Astrid Leitner
Total score: 83/100
Title [[4/4 – nice and descriptive]]
Evaluation of Both Physical and Biological Habitat Associations for the Benthic
Invertebrate Community in a Temperate Kelp Forest Ecosystem
Clarity [[12/14 – work on varying sentence length and omitting any extraneous
words to give your writing more oomph.
Introduction [[15/20 – I especially like your ecological context and examples. You
have the main elements, but it’s not flowing together terribly well and you didn’t
address the novelty of this study]]
Understanding how diversity is maintained within an ecosystem has long
been a goal of ecologists. This is a complex and debated topic; however, ecologists
have identified niche partitioning as an important process for maintaining high
diversity. Niche partitioning maintains diversity by reducing competition among
species; instead of competing for the same resource the species use different parts
of the same resource or niche, thus functionally dividing the resource between them
(Schoener 1974) [[nice description]]. This allows for coexistence of previously
competing species by reducing the size of their realized niches relative to their
fundamental niches. One key way to study resource partitioning is through habitat
association studies. By understanding each organism’s individual habitat, one can
begin to piece together how different niches are partitioned throughout the
coexisting community, and therefore how diversity is maintained [[nice]].
Species-habitat association studies have a long history in both terrestrial and
marine ecosystems. For example, Robert Macarthur conducted a classic study
highlighting how multiple species of warbler can persist by utilizing different
sections of the same tree (Macarthur 1958). Resource partitioning has also been
cited as a major cause of the present diversity of rockfishes within the Pacific coast
kelp forest ecosystem (Hallacher and Roberts 1985). Species-species associations
have also been previously documented; for example, in tropical reefs, associations
between fish assemblages and corals as well as macroalgae are well documented
(Syms 1995). However, in temperate waters there has been considerably less work
done on species associations. Moreover, there are no studies that I am aware of that
have attempted to link species to species as well as species to physical habitat
structure and then attempted to evaluate the relative importance and strengths of
these associations, especially not in temperate reefs. In this respect, this is a novel
study. [[good examples with citations]]
A good approach to studying both types of associations (species-species and
species-habitat) is to look at highly diverse communities such as tropical rain
forests, coral reef systems, and kelp forests. In such systems resource partitioning
maintains high levels of diversity, and so they are ideal for association studies. The
kelp forest is also an ideal study area for this work because sampling done via
SCUBA is fairly simple due to kelp’s shallow, near shore distribution. [[this is good,
but you might want to reference Hopkins and its characteristics specifically right
after the general description]]
Moreover, the kelp forest is an ecosystem that provides many important
services to our society including provisioning services, regulating services, cultural
services, and supporting services. For example, the kelp forest provides us with
many products including kelp itself, whose canopy is often harvested, as well as food
from the fisheries it supports. The kelp forest also attracts and supports many
tourist activities that are important to local economies. [[this paragraph seems like a
bit of a tangent]]
In order to effectively manage and protect this ecosystem and all the services
the kelp forest system provides to humans, more information is needed about the
intricacies of this complex system. This study aims to better understand the
community by elucidating species-habitat and species-species associations by
addressing several questions [[this is a bit awkward with the two “by”s]]: firstly, do
species-habitat associations exist in the kelp forest; secondly, do these associations
differ in relative strength for different species; thirdly, do species-species
associations exist in the kelp forest, and do these associations differ in relative
strength; finally, which association is more important in determining community
composition, the physical or the biological?
We hypothesized that both species-habitat and species-species associations
do exist in the kelp forest and that both these associations will vary in relative
strengths. We also hypothesized that physical habitat associations will be more
important in determining community composition because physical conditions are
more often what determine a species fundamental niche where as the biological
associations often shape the realized niche. [[good job introducing the questions and
hypotheses]]
Methods [[16/18 – you’ve got all the essential bits, but I might reorder … notes
below]]
In order to address these questions we conducted an observational field
study at the Hopkins Marine Station in Pacific Grove, California (36°37'12.3"N
121°54'11.2"W) (Map Figure 1).
The Study System
Our research was conducted within the Hopkins State Marine Reserve, which
was previously known as the Hopkins Marine Life Refuge (Jones 1985). Since 1985
the taking of fish, plants, and marine invertebrates has been prohibited, making this
an ideal place to study natural occurring habitat associations (Jones 1985).
Moreover, this area has a high diversity of benthic species, making it an ideal place
for species-species association work. Macrocystis pyrifera, or giant kelp, dominates
the kelp forest, and granite is the dominant rock type in this region (Watanabe
1984). The study area also has a variety of substrate types, including bedrock,
boulder, cobble, and sand, as well as complex and varying habitat structure in the
area ranging from shallow to nearly vertical relief. Therefore, the area is also ideal
for habitat association studies. [[good]]
Methodology Overview
To answer our primary questions we used a combination of two different
sampling methods: swath sampling and uniform point contact methodology (UPC).
Both were conducted via SCUBA at the same transects off the Hopkins main transect
cable. We used UPC to sample sessile benthic species and their physical habitat,
substrate and relief. UPC primarily samples those species for which individuals are
not identifiable (either because they occur in aggregations or because of their
growth form) or those that are not countable due to their small size and sheer
number. UPC gives a percent cover for those species, as well as for substrate type
and relief. The swath surveying was done for countable species over a 30 m by 2 m
area. This method gives a density for the species counted (individuals per area). The
resulting data sets were then linked [[at what scale?]]so that we could determine if
the physical and biological habitat characteristics (from the UPC) were associated
with the distribution of countable species. [good level of detail]]
Swath Methodology [[I would move these full descriptions down until after you’ve
explained WHY you did things this way (i.e. introduced the questions and specific
methodology for each]]
We collected data from 20 transects running on and offshore off the
permanent transect cable at Hopkins marine station, sampling from the 90 meter
mark to the 135 meter mark. All swaths were 30 m in length and 2 m wide with each
diver within two man buddy teams sampling 1 m on either side of the transect tape.
Each 30 m transect was split into six 5 meter long sections; therefore, the data could
be easily combined with the UPC data. No organisms under 2.5 cm in diameter were
counted so that easily undercounted, small species did not bias the data. Highly
abundant individuals were subsampled. If over 15 individuals were encountered
within one 5 m section, the meter mark at which the 15th individual was
encountered was noted and the remaining individuals of that species within that
section were not counted. 37 species were counted in these surveys including 9
seastars, 3 anemones, 2 species of urchin, 3 species of sea cucumber, 7 species of
crustacean, 8 species of molluscs, 2 algae, 1 sponge, 1 solitary tunicate, 1 hydrocoral
(see table 1). Note that Macrocystis were only counted if the stipes were greater
than 1 m in height, and Cystoseira were only counted if they had a minimum
diameter of 6 cm.
UPC Methodology
In UPC data is collected at uniformly spaced points along a meter tape. At
each of these points the species of the primary substrate holder directly under the
meter tape is identified and recorded. This makes it possible to survey invertebrates
that act as primary substrate holders, which are often impossible to count as
individuals (see table 2).
To collect the UPC data, divers in two man teams conducted two dives at
each 5 m increment, the first heading offshore (90° heading) and the second one
heading inshore (270° heading). Each transect had a length of 30 m, which was
further subdivided into 5 m increments. These 5 m increments were sampled at
every half-meter with the first diver sampling the first half (points 0, .5, 1, 1.5, and 2
m) and the second diver sampling the second half of each increment (points
2.5,3,3.5,4,4.5, and 5 m). At each point divers identified the substrate as being either
bedrock (rock greater than or equal to 1m in extent), boulder (between 10 cm and 1
m), cobble (less than 10 cm), or sand. Additionally, divers classified the relief at each
point by noting the maximum elevation change occurring within a 1 m by .5 m
rectangle (.5 m to either side of the transect line and .25 m ahead and behind the
point). A four point relief scale was used to classify relief: F-flat for relief between 0
and 10 cm, S-shallow from 10 cm to 1 m, M-moderate from 1 to 2 m, and H-high for
relief greater than 2 m. The presence of a superlayer of drift algae and juvenile
Laminariales was noted as well. Finally the species that occurred directly under each
point were identified and recorded (or the type of inanimate substrate if there was
no biotic organism present). This methodology was repeated for all 5 m increments
along each transect.
Other
Tuni
Cnidarians
cates
Snail
s
Tube
Worms
Brown Algae
Coral
line
Red Algae
Inanimate
Table 2: UPC species list with codes used.
Cover
Bare rock
Bare sand
Shell Debris
Sediment/mud
Dead Kelp Holdfast (any)
BRANCH-flat branching
LEAF- blade, unbranched
BUSHY-cylindrical branches
LACY-filamentous/dense
ENCRUSTING RED
TURF - red turf - < 2 cm
Crustose coralline algae
Articulated coralline algae
Cystoseira osmundacea
Dictyoneurum californicum
Egregia menziesii
Desmarestia spp.
Macrocystis holdfast (Live)
Laminariales Holdfast (Live)
Dictyotales (Dictyota Dictyopteris)
Tubeworm - Other Solitary
Diopatra ornata / Chaetopterus
Phragmatopoma
Dodecaceria spp.
Serpulorbis squamigerus
Petaloconchus montereyensis
Corynactis californica
Cup Corals
Other anemone
Hydroids
Stylaster calif. (Calif Hydrocoral)
Colonial tunicate
Solitary tunicate
Scallop
Embedded Cucumber
Barnacle
Bryozoan
Sponge
Mussel
Linking Swath Data to UPC Data
Code
BARROC
BARSAN
SHELL
SED/MUD
DEADHOLD
BRANCH
LEAFY
BUSHY
LACY
ENCRED
TURF
CRUCOR
ARTCOR
CYSOSM
DICCAL
EGRMEN
DESSPP
MACHOLD
LAMHOLD
DICTYOTALES
TUBEWORM
DIOCHA
PHRCAL
DODFEW
SERSQU
PETMON
CORCAL
CUP
ANEM
HYDROID
STYCAL
COLTUN
SOLTUN
SCALLOP
CUCSPP
BARN
BRYO
SPONGE
MUSSEL
In order to examine possible associations between the countable swath
species and the UPC data, all transects were split into six 5 m long sections. For each
section there was one set of species counts from the swath and 10 UPC points
spaced half a meter apart (see Figure 2). For each section the following percentages
were calculated: 1) percent of the substrate that is bedrock, boulder, cobble, or sand
2) percent of area that has flat, shallow, moderate, or high relief 3) percent of the
section area made up by each UPC species sampled. These percentages were then
linked to the swath species counts for each section. [[nice, but explain that they’re
linked at a 10 sq m spatial scale]]
Habitat Associations
In order to determine if physical habitat characteristics, in this case substrate
type and relief, determined community composition (for countable species) a
dissimilarity matrix was calculated using Euclidean values for the different sections
for each transect. This matrix was then linked to another dissimilarity matrix
calculated using Bray-Curtis values for the swath species using a Spearman
correlation. This was done to determine if swath species dissimilarity was related to
habitat dissimilarity. From the results, the swath species dissimilarity could be
plotted against the habitat dissimilarity to bring out any relationship between them.
An analysis of variance table was then constructed between all swath species and
substrate type and relief. A 95% confidence interval was used to evaluate the
significance of the resulting relationship.
Habitat Association Strengths
To test the hypothesis that differences exist in the strengths and signs
(positive or negative) we performed a series of correlations between swath species
and their substrates and relief types. All correlations greater than 0.1 and less than
-0.1 were significant using a 95% confidence interval and were therefore considered
strong associations. Correlations less than .1 and greater than -.1 were considered
weak associations and not used in the analyses.
Four pairs of species were selected to be examined in detail: Macrocystis
pyrifera and Cystoseira osmundacea, Balanus nubilus and Styela montereyensis,
Cryptochiton stelleri and Lithopoma gibberosa, and Patiria miniata and Pisaster
giganteus. These species were selected because they were abundant and showed
interesting and related habitat associations.
Species-Species Associations
In order to test the hypothesis that biological habitat characteristics, in this
case UPC species, influenced the community composition for countable species, a
Bray-Curtis dissimilarity matrix was calculated for UPC species and compared to the
swath species dissimilarity matrix again using the Spearman rank correlation. Again
the results were used to plot the swath species dissimilarity against the UPC species
dissimilarity. A slope of 0 would show that there is no relationship between the two.
An analysis of variance table was constructed to determine whether the associations
were significant or not. 95% confidence intervals were used to determine
significance.
Species-Species Association Strengths
To test the hypothesis that species-species associations varied in relative
strength and sign, another series of correlations were done this time between UPC
species and swath species. 95% confidence intervals determined that all
correlations greater than 0.1 and less than -0.1 were significant. Only significant
correlations were included in the results.
Relative Importance of Physical versus Biological Associations
In order to determine whether physical or biological attributes had a larger
impact on community composition a variance component analysis was run on the
data. This analysis provided us with the relative contribution of each attribute to the
resulting community composition. [[I envisioned this going further up, before the
detailed methods and including the field sampling methods that enabled you to do
these analyses]]
Results [[12/16 – you’ve got a lot more details than you need here, and it’s
drowning out the important points you’re making. Good job being specific about
whether the results support or reject the hypotheses. Also, I’d prefer if you put the
figures all in one section rather than interspersing in the text as it makes it difficult
to follow]]
The kelp forest community at the Hopkins Marine Station was highly diverse
in both physical habitats and biological species. Based on this observational field
study, we determined that specific physical habitat associations are most important
in determining community composition. Nevertheless, species-species associations
do also exist with a wide variety of strengths, and they are still important to the
community’s structure, especially for understanding resource partitioning that
maintains the diversity of communities such as this kelp forest.
Habitat Associations
The null hypothesis for habitat associations was rejected (P-value
<.0.000001) (see table 3). Habitat associations were found to exist in the
community, and the physical attributes of substrate and relief did influence
community composition (see figure 3).
Habitat Association Strengths
For the eight species that were examined in more detail, habitat associations
varied in strength and sign with some species showing positive correlations to some
substrates and negative correlations to others (see figure 4).
Figure 4: For eight selected species the correlations to each substrate type (bedrock: rock greater
than or equal to 1m in extent, boulder: between 10 cm and 1 m, cobble: less than 10 cm, or sand) and
to each relief type (flat for relief between 0 and 10 cm, shallow from 10 cm to 1 m, moderate from 1
to 2 m, and high for relief greater than 2 m). Correlations greater than 0.0 are positive, meaning the
species is found on that physical habitat more than would be expected by chance; correlations less
than 0.0 are negative, meaning the species is found on that physical habitat less frequently than
would be expected by chance. The dashed lines represent significant positive and negative
correlation values (with 95% confidence intervals).
Both algal species examined here, Cystoseira osmundacea and Macrocystis
pyrifera, showed significantly positive correlations with bedrock and lower relief;
both showed significantly negative correlations with small clast size substrates.
Cystoseira showed negative associations with sand and moderate relief and had
positive associations with shallow relief and bedrock. Macrocystis showed positive
correlations to bedrock and shallow relief as well and was negatively correlated
with cobble and flat relief.
Another pair of species that showed strong habitat associations to specific
substrates and relief types was Balanus nubilus and Styela montereyensis. Balanus
showed strong positive correlations with boulder substrates and moderate and high
relief; we also found negative associations with sand and shallow relief. Styela, on
the other hand, showed a strong positive association with bedrock and shallow
relief. Styela had negative associations with sand and flat relief similar to Balanus.
The gumboot chiton (Crypotchiton stelleri) showed positive associations with
moderate relief and cobble and boulder substrates with negative associations to
sand and flat to shallow relief. The other mollusc that was examined in more detail
was Lithopoma gibberosa, the wavy turban snail. Lithopoma was found to have a
strong positive association with high relief habitats and a strong negative
association with moderate relief. The snail showed no significant positive
associations to any particular substrate but was found to have significant negative
associations with sand and boulder substrates.
Finally the last species pair that was examined was a pair of seastars, the
giant spined seastar (Pisaster giganteus) and the bat star (Patiria miniata). Patiria
showed a barely significant positive association with sand substrate and a barely
significant negative association with moderate relief. No significant correlations
were found for any other relief or substrate types. Giant-spined seastars were found
to have a positive association with boulder habitats, no preference for any specific
relief type, and negative associations to sand and bedrock. [[you don’t really need all
these details, a bit of a laundry list]]
Species-Species Associations
The null hypothesis was also rejected for species-species associations as
there were many species for which significant species correlations were found.
Therefore, biological habitat attributes do contribute to community composition
(see figure 5).
Swath Species Dissimilarity
Biological Habitat Association
y = 0.3481x + 27.886
R² = 0.07439
80
70
60
50
40
30
20
10
0
0
20
40
60
UPC species Dissimilarity
80
Figure 5: This is a graphical representation of the biological habitat associations. Swath species
dissimilarity is plotted against UPC species dissimilarity as calculated from Bray-Curtis dissimilarity
matrices. This shows that a relationship between swath species and UPC species does exist.
The two algal species Cystoseira osmundacea and Macrocystis pyrifera
showed interesting and varying species associations as well as the above mentioned
physical associations. Most extreme was the strong positive correlation (over .55)
with solitary tunicates, which were mostly Styela montereyensis. Macrocystis also
showed significant positive associations with colonial tunicates, Cystoseira,
encrusting red algae, and Dictyoneurum californicum. Macrocystis was found to have
negative correlation values with dead Macrocystis holdfasts and lacy red algae.
Cystoseira was not surprisingly also strongly correlated with Macrocystis as well as
with branching red algae, crustose coralline algae, other Cystoseira, Dictyoneurum
californicum, and other Laminariales. Interestingly Cystoseira also showed negative
correlations with sponges, Phragmatopoma or sand castle worms, and dead
holdfasts (see figure 6).
Figure 6: This figure shows the two algal species included in this study Cystoseira osmundacea and
Macrocystis pyrifera and their correlations to UPC species (for UPC species codes see Table 2). The
dashed lines mark significant correlations (using a 95% confidence interval). Positive correlations show
co-occurrence more than expected by chance, negative correlations show co-occurrence less than
expected by chance.
Balanus nubilus showed a very strong positive correlation to hydroids (over
.3) as well as cup corals, branching red algae, turf, and strangely also to bare sand
and Diopatra ornata/ Chaetopterus, which are also sand associated. We found a
negative correlation to shell debris and solitary tunicates (Styela m.). Styela
montereyensis, however, showed a positive association to barnacles as well as to
articulated and crustose coralline algae, branching and bushy red algae, and sponges
(see figure 7).
Figure 7: This figure shows associations between Balanus nubilus and UPC species (upper half) and
Styela montereyensis and UPC species (lower half). The dashed lines mark significant correlations
(using a 95% confidence interval). Positive correlations show co-occurrence more than expected by
chance, negative correlations show co-occurrence less than expected by chance.
The gumboot chiton was most strongly positively associated with sponges
and Dictyoneurum californicum, as well as with multiple kinds of algae both browns
and reds and crustose coralline algae. Lithopoma also showed strong associations
with various types of algae including various browns and reds, but Lithopoma also
showed a strong association to bryozoans. The snail showed negative associations
to anemones, dead holdfasts, and Diopatra as well as leafy red algae. The chiton
showed significant negative associations with specific kinds of red algae such as lacy
and encrusting red algae as well as with solitary and colonial tunicates and shells
(see figure 8).
Figure 8: This figure shows the different strengths of species-species association for the gumboot
chiton (Cryptochiton stelleri) and the wavy turban snail (Lithopoma gibberosa). The dashed lines
mark significant correlations (using a 95% confidence interval). Positive correlations show cooccurrence more than expected by chance, negative correlations show co-occurrence less than
expected by chance.
The bat star was found to be positively associated with barnacles, branching
red algae, bryozoans, sponges, and Laminariales. It was found to be strongly
negatively associated with the strawberry anemone (Corynactis californicus) (more
than -.3). The giant spine seastar was found to be positively associated with turf and
Dictyoneurum californicum and interestingly also with barnacles. Like the bat star,
the giant spine seastar was also negatively associated with the strawberry anemone.
Additionally, it was negatively associated with colonial tunicates, lacy red algae, and
tubeworms (see figure 9).
Figure 9: This figure shows the different strengths of species-species association for the bat star
(Patiria miniata) and the giant spine seastar (Pisaster giganteus). The dashed lines mark significant
correlations (using a 95% confidence interval). Positive correlations show co-occurrence more than
expected by chance, negative correlations show co-occurrence less than expected by chance.
Relative Importance of Physical versus Biological Associations
Overall, physical associations were found to be about three times more
important in determining community composition than biological associations.
Physical attributes were calculated to explain 76% of the variance of swath species
abundances using variant component analysis. Nevertheless, biological habitat
attributes did still have an impact and were calculated to explain the remaining 24%
of the variance seen in the swath species abundances. [[why did you bury this so
deeply? it’s one of the coolest bits!]]
Discussion [[18/22 – lots of good information here, but you could pare it down to
make it more powerful. Good job getting the direct answer to each specific question
in the very beginning of each section. You could also improve your use of the
scientific literature to put your study in the context of past work.]]
The results suggest that species diversity in the kelp forest may indeed be
maintained by resource partitioning. They also indicate that species composition is
determined by a combination of physical and biological factors. Moreover, the
physical attributes of substrate and relief were found to be more influential than the
biological attributes. [[nice links back to the big ecological questions from the intro]]
Habitat Associations
As predicted habitat associations did exist and did vary for different species
in the study in both sign and strength. Moreover, these associations mostly make
sense in light of life history information for the species in question. Other
associations seem to bring up new and interesting questions that could be the basis
for future research.
The associations found for the two algal species make sense given our
observations that the two were frequently found together; Cystoseira was frequently
observed growing around the holdfasts of Macrocystis. These physical associations
also make sense given each species’ physiology. Macrocystis anchors itself by
attaching its haptera to rock; therefore, it requires hard, stable substrates to grow
and recruit (Deysher et al. 2003, Edwards 2003). If this attachment rock is unstable
or movable by wave action as are smaller substrates like boulders or cobble, the
growing algae would not be able to survive. Therefore the strong correlation found
with stable bedrock substrates is as expected from the life history of Macrocystis. By
this reasoning, however, one would also have expected a strong negative association
with cobble. A very slight and insignificant negative association to cobble was seen,
but the insignificance of this result may be due to the very limited amount of cobble
substrate that was sampled. [[good interpretation]]
The association for Balanus also makes sense in the light of life history
information for the species. We found a strong association to bedrock, which is to be
expected knowing that barnacles require hard substrate for attachment and
metamorphosis (Buschbaum 2001). Styela also require hard substrate for
attachment; it anchors itself to substrate with an irregular tunic holdfast, and its
long stalk holds it siphons into the prevailing currents so the animal can filter feed
(Young and Braithwaite 1980). It needs a stable substrate to anchor to because it is
frequently found in shallow areas where surge causes the organism to oscillate
frequently (Young and Braithwaite 1980). Therefore the association with bedrock
seems logical.
Not much research has been conducted on the subtidal distribution of the
gumboot chiton, and so the results found in this study are quite interesting. The
gumboot chiton is a generalist herbivore that feeds mostly on macroalgae by
scraping it off hard surfaces with its radula; therefore its positive association with
boulder and cobble seems reasonable. However, it is interesting that no association
was found with bedrock. From personal observations, gumboot chitons are not
common exposed either on low relief habitats or on vertical walls. Instead, they are
usually seen tucked in crags with moderate relief. This preference for moderate
relief and more complex substrates may be due to predation pressures in exposed
habitats. The other mollusk in this study, Lithopoma, showed only negative
associations to substrates. I would have predicted a positive association with
bedrock from cursory observations, and there was an insignificant positive
correlation with bedrock, which may have been insignificant due to the low
abundances of the snail. The association with high relief is consistent with
observations of the snail on steep and vertical faces although why the snail would
prefer high relief is not clear.
The lack of very strong habitat associations for the bat star is not surprising
as it is the most common species in the kelp forest at Hopkins and therefore is
widely distributed across almost all habitat types. Bat stars are frequently observed
feeding on detritus over sand, which would agree with the slight positive association
with sandy substrate. The other seastar, Pisaster giganteus, is a predator, and
specifically preys on mussels, barnacles, and other molluscs (Gotshall 2005). It is
interesting to note that its positive association to boulder substrates may correlate
to the habitat preference of its prey items, notably the positive association of
Balanus nubilus to boulder substrate as well. [[you don’t need SO MANY examples,
but they’re all well explained and it seems like you might have had fun thinking
about them]]
Species-Species Associations
Our hypotheses that species-species associations do exist in addition to
physical associations and that these biological associations also vary in strength
were supported by our data. Some of these associations seemed to arise logically
from the habitat associations while others provided insight into possible speciesspecies interactions such as predator avoidance, competition, and predation. These
interactions are also important in determining community composition and
maintaining diversity in the ecosystem. [[nice big picture]]
The observed association between Cystoseira and Macrocystis makes sense
given the similar habitat preferences highlighted in the previous section as well as
personal observations of the two species frequently co-occurring. This interaction
would be interesting to study further, especially at Hopkins because it is one of the
few places in the Californian kelp forests where Pteryogophora californica is not the
dominant understory kelp. Perhaps the dynamics between Cystoseira and
Macrocystis are similar to the dynamics between Macrocystis and Pteryogophora,
where Pteryogophora can initially outcompete giant kelp eventually the kelp
outgrows the Pteryogophora and forms a canopy that can limit further recruitment
(Reed and Foster 1984). Cystoseira was also positively correlated with crustose
coralline algae, which has also been experimentally shown to increase recruitment
relative to bare rock (Reed and Foster 1984). The negative association between
Cystoseira and Phragmatopoma also makes sense due to Cystoseira’s negative
correlation with sand due to its requirement for hard substrate for attachment.
The negative association between Balanus and solitary tunicates may be due
to competition because both are primary substrate holders that filter feed and
require hard surfaces to settle (Bauschbaum 2001). Therefore the positive
association between Styela and barnacles is most likely due to barnacle species
other than Balanus. The association between Balanus and Diopatra and sand is
unexpected because Balanus was found to be negatively associated with sand in the
habitat association section. However, this bare sand could be an artifact of the UPC
methodology in which sand that has settled in a crack on rock is still counted as
sand. The association with Diopatra is even more curious because I have never
observed barnacles alongside ornate tubeworms. The association between Styela
and crustose aglae is also interesting, and it begs the question whether crustose
algae are a preferred substrate for the recruitment of Styela.
The two herbivorous molluscs in this study were logically found to be
positively associated to many different algae, as one would expect because a species
would actively remain near its prey items. It is interesting, however, that Lithopoma
has a significant negative correlation to leafy red algae perhaps demonstrating that
the snail has a selective diet and prefers certain types of algae to others. The
negative association of Lithopoma to anemones may be a predator avoidance
response, where the snail is actively avoiding the anemone.
The association found between Pisaster giganteus and barnacles may be due
to the predatory behavior of the seastar where it actively seeks out its prey and so
was found significantly more often with barnacles. It was interesting that both
seastars had negative associations to the strawberry anemones. This could be
further investigated by laboratory experiments to test whether the stars are actively
avoiding those anemones, and if so why this would be the case.
Relative Importance of Physical versus Biological Associations
As predicted the physical attributes had a greater impact on the community
composition than the biological habitat attributes. This may be due to the fact that
physical attributes shape the fundamental niches of organisms, and the biology and
growth form of the species themselves will often restrict species to specific reliefs
and substrates. Nevertheless, biological attributes were also found to explain some
of the swath species abundances, and these gave us a window into interesting
interactions that may influence the behavior of different species and consequently
the community composition.
Conclusion
In summary, the diversity of the kelp forest is maintained by resource
partitioning which is expressed through different specific habitat associations and
preferences for various coexisting species. The factors that influence community
composition are a combination of physical and biological characteristics that
together create the community we observe. Neither the physical habitat nor the
species interactions can be taken alone if one is to understand how the community
truly functions. [[directions for future research? Management implications?]]
References [[6/6]]
Buschbaum, C. 2001. Selective settlement of the barnacle Semibalanus balanoides
(L.) facilitates its growth and reproduction on mussel beds in the Wadden
Sea. Helgoland marine research. 55.2:128-134.
Deysher, L.E., T.A. Dean, R.S. Grove, A. Jahn. Design considerations for an artificial
reef to grow giant kelp (Macrocystis pyrifera) in Southern California. ICES
Journal of Marine Science. 59(suppl): S201-S207.
Edwards, M.S. 2004. Estimating scale-dependency in disturbance impacts: El Niños
and giant kelp forests in the northeast Pacific. Oecologia.138: 436–447.
Gotshall, D.W. 2005. Guide to Marine Invertebrates Alaska to Baja California. Page
100. Shoreline Press, Santa Barbara, CA USA, 117 pages.
Jones, B. 1985. The Hopkins Marine Life Refuge: Information and Background.
<http://www.stanford.edu/group/dbr/HMLRhistory.htm>
Lord, J.P. 2010. Modeling of life history strategies in organisms with indeterminate
growth, with a focus on the distribution and life history of the gumboot
chiton Cryptochiton stelleri. (Masters Thesis). Oregon State University.
MacArthur, R.H. 1985. Population Ecology of Some Warblers of Northeastern
Coniferous Forests. Ecology. 39.4: 599-619.
Reed, D.C., Foster, M.S. 1984. The Effects of Canopy Shadings on Algal Recruitment
and Growth in a Giant Kelp Forest. Ecology. 65.3: 937-948.
Schoener, T.W. 1974. Resource partitioning in ecological communities. Science. 185:
27–39.
Syms, C. 1995. Multi-scale analysis of habitat association in a guild of blennioid
fishes. Marine Ecology Progress Series. 125: 31-43.
Watanabe, J. 1984. The Influence of Recruitment, Competition, and Benthic
Predation on Spatial Distributions of Three Species of Kelp Forest Gastropods
(Trochidae: Tegula). Ecology. 65.3: 920-936.
Young, C.M. , L.F. Braithwaite. 1980. Orientation and Current-Induced Flow in the
Stalked Ascidian Styela montereyensis. Biological Bulletin. 159.2 : 428-440.