower concentration of silicate.
b. Temperature, Salinity, and Chlorophyll-a analysis
Chlorophyll-a concentration was lowest in the deeper waters of 40 ft, and not
significant different between the other depths (15 ft. and 25 ft.) (Figure 3). Salinity
and temperature data where also collected, but were not used in our analyses because
they were not collected in-situ, so we thought them to be inaccurate. In addition, more
data are needed to conclude any further distribution patterns.
c. Rugosity
We calculated the rugosity value by dividing the five meter chain length
sections by the distance covered along the transect line. This gave us a unitless value
from which the mean and standard deviation of the rugosity could be calculated,
values are shown in (Figure 4). We found the rugosity to be similar among all
isobaths examined.
3.2 Mobile Invertebrates
For the benthic invertebrate survey performed, the means and standard error
for the number of species/groups present were analyzed. The taxonomic species
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present during the survey were: echinoderms, arthropods, annelidae, molluska, and
porifera. As a taxanomic group, echinoderms were the most abundant, and porifera
and molluska were the least abundant (Figure 5). Looking at single species/groups,
both Echinometra mathaei, and hermit crabs had the highest mean population per
quadrat. Herbivore invertebrates were the most prevalent tropic level.
3.4 Percent Benthic Cover
a. Point Intercept
Our team analyzed the Point intercept data using Microsoft Excel to illustrate
the percentage cover of the species found at the outer reef flat (Figure 6). The most
common coral species was Porites lobata (28%) and the highest percentage found
among algae was turf (50%). The second most common coral species was Porites
evermanii (14%). We expected turf algae to be of highest abundance at the reef flat
because this is an area of high wave action, making it less suitable for coral growth;
however, since turf algae is an assemblage and not a species, turf algae did not
account for species diversity, but accounts for benthic cover. Turf algae can be
difficult to quantify when there is no taxonomic key to differentiate species. In
addition, many species may be found within very small portions of substrate. Other
coral and algal species found included: Porites compressa (3%) Pocillopora
meandrina (1%), Crustose coralline algae (1%), and cyanobacteria (1%).
b. Grid Quad
See section 3.7
c. Photo Quad
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We used benthic marine photographic processing and analysis (Photogrid 1.0
beta) to calculate percent benthic cover. Using this method, we found Porites
compressa to be the most abundant coral species at 40 ft. in Ke’ei (Figure 7). Porites
lobata accounted for 9% of the substrate. The most common algal species at 40 ft.
was turf algae (25%), followed by Tolypiocladia glomerata (21%), and crustose
coralline algae (13%). During our second dive, we surveyed the 25 ft. isobath and
found a high abundance of Porites lobata (27% cover) and turf algae (28% cover)
(Figure 8). This suggests a trend according to the intermediate disturbance
hypothesis, but it is not statistically significant. We also found sand to account for
about 20% of the substrate at 25 ft. Crustose coralline algae showed a similar
percentage in the first survey, with a percent cover of 21%.
When we cropped our pictures in Photoshop 6.01 partial portions of the
quadrat was left in the pictures. This caused some of the random numbers to fall
across quadrat points, which accounted for 3% of the percent benthic cover. This can
be avoided in the future by cropping most of the quadrats out of the photographs.
3.6 Fish Abundance
a. Strip Survey Transect
We sampled the inner reef flat at Ke’ei and found the following fish to be
most abundant using the SST method: Thalassoma duperrey (21  13), Paracirrhites
arcatus (41  2.5), Gomphosus varius (4  3.5) and Zebrasoma flavescencens (4  3)
(Figure 9). The three most abundant species were found more in the benthic portion
of the water column directly above, or in even within, the reef structure. These
species were best represented in this survey due to the fact that the surveyors were
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close to the benthos and could easily survey the benthic fish populations. The other
fishes present along the transect included: Plectroglyphidodon imparipennis,
Canthigaster jactator, Halichoeres ornatissimus, Melichthys vidua, Chromis ovalis,
Plectroglyphidodon johnstonianus, Chlorurus sordidus, Canthigaster amboinensis,
and Coris gaimard. A strong current and heavy surge during the survey caused many
of the fish to hide under reef cervices, some were visible, but not all.
b. Circular Plot
Using the C-Plot method at 40 ft., we found the most common fish species to
be: Chromis agilis (65  8), Ctenochaetus strigosus (27  8), and Zebrasoma
flavescencens (21  6.5) (Figure 10).
Also present were: Gomphosus varius,
Chaetodon ornatissimus, Acanthurus. nigrofuscus, Chromis vanderbilti, Thalasoma
duperrey,
Chaetodon
multicinctus,
Naso
lituratus,
Chromis
hanui,
Plectroglyphidodon johnstonianus, Chlorus sordidus, Scarus rubroviolaceus.
Acanthurus nigroris, Melichthyes vidua, Oxycheilinus unifasciatus, Stethojulis
balteata, and Cephalopholis argus. The three most abundant species are schooling
fishes; this fact can easily account for their proportionally high abundance meaning
that a school of these fish could of swam within the survey area. Also, due to the fact
that this survey was performed vertically within the water column, benthic fish
species may have been under represented. We believe that the 5 minutes allowed to
record species may not be enough time to record all fishes. We saw a larger number
of fish swimming into the sampling area after the time expired. We suggest that, for
future methods, the time allowed to let fish return to those areas where divers might
scare them off should be extended to perhaps 8-10 minutes.
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QUESTION SPECIFIC:
3.7 Species Diversity among Depths
Using the benthic grid survey method we found a pattern in diversity among
depths. First, using all of the data from the grid survey (abiotic and biotic responses),
we conducted a Bartlett’s test of equal variances and found that the variances were
equal. We observed a statistically insignificant pattern (P = 0.137) with benthic
diversity among depths using a One-Way ANOVA test (Table 4). We continued to
analyze the data by seperating data based upon either coral or algal groups. In
addition, we used two analytical methods for determining diversity: species richness
and the Shannon-Wiener Index Formula.
a. Species Richness
After breaking the observed data into groups, coral species diversity was first
analyzed using species richness. We conducted a Bartlett’s test of equal variances and
found them to be equal. Then, we used a One-Way ANOVA to determine if they were
statistically different among different isobaths. The test showed the different isobaths
to be different in diversity, but did not produce a statistically significant result (Table
6, P = 0.103).
Analyzing the data in terms of species of macroalgae produced a similar
statistically insignificant result using species richness data (Table 7, P = 0.163).
After conducting a Bartlett’s test of equal variances we found the variances to be
equal.
A One-Way ANOVA revealed that there was no statistically significant
difference among isobaths. The means revealed a statistically insignificant pattern,
with the 40 ft. isobath having the greatest diversity (Figure 12). The 15ft. (reef flat)
isobath was the least diverse.
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b. Shannon-Wiener Index
Using the Shannon-Wiener Index, we ascertained similar results for all groups
of benthic cover. After conducting a Bartlett’s test to determine equal variances, we
ran a One-Way ANOVA test. The results revealed a statistically insignificant pattern
(P = 0.390), with the 25 ft. isobath having the greatest diversity (Table 8). This was
consistent with the above method of computing species diversity.
Splitting the data into groups, we first examined coral diversity among depths
using the Shannon-Wiener Index. We ran a Bartlett’s test for equal variances and
found the variances to be equal. We then ran a One-Way ANOVA that produced
similar results (Table 9). We found that the 25 ft. isobath was the most diverse, and
the result was closer to statistically significant (P = 0.185) (Figure 12).
We found the same basic result using the Shannon-Wiener Index to calculate
diversity of macroalgal species.
Macroalgal diversity was greatest at the 40 ft.
isobath, but the results were not statistically significant (P = 0.182) (Table 10, Figure
12). The result was also consistent with the alternative method of calculating species
diversity.
c. Power and Sample Size
Using the pooled standard deviation from the ANOVA tests, we conducted
power tests for all of our results, as well as calculated an ideal sample size for future
studies (Table 11). For all of the tests we conducted, the power was insignificant by
a great margin. The necessary number of samples (quadrats) needs to be increased to
about 100 for adequate power.
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d. Percent Cover with Depth (Grid Quad)
Using the percent cover data from the benthic grid method, we found
statistically significant differences with depth.
We ran a Bartlett’s test and
determined that the variances were equal. We then ran an ANOVA test between turf
algae and isobath. We obtained statistically significant results (P = 0.01) (Figure 13),
and went on conduct a Tukey’s comparison test to test which isobaths were different.
We ascertained that the 15 ft. isobath was significantly different than the 40 ft. The 25
ft. isobath was not significantly different from the 40ft. or the 15ft. isobath.
Next, we compared Porites compressa among the three isobaths. Again, we
ran a Bartlett’s test to determine equal variances.
The ANOVA test revealed
significant difference (P = 0.028) (Table 12, Figure 13). Then, we ran a Tukey’s test
to determine which isobaths differed. Again, the 40 ft. isobath was different from the
15 ft. isobath. Also, the 25 ft. isobath was statistically similar to the 15ft. isobath, as
well as the 40 ft isobath.
We found somewhat different results when examining Porites lobata. After
running a Bartlett’s test for homogeneity, we ran an ANOVA test and found that there
was no detectable difference (P = 0.132) (Table 13, Figure 13). The mean percent
cover of Porites lobata was lowest at the 15 ft. isobath and was greatest at the 40 ft.
isobath.
4. Discussion
Coral and algal species diversity were statistically similar among depths at
Ke’ei. However, trends were evident that were consistent with the Intermediate
Disturbance Hypothesis (Figure 11, 12) (Hughes and Connell 1999). For example,
the intermediate zone of 25 ft. had the greatest species richness among depths (Table
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6, Figure 11). Using the Shannon-Wiener Index, we also found the greatest coral
diversity at the 25 ft. isobath (Table 8, Figure 11). However, more studies are
needed to clarify these trends.
We found a slightly different pattern of algal diversity among isobaths.
According to both analytical methods, algal diversity was greatest at the 40 ft isobath
(Tables 7, 10, Figure 12). To support the Intermediate Disturbance Hypothesis,
more studies must be conducted to determine if diversity of algae decreases with
depth. It is also possible that physical disturbances do not influence algae growth as
much as coral growth. Other factors, such as grazing must be investigated.
Since data were collected for the QUEST class, sample size was limited by
field time. Power tests determined that our sample size was not sufficient to detect a
change (Table 11).
For power testing, each 0.25 m2 quadrat was considered a
sample. Using the pooled standard deviation from our samples, we determined that
an appropriate sample sizes for future studies is between 95 and 120. Perhaps future
studies could use larger quadrats, as well as greater differences between isobaths, to
reduce the necessary amount of samples. Conservative safety regulations of the class
limited the isobaths that could be surveyed.
Since QUEST students are just beginning scientific diving, possible species
misidentification must be considered.
Also, we could not distinguish between
different crustose coralline species and different turf algae species. A turf algae
community consists of an assemblage of species and the exact species composition
can only be determined through extensive microscopic analysis. Species composition
of crustose coralline algae assemblages is unknown due to a lack of research.
Therefore, compositions of both of these groups were analyzed above the species
level.
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When testing the Intermediate Disturbance Hypothesis, it also important to
realize that there are a number of disturbances affecting an area at any given time.
Another possible disturbance at Ke’ei is predation by corallivores including, such as
Acanthaster planci and Forcipiger logirostris, and herbivorores, such as Zebrasoma
flavessence
and Echinmetra matheai.
Abiotic disturbances could include
temperature and nutrient fluctuations due to ground water input.
It is well
documented that there is a significant level of ground water entering Ke’ei Bay (Bill
Walsh, presentation 05/24/06). Nutrient input may be a chronic disturbance that
could be the cause for turf algae abundance along the reef flat. This is because high
levels of nutrients are beneficial to primary producers, such as algae, but may be
detrimental to the coral-zooxanthellae symbiosis in excessive amounts.
In any ecosystem, species diversity is important for the stability and resilience
of the system. Coral reefs are one of the most diverse ecosystems in the world and it
is important to understand the factors influencing their diversity and to be able to
apply this reasoning to managing reef ecosystems. This has been achieved in this
study using Connell’s Intermediate Disturbance Hypothesis. Data collected during
this study seem to support the Intermediate Disturbance Hypothesis although more
data are needed to adequately test this hypothesis.
Natural disturbances on coral reefs include wave action and predation. If
highest diversity is not found in areas of intermediate wave action and predation, then
other factors, such as anthropogenic nutrient input, may be adversely affecting the
reef. By examining natural disturbances in relation to coral and algal diversity,
perhaps it is possible to assess the health of a reef. Data collected during QUEST
2006 can be used to as a baseline for future monitoring and for management of
Ke’ei’s reefs and reef resources.
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The results for percent cover of Porites compressa, Porites lobata, and turf
algae further support the intermediate disturbance theory (Hughes and Connell 1999).
Looking at the bar graph that was produced (Figure 13) we can see how the diversity
of these three groups changes with depth. We found that on the reef flat, turf algae
sticks out as the most abundant group, perhaps because of the high wave action does
not allow anything else to stick to the substrate. We also found that on the 40ft.
isobath Porites compressa sticks out as the dominant species because of its fast
growth rate despite its columnar structure that would make it susceptible to high wave
energy. We found that on the 25ft. isobath there was no statistical difference between
these three groups, and that they were equally abundant. This data would lead us to
believe that the intermediate depth for these groups resides somewhere close to our
25ft. isobath.
The coral reef at Ke’ei appears to be in a healthy and stable state based upon
the low abundance of macroalgal cover in proportion to coral cover as well as great
diversity and abundance of fish and invertebrates populations (other QUEST 2006
reports). Due to the current declining state of the world’s coral reefs it is important to
protect healthy reefs like the one studied for this report. Through the maintenance of
healthy reefs more can be learned about coral reef ecosystems and how to properly
direct conservation and restoration efforts.
Acknowledgements
We would like to thank the QUEST 2006 staff, especially Dr. Jennifer Smith
for her advice and guidance through this report. QUEST would not be possible
without Mr. John Coney’s assistance and organization.
Thank you to Kevin
Flannagan for being lead diver and primary dive instructor. We would also like to
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thank Kahmehameha Schools and Bishop Estates for allowing us access to the field
school site. Connie Pua and Glennon Gingo are greatly appreciated for feeding our
bodies and minds.
Literature Cited
Fenner, D. 2005. Corals of Hawai’i. A field guide to the hard, black, and soft corals of
Hawaii and the Northwest Hawaiian Islands including Midway. Mutual
Publishing, . Honolulu Hawaii 96816.
Hawaii Fishing Regulations. February 2006. Board of Land and Natural Resources,
Division of Aquatic Resources, Honolulu, Hawai’i 96813.
Hoover, J.P. 2003. Hawaii Fishes. A guide for snorkelers, divers and aquarist. Mutual
Publishing. Honolulu Hawaii 96816.
Hughes, T.P., Connell, J.H. 1999. Muultiple stressors on coral reefs: a long term
perspective. Limnology and Oceanography. 44: 932-940.
Jompa, J., McCook, LJ. 2002. Effects of competition and herbivory on interactions
between a hard coral and a brown alga. J. Exp. Mar. Biol. Ecol. Vol. 271, pp.
25-39. Elsev. Sci. B.V
Sorokin Yuri I., 1989. Coral Reef Ecology, Ecol. Stud. Vol. 20 Springer-Verlag
Berlin Heindelberg, NY, USA.
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APPENDIX 1:
Tables
Table 1:
Photo Quad Ke'ei 25' Left
Species
n
Mean % Cover
Standard Error
Porites compressa
12
8
4.0
Porites lobata
12
27
6.0
Tolypiocladia glomerata
12
3
1.6
Turf algae
12
28
8.2
Crustose coralline
12
11
2.6
Sand
12
20
2.9
Quadrat
12
3
0.8
TOTAL
100
Table 2:
Photo Quad Ke'ei 40' Right
Mean %
Standard
Species
n
Cover
Error
Porites compressa
12
24
3.2
Porites lobata
12
9
4.6
Tolypiocladia glomerata
12
21
5.2
Turf algae
12
25
4.0
Crustose coralline
12
13
3.2
Quadrat
12
8
1.0
TOTAL
50
20
Table 3: Coral and algal species present among isobaths.
15 ft
25 ft
40 ft
P. compressa
X
X
X
P. evermanii
X
P. lobata
X
X
X
X
P. meandrina
M. capitata
X
M. patula
X
X
X
X
P. varians
L. bottae
X
C. ocellina
X
Turf algae
X
X
X
Crustose coralline
X
X
X
Galaxaura
X
Turbinaria
X
T. glomerata
X
X
X
Cyanobacteria
X
X
Table 4:
One-way ANOVA: Benthic Fauna versus Isobath
Source
Isobath
Error
Total
DF
2
88
90
S = 1.225
Level
25
40
RF
N
27
32
32
SS
6.09
132.02
138.11
MS
3.05
1.50
R-Sq = 4.41%
Mean
3.630
3.406
3.000
StDev
1.115
1.214
1.320
F
2.03
P
0.137
R-Sq(adj) = 2.24%
Individual 95% CIs For Mean Based on
Pooled StDev
------+---------+---------+---------+--(-----------*----------)
(----------*----------)
(----------*----------)
------+---------+---------+---------+--2.80
3.20
3.60
4.00
21
Table 5:
One-way ANOVA: Coral Diversity versus Isobath
Source
Isobath
Error
Total
DF
2
88
90
S = 0.7962
SS
2.958
55.789
58.747
Level
25
40
RF
MS
1.479
0.634
N
27
32
32
R-Sq = 5.03%
Mean
1.9259
1.5313
1.5313
StDev
0.6752
0.8026
0.8793
F
2.33
P
0.103
R-Sq(adj) = 2.88%
Individual 95% CIs For Mean Based on
Pooled StDev
+---------+---------+---------+--------(-----------*-----------)
(----------*----------)
(----------*----------)
+---------+---------+---------+--------1.25
1.50
1.75
2.00
Table 6:
One-way ANOVA: Algal Diversity versus Isobath
Source
Isobath
Error
Total
DF
2
88
90
S = 0.8468
Level
25
40
RF
N
27
32
32
SS
2.660
63.098
65.758
MS
1.330
0.717
R-Sq = 4.04%
Mean
1.7037
1.8750
1.4688
StDev
0.8234
0.9070
0.8026
F
1.85
P
0.163
R-Sq(adj) = 1.86%
Individual 95% CIs For Mean Based on
Pooled StDev
-+---------+---------+---------+-------(----------*----------)
(---------*--------)
(---------*---------)
-+---------+---------+---------+-------1.20
1.50
1.80
2.10
22
Table 7:
One-way ANOVA: Benthic Fauna via Shannon-Wiener versus Isobath
Source
Isobath
Error
Total
DF
2
88
90
S = 0.3309
SS
0.208
9.637
9.845
Level
25
40
RF
MS
0.104
0.110
R-Sq = 2.12%
N
27
32
32
Mean
0.9259
0.8775
0.8080
StDev
0.2631
0.3621
0.3488
F
0.95
P
0.390
R-Sq(adj) = 0.00%
Individual 95% CIs For Mean Based on
Pooled StDev
-+---------+---------+---------+-------(------------*-----------)
(-----------*----------)
(-----------*----------)
-+---------+---------+---------+-------0.70
0.80
0.90
1.00
Table 8:
One-way ANOVA: Coral Diversity via Shannon-Wiener versus Isobath
Source
Isobath
Error
Total
DF
2
88
90
S = 0.3212
Level
25
40
RF
N
27
32
32
SS
0.355
9.077
9.432
MS
0.178
0.103
R-Sq = 3.77%
Mean
0.3864
0.2368
0.2689
StDev
0.2823
0.3095
0.3608
F
1.72
P
0.185
R-Sq(adj) = 1.58%
Individual 95% CIs For Mean Based on
Pooled StDev
--------+---------+---------+---------+(------------*-----------)
(-----------*----------)
(----------*----------)
--------+---------+---------+---------+0.20
0.30
0.40
0.50
23
Table 9:
One-way ANOVA: Algal Diversity via Shannon-Wiener versus Isobath
Source
Isobath
Error
Total
DF
2
88
90
S = 0.3610
Level
25
40
RF
N
27
32
32
SS
0.452
11.470
11.923
MS
0.226
0.130
F
1.73
R-Sq = 3.79%
Mean
0.2978
0.3928
0.2252
StDev
0.3536
0.3741
0.3539
P
0.182
R-Sq(adj) = 1.61%
Individual 95% CIs For Mean Based on
Pooled StDev
--+---------+---------+---------+------(-----------*----------)
(----------*---------)
(----------*---------)
--+---------+---------+---------+------0.12
0.24
0.36
0.48
Table 10: Power Test to Determine Optimal Sample Size and Power of ANOVA
Tests
Depth
Sample
Greatest Difference
Test
(ft.)
Size
in Means
St. Dev.
Power
Needed (0.90)
Coral
25
27
0.4129
0.792
0.371889
95
Species
40
32
0.4129
0.792
0.434582
95
Richness
RF
32
0.4129
0.792
0.434582
95
Algal
25
27
0.4062
0.8468
0.320505
111
Species
40
32
0.4062
0.8468
0.375086
111
Richness
RF
32
0.4062
0.8468
0.375086
111
Coral
25
27
0.1496
0.3212
0.304102
118
Diversity
40
32
0.1496
0.3212
0.355862
118
(S-W)
RF
32
0.1496
0.3212
0.355862
118
Algal
25
27
0.1672
0.361
0.301095
119
Diversity
40
32
0.1672
0.361
0.352326
119
(S-W)
RF
32
0.1672
0.361
0.352326
119
24
Samples
Table 11:
One-way ANOVA: turf versus Isobath
Source
Isobath
Error
Total
DF
2
88
90
S = 25.19
Level
15
25
40
N
32
27
32
SS
9511
55831
65343
MS
4756
634
R-Sq = 14.56%
Mean
40.66
31.73
16.52
StDev
30.22
20.64
23.02
F
7.50
P
0.001
R-Sq(adj) = 12.61%
----+---------+---------+---------+----(------*------)
(-------*-------)
(-------*------)
----+---------+---------+---------+----12
24
36
48
Tukey 95% Simultaneous Confidence Intervals
Isobath = 15 subtracted from:
Isobath
Lower Center Upper
25
-24.62
-8.93
6.75
40
-39.15 -24.14 -9.14
Isobath = 25 subtracted from:
Isobath
Lower Center Upper
40
-30.89 -15.21
0.48
+---------+---------+---------+--------(-------*------)
(-------*------)
+---------+---------+---------+---------40
-20
0
20
+---------+---------+---------+--------(------*-------)
+---------+---------+---------+---------40
-20
0
20
25
Table 12:
One-way ANOVA: compressa versus Isobath
Source
Isobath
Error
Total
DF
2
88
90
S = 25.61
SS
4894
57695
62589
Level
15
25
40
MS
2447
656
R-Sq = 7.82%
N
32
27
32
Mean
17.50
28.48
34.80
F
3.73
P
0.028
R-Sq(adj) = 5.72%
StDev
25.90
23.46
27.00
-+---------+---------+---------+-------(--------*-------)
(--------*---------)
(--------*--------)
-+---------+---------+---------+-------10
20
30
40
Tukey 95% Simultaneous Confidence Intervals
Isobath = 15 subtracted
Isobath Lower Center
25
-4.96
10.98
40
2.05
17.30
from:
Upper
26.93
32.56
Isobath = 25 subtracted from:
Isobath Lower Center Upper
40
-9.62
6.32 22.27
-----+---------+---------+---------+---(---------*----------)
(----------*---------)
-----+---------+---------+---------+----15
0
15
30
-----+---------+---------+---------+---(---------*----------)
-----+---------+---------+---------+----15
0
15
30
Table 13:
One-way ANOVA: lobata versus Isobath
Source
Isobath
Error
Total
DF
2
88
90
S = 21.71
Level
15
25
40
N
32
27
32
SS
1953
41470
43423
MS
976
471
R-Sq = 4.50%
Mean
16.48
23.03
11.48
StDev
17.21
24.47
23.23
F
2.07
P
0.132
R-Sq(adj) = 2.33%
Individual 95% CIs For Mean Based on
Pooled StDev
----+---------+---------+---------+----(----------*---------)
(-----------*-----------)
(---------*----------)
----+---------+---------+---------+----7.0
14.0
21.0
28.0
26
APPENDIX 2:
Figures
260°
250°
40’
25’
55°
60°
240°
RF (Outer)
RF (Inner)
230°
Figure 1: Ke’ei transect map
27
Nutrient Concentrations across Depths at Ke'ei
3.5
Concentration (uM)
3.0
2.5
Nitrate
Silicate
2.0
1.5
1.0
0.5
0.0
15
25
Depth (ft)
40
Figure 2: (Mean ± Standard Error) Concentrations of nitrate and silicate among
depths at Ke’ei.
Chlorophyll-A across Depths in Ke'ei
0.80
Concentration (ug/L)
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
15
25
40
Depth (ft)
Figure 3: (Mean ± Standard Error) Chlorophyll a concentions among depths at
Ke’ei.
28
Rugosity at Ke'ei
1.8
1.6
1.4
Mean Rugosity
1.2
1
0.8
0.6
0.4
0.2
0
40
25
15
Transect Isobath (ft.)
Figure 4: (Mean ± Standard Deviation) Bar graph of ruugosity among depths at
Ke’ei.
Benthic Invertebrates
5
4.5
4
Number present
3.5
3
2.5
2
1.5
1
0.5
0
E. mathaei Hermit crab C. gigantea
S.
spectabilis
Echinothrix
spp.
S.
giganteus
T. gratilla
Phyllum
Porifera
Conus spp.
Species
Figure 5: (Mean ± Standard Error) Bar graph of mobile invertebrates abundace at
Ke’ei, 40’ left.
29
Point Intercept of Outer Reef Flat at Ke'ei
Sand
2%
Cyanobacteria
1%
Porites compressa
3%
Crustose coralline
1%
Porites evermanii
14%
Turf
50%
Porites lobata
28%
Pocillopora meandrina
1%
Montipora capitata
0%
Figure 6: Benthic percent cover using point intercept at Ke’ei, outer reef flat.
Photo Quad Ke'ei 40' Right
Quadrat
8%
Porites
compress
a
Crustose
coralline
13%
Porites
lobata
Turf algae
25%
Tolypiocladia
glomerata
21%
Figure 7: Benthic percent cover using photo quad at Ke’ei, 40’ right.
30
Photo Quad Ke'ei 25' Left
Quadrat
3%
Sand
20%
Porites
compress
a
Porites
lobata
Crustose
coralline
11%
Tolypiocladi
a glomerata
3%
Turf algae
28%
Figure 8: Benthic percent cover using photo quad at Ke’ei, 25’ left.
Average abundance per transect
Fish Strip Survey Transect
40
35
30
25
20
15
10
5
T.
du
pe
r re
P.
y
ar
c
Z.
a
fla tus
ve
sc
en
s
P. G. v
ar
im
iu
pe
rip s
en
ni
C.
s
ja
H.
c
ta
or
to
na
r
tis
sim
us
M
.n
ig
er
M
.v
id
ua
C.
P.
ov
jo
hn
al
is
st
on
ia
nu
C.
s
s
or
C.
d
am
id
bo us
in
en
sis
C.
ga
im
ar
d
0
Fish Species
Figure 9: Bar graph for the averge fish abundance of fish species per transect for the
inner reef flat.
31
Fish C-Plot of 40' Right at Ke'ei
80
Number Present
70
60
50
40
30
20
10
us
vi
ol
ac
eu
A.
s
ni
gr
O
ic
.u
an
ni
s
fa
sc
ia
tu
s
C
.a
rg
us
S.
r
ub
ro
to
ni
an
P.
jo
h
ns
im
us
us
vi
ss
fla
F.
C
.m
ul
ti
de
r
ci
nc
t
bi
lti
us
C
.v
an
tis
rn
a
C
.o
Z.
fla
ve
C
.a
sc
si
m
en
s
gi
lis
0
Species
Figure 10: Bar graph for average fish abundace using the cylindrical plot survey at
the right 40 foot isobath.
Number of Species per
Quadrat
Diversity vs. Depth via Species Richness
3
Coral
Diversity
2
(P = 0.10)
1
Algal
Diversity
(P = 0.16)
0
15
25
40
Depth (feet)
Figure 11: (Mean ± Standard Error) Coral and algal species richness among depths
at Ke’ei.
32
Diversity vs. Depth via Shannon-Weiner Index
Diversity Index
0.5
0.4
Coral
Diversity
0.3
(P = 0.19)
0.2
Algal
Diversity
0.1
(P = 0.18)
0
15
25
40
Depth (feet)
Figure 12: (Mean ± Standard Error) Coral and algal species diversity via ShannonWiener Index among depths at Ke’ei.
Percent Cover
Benthic Percent Cover Among Depths
Turf (P = 0.01)
P. Compressa (P = 0.03)
P. Lobata (P = 0.13)
50
45
40
35
30
25
20
15
10
5
0
15
25
40
Depth (feet)
Figure 13: Benthic percent cover among depths at Ke’ei.
33