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Kaitlyn Bretz
Dr. Bert Ely
BIO 303: Genetics
1 Nov 2013
Population genetics: the analysis of coral populations in various reef systems, and how genetics play a
role in designing regional conservation programs
Coral reefs are the ocean’s most diverse ecosystems; they harbor an enormous number of marine
species, and are one of the most fragile environments on the planet. As marine scientists struggle to find
ways to protect and conserve these valuable reefs from climate change and other anthropogenic impacts,
several critical questions need to be addressed: what coral species are crucial to the survival of reefs, and
how these species have spread across the ocean. These seemingly straight-forward questions have
multiplied in their complexities as scientists have come to realize that today’s identified species may not
be the true species delineation, that coral genetic migration is drastically affected by different modes of
reproduction and larvae viability, as well as the effects of physical barriers in and around reef systems. A
combination of multiple studies, centered on genetic determination of species and genetic flow and
diversity for various populations, allows for scientists to begin generating tentative responses to the
initially proposed questions. From those conclusions, scientists can create rudimentary guidelines to aid in
international conservation efforts.
The development of advanced technology has taken genetics and propelled it to the forefront of
scientific research; new procedures, faster and smarter computers, and better technology have allowed
scientists to collect and analyze more data than they had ever before. The analysis of organisms’ entire
genomes, for instance, is now possible, and has been instrumental in the determination of species
differentiation. Pinzón et al. (2013) designed a project to identify the coral species in the genus
Pocillopora, a hard coral found throughout the Indo-Pacific region. This coral is “common, ecologically
important, and widespread…but their phenotypic plasticity in response to environmental conditions and
their nearly featureless microskeletal structures confound taxonomic assignments and limit an
understanding of their ecology and evolution,” (Pinzón et al. 2013). Traditional morphological
classifications are based on skeletal and colony features, however due to disparity in taxonomy, scientists
have recognized anywhere from 17 species (Veron 2003) to 7 species (Cairns 1999) of this genus.
Pocillopora corals are one of the most susceptible reef-building corals to rapid climate change and it is
necessary to conserve its multiple species. Through the collection of samples and analysis of internal
transcribed spacer 2 (ITS2), mitochondria open reading frame loci (ORF) and seven microsatellite loci,
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Pinzón et al. (2013) were able to provide significant evidence that current special divisions are incorrect
and that scientists need to redouble their efforts into classifying the natural world prior to conserving
them.
Samples of Pocillopora were collected from reefs all over the Indo-Pacific region, although some
previously collected data from Pinzón and LaJeunesse (2011) were used. These collections were
identified by their morphospecies using photographs and when possible, were verified with local experts.
DNA was extracted from the skeleton and tissue samples and then the internal transcribed spacer 2 (ITS2)
and mitochondrial loci open reading frame (ORF) were amplified with their respective primers. The
resulting ITS2 and ORF data were sequenced, reviewed, edited and aligned by various programs. Two
separate phylogenies were created for ORF and ITS2 to show possible Pocillopora speciation. Seven
microsatellites for Pocillopora species were already described from prior research (Starger et al., 2008;
Pinzóne & LaJeunesse, 2011), so Pinzón et al. (2013) identified the loci, marked them and ran them
through PCR so they could analyze the data. Hardy-Weinberg equilibrium in each phylogenetic group
was also analyzed.
ORF sequencing resulted in the identification of 21 distinct haplotypes from the 906 samples
collected. Eight well-differentiated groups were distinguished, and the haplotypes that differed by more
than five or six base changes were assigned to types 1 to 8 (Figure 1). ITS2 analysis (Figure 2) was
largely concordant with the ORF data, however ORF types 4 and 7 were unresolved and ITS2 type 8
could not be amplified. ORF type 1 was divided into 2 groupings, type 1 and type 9 because of a
comparison with microsatellite data. The parallel between the ORF and ITS2 data indicated that each
type/group represented “genetically isolated groupings or discrete species”; these results were tested by
further analyzing the data from microsatellite markers. These markers held an entire data set of
genotypes, comprised of 806 samples, which were used to identify populations that covered isolated gene
pools. The seven loci “conservatively delimited at least five but no more than seven genetically cohesive
Indo-Pacific populations” (Pinzón et al. 2013). Hybridization was also taken into account and the results
obtained varied by geographic location: for example, samples collected in Hawaii showed five
reproductively isolated lineages and with further analysis Pinzón et al. (2013) found that there was a 9.7%
admixture among genotypes, a higher than normal hybridization, whereas samples collected in California
contained only one single genetic lineage, with no population subdivision or hybridization (Figure 3).
Overall, hybridization was inconsequential at many locations.
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Figure 1: Mitochondrial ORF
unrooted parsimony tree
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Figure 2: ITS2 ribosomal DNA rooted
parsimony tree and geographical
distributions observed for rare or less
common Pocillopora types.
With a more in-depth comparison of ORF, ITS2, and microsatellites, there were some difficulties
discovered, mainly in differing resolutions of the data: differences in sibling lineages, the possibility of
haplotypes 3h-j and 7 belonging to a single homologous species, and the disparity between types 2 and 6
as separate lineages or one type. Major groupings defined with a large resolution were usually agreeable,
yet the smaller divisions between populations and close-related sibling lineages were difficult to
differentiate and weren’t always accurate. This incongruence could be corrected by an increase in sample
size, finer statistical resolution, or further development and application of additional and variable
microsatellite loci.
Pocillipora has relatively low species diversity compared to other widespread genera. This could
be explained by the lack of hybridization and a temporal difference in spawning, which minimizes the
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chances of recombination between species. Also, “high connectivity that persists over time ultimately
minimizes the potential for allopatric speciation, and may further explain why species diversity…is low,”
(Pinzón et al., 2013). Thus, low hybridization has allowed several species to spread throughout the IndoPacific region; however interspecific recombination doesn’t occur frequently enough to break down
genetic differentiation that occurs between widespread types. On this note, low species diversity means a
small number of species present in the Pacific, and this does not correlate with the current number of
accepted morphospecies. This frequent “discordance between morphology and genetics over broad
geographic scales could lead to incorrect inferences about connectivity and hybridization,” (Pinzón et al.,
2013). Such inferences in the past have led to incorrect classification of endemic versus widespread
species, a key example being the disparity in species classification between Hawaii and California (Figure
3). Widespread species are more prevalent in Pocillopora than initially realized, as types 1, 3, 5 and 9
were all found to be homogenous over thousands of kilometers. Continental landmasses often restrict
major ocean currents, limit genetic connectivity, and maintain “zoogeographical breaks” between oceans,
and can also further separate species through ocean basins (i.e., the Arabian Peninsula and the Red Sea).
Geographical factors may explain why several species were highly divergent, such as types 2 and 6,
which were found only at Clipperton Atoll and O’ahu, Hawaii, respectively. The variances in geographic
spread among Pocillopora could be accounted for by the different species’ reproduction methods:
broadcast and brooding. Explained further in Underwood et al. (2009), Pinzón et al. (2013) determined
that types 1, 3, 7 and 9 were broadcast spawners, while the brooders were types 4 and 5. The reproductive
modes of types 2 and 6 were not available, but Pinzón et al. (2013) inferred from the coral’s phylogenetic
placement and small geographical distribution that they were brooders. While hard corals (Scleractinia)
are often broadcast spawners, Pocillopora corals use both broadcast and brooding modes of reproduction,
which may explain why Pocillopora corals are less diverse, have low levels of hybridization and are
found in certain geographical regions.
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Figure 3: A comparison of Pocillopora
morphospecies in Hawaii and
California, and the results of genetic
analysis from Pinzón et al. (2013)
Out of the initial estimation of 21 species of Pocillopora, Pinzón et al. (2013) determined there to
be anywhere between five and eight genetically distinct lineages in the Indo-Pacific region. Colony
morphology was not an accurate indicator for true species differentiation, which resulted in Pinzón et al.
(2013) determining that the general delineation of species diversity through genetics needs to take
precedence over the taxonomic division based on morphology. Genetic identification of organism
speciation will advance the general understanding of any species’ geographical distribution, ecology and
evolution; the conclusions reached by Pinzón et al. (2013) concurred with many other studies completed
prior to 2013, and all called for a larger reliance on genetic research for future ecological and
experimental work.
Corals have the ability to sexually reproduce in two ways: brooding or broadcast spawning.
Spawning corals release eggs and sperm which then fertilize one another and leave developing zygotes to
settle on a reef; broadcast corals become fertilized and then harbor the developing zygote until larvae is
released to settle on a reef and develop into coral. Genetic variation is heavily affected by the different
reproductive methods; scientists recognize that “long distance dispersal has…been associated with the
production by outcrossed sexual reproduction of genotypically diverse propagules, which maintain
genetic homogeneity of interconnected local populations…in contrast, restricted dispersal of propagules
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is…associated with inbreeding, loss of heterozygosity, and increased genetic subdivision due to drift and
site specific selection,” (Ayre et al., 2000). While this pattern is not guaranteed to match all marine
organisms, Underwood et al. (2009), with their research on two reproductively different corals in
northwest Australia, Acropora tenuis and Seriatopora hystrix, discovered that “levels of genetic
subdivision among populations were markedly higher in the brooder than in the broadcast
spawner…[which was] congruent with expectations based on life histories.” Beyond just reproductive
methods, Underwood et al. (2009) also used high-resolution genetic markers to investigate temporal
effects on reproduction, and their results have led to a conservation plan focused on the development of
coral reef protection areas based around “routine dispersal distances” for key coral species.
Underwood et al. (2009) collected samples from three locations in northwest Australia: Rowley
Shoals, Scott Reef systems, and Browse Island systems. In total, 576 colonies of broadcast-spawning
Acropora tenuis from the Rowley Shoals and Scott Reef systems, and 476 colonies of brooding coral
Seriatopora hystrix were collected. GPS coordinates of each sample were recorded for the development
of an x and y coordinate map. Corals which were likely to have been produced via asexual reproduction
were avoided, and Underwood et al. (2009) came up with 98% of samples having unique multi-locus
genotypes caused by sexual derivation. Final sample sizes averaged about 21 and 50 individuals being
analyzed at each site. DNA was extracted from the samples, then separate genotyping procedures were
used for each coral: eight microsatellite loci from Seriatopora hystrix and seven microsatellite loci from
Acropora tenuis were analyzed. Two multiplex PCR were conducted using fluorescently labeled primers
and then the products were analyzed. Genotyping errors were minimized by manually checking the PCR
results and any uncertainties in the data were re-amplified and compared once more. Several tests were
subsequently conducted, including Hardy-Weinberg equilibrium and FST approximations. HardyWeinberg estimates revealed that significant heterozygote deficits were detected at all sites for both
species, meaning that these deficits were “common features of these populations…[and likely
attributed]…to biological factors associated with spatial and/or temporal admixture and nonrandom
mating within sites,” (Underwood et al., 2009). FST values were calculated to quantify the geographic
genetic variation at different alleles, and represented three relationships between sites: system to system,
reef to reef and site to site. The genotype likelihood ratio distance (DLR) is the “mean genotype loglikelihood ratio across individuals from the two populations,” (Underwood et al., 2009), and was
calculated for pairs of sites for both species. A Principle Coordinate Analysis (PCA) allowed Underwood
et al. (2009) to create a coordinate graph from the DLR genetic distance matrix (Fig 4). A spatial
autocorrelation analysis was also conducted, which uses spatial positioning of the genetic identity of
individuals as data, rather than a summary of statistics that FST and DLR rely on. The resulting data is then
displayed as a ‘correlogram’; in effect, the data (Fig 5) can be interpreted by looking at two points: the x-
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intercept of the graph, the estimated distance where random effects of genetic drift are primary
determinates of genetic composition, and where r begins to decline after an initial plateau, which is the
limit of mixed genetic neighborhood and the distance past which the gene flow is limited. Finally, coral
samples were tested to predict the likelihood of an individual belonging to a particular population
(Bayesian analysis). This final test was where long-distance migrants were identified.
Figure 4: Genetic differentiation
between Rowley Shoals, Scott Reef
System and Browse Island System
(Underwood et al., 2013)
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Figure 5: Spatial autocorrelation
analyses of the genetic correlation
coefficient (r) as a function for
distance for A. tenuis and S. hystrix
gene flow/migration
On a broad scale, there was a “clear lack of panmixis across…the study, with significant
subdivision detected between systems, between reefs, and even within some reefs” (Underwood et al.,
2009). There were also major differences in subdivisions between S. hystrix and A. tenuis and differences
in genetic distance between the two species. FST values for the brooding coral (FST [excluding Browse
Island]=0.191) were far higher when compared with the broadcast spawner (FST [excluding Browse
Island]=0.034) indicating that the brooding coral has higher genetic diversity than the broadcast spawner;
this pattern remained when Underwood et al. (2009) adjusted for null alleles. The genetic distances
between the species (DLR) were similarly differentiated, as S. hystrix DLR(avg)=6.34 and A. tenuis
DLR(avg)=0.06. These patterns displayed in the Principle Coordinate Analysis (PCA) plots (Fig 4) show
the clear definition between systems: each reef is generally in a different quadrant of the graph and
similar sites are relatively crowded together. Each graph also represents one species and comparisons of
the site clusters show that S.hystrix (brooding) have more defined subdivisions between systems than A.
tenuis (broadcast) does, indicating higher diversity, and there is also larger genetic distances between
pairs of populations. On a more local scale, Underwood et al. (2009) discovered that S. hystrix has a
smaller ‘genetic neighborhood’, meaning that “larvae are routinely [recruited] over much smaller
distances in the brooder corals compared with the broadcast spawner.” Spatial autocorrelation analyses of
the genetic correlation coefficient (r) shows the distances the two species were most likely to be recruited
from certain systems: the r-values of S. hystrix cross the axis before A. tenuis at the Scott Reef system and
Rowley Shoals (Fig. 5), indicating the brooder had more local recruitment. The Bayesian analysis, where
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“no [S. hystrix] colonies were assigned to sites from different systems,” (Underwood et al., 2009),
provides further evidence for the local recruitment hypothesis.
On the basis of the their results, Underwood et al. (2009) summed up their conclusions with three
broad conclusions: differences in the reproductive mode of coral species influence levels of genetic
subdivision; many coral reefs are genetically differentiated; and panmixia is only generally observed over
scales of tens of kilometers or less. Brooder corals generally had higher genetic subdivision than
broadcast corals, and most brooder corals settled relatively close to their parent colony. S. hytrix, the
representative brooder coral, had larvae that settled “within 100 meters of their parent colony, while most
A. tenuis larvae…dispersed within reefs over distances of kilometers to a few tens of kilometers,”
(Underwood et al., 2009). Observations of life histories for the coral larvae reflect and reaffirm these
results. Studies conducted in laboratory conditions show that S. hystrix larvae “are competent to settle
within six hours of release,” (Isomura and Nishihira, 2001), while the broadcast coral A. tenuis “are
competent after 3-4 days,” (Nishikawa et al., 2003); these temporal differences in biological behavior
provide further evidence for the pattern of more local dispersal for brooding corals when compared to
dispersal of broadcast corals. However, there were some instances of rare longer-distance dispersal from
both species. Several samples that had very little differentiation between sites demonstrate that once
larvae drift beyond local influences they are able to disperse between reefs. These anomalies in the
general pattern of the data allow for populations to stay relatively homogenized and to keep the species
from completely differentiating, potentially saving environments from collapse by allowing other
populations in separate reefs to restore dying populations. Overall, coral larvae had much more local
recruitment than originally hypothesized and the relationship between close reefs remains an important
subject of study.
Studies on cross-ocean dispersal and genetic connectivity that also support the importance of reef
self-recruitment of coral larvae are all developed from studies of sexually-reproduced propagules.
However, “asexual reproduction is commonly regarded as important for local proliferation, whereas
sexually derived propagules are thought to be important for larger-scale dispersal,” (Whitaker, 2006).
Asexual recruitment can occur in two ways: clonal production of larvae or colony fragmentation.
Understanding the importance of asexual reproduction and local recruitment is imperative for colony
conservation, especially if scientists have been overestimating the importance of sexual reproduction in
gene flow. The purpose of the Whitaker (2006) study was to examine genetic mixing of the hard coral
Pocillopora damicornus between and within reefs, to quantify the level of asexual versus sexual
reproduction, and to validate the importance of independent recruitment for genetic diversity.
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Pocillopora damicornus samples were taken from 10 sites at two separate locations: the Ningaloo
Reef (8 sites) and Houtman Abrolhos Islands (2 sites). 644 Growing tips from phenotypically-consistent
P. damicornus were collected, frozen, and then had allozymes extracted and subsequently run through
electrophoresis, where ‘six consistently scorable polymorphic loci were found after preliminary screening
of 30 enzymes encoding 37 loci on 6 buffer systems,” (Whitaker, 2006). Hardy-Weinberg deviations were
calculated at individual loci, and then two methods were used to estimate the extent of asexual
reproduction: one test to estimate the maximum proportion of the sample that could be produced by
sexual reproduction (N*:Ni), and another to observe multi-locus genotype diversity by comparing
expected conditions assuming panmixis to the observed condition (GO:GE). For allelic variation, FST tests
were conducted on two different sample groups: one with all individuals irrespective of the reproductive
origin and the other with only individuals from sexual reproduction.
The results of the Hardy-Weinberg estimations varied greatly from site to site. Out of the 10 sites
tested, only two sites (3 and 8) matched Hardy-Weinberg expectations, and the other 8 sites varied even
further by different amounts of heterozygous excess and deficits. Pairwise comparisons showed strong
genetic subdivision at nearly all of the sites, despite having some evidence of sexual reproduction; the
maximum proportion for sexual representation (N*:Ni) varied from 4% (site 10 ) to 100% (site 2) (Fig. 6).
The ratio test (GO:GE) illustrating the relative importance of sexual versus asexual production revealed
significant variation between sites as well: only sites 3 (0.770) and 8 (0.725) showed levels of genetic
diversity which are similar to those under conditions with sexual reproduction (Fig. 6). Allelic variation
from site to site didn’t vary however, as “samples from the Houtman Abrolhos Islands shared just as
many genotypes with Ningaloo as did samples within Ningaloo,” (Whitaker, 2006).
Figure 6: results from the ratio tests
concerned with identifying the
importance of sexual reproduction
and multi-locus genotypic diversity
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Reproduction methods of Pocillopora damicornis at the tested locations, Ningaloo Reef and
Houtman Abrolhos Islands, showed that populations have dual modes of reproduction (asexual and
sexual), “but that there is considerable variation in the relative contribution of each to those populations
sampled,” (Whitaker, 2006). Of the 644 individuals sampled, only 96 (15%) were from ‘apparent sexual
origin’; but note that this number may be biased due to inadequate quantification of asexual propagule
dispersal, or to the limited number of loci sampled. The disparity between reproductive modes from siteto-site can be seen in a comparison of sites 1 and 4 with sites 3 and 8. Sites 1 and 4 were highly impacted
by asexual reproduction, while there was little to no evidence of asexual recruitment from the latter sites.
Asexual reproduction had been formally reported in populations around the Pacific, and evidence
suggests that the majority of asexual recruitment is from brooded ameiotic planulae and coral fragments
following storm activity. Scientists have not been able to determine if certain conditions favor one mode
of reproduction over the other since no consistent pattern has been discerned, as the variation in
importance of sexual and asexual reproduction fluctuates from population to population and differs from
study to study. The high diversity of Pocillopora damicornis creates a complex population structure,
especially since “most sites share less than half their genotypes” (Whitaker, 2006). The combined results
of genetic diversity between sites and the low percentage of sexual reproduction provide evidence that
“asexual reproduction contributes substantially to local abundance, making an otherwise relatively rare
organism common,” (Whitaker, 2006); however, the results vary depending on the study, so “the
inference of restricted gene flow and asexual reproduction and inbreeding among some sexually
reproducing colonies should be treated as a working hypothesis,” (Whitaker, 2006). The precise
reproductive modes of coral populations need to be identified by more ‘sophisticated markers’ than
allozymes. Until this time, the conclusions from this study and all other studies are still tentative.
While biological factors greatly influence the genetic diversity and gene flow of coral species,
scientists cannot forget the physical side of the equation. The structures of the reefs, systems, and islands
themselves have an impact on genetic flow, not to mention the additional influence of ocean and air
currents and local weather; these factors greatly influence coral genetic diversity, especially “following
gamete release or in the early stages of larval life when behavioral capabilities are poorly developed,”
(Underwood et al., 2012). The effects of ocean and air currents and local weather have not been
sufficiently quantified to produce reliable results explaining their effects on the genetic dispersal of
marine species. The location and shape of various geological structures, however, are generally static and
relatively easy for scientists to compare and conjecture how they affect coral populations. Underwood et
al. (2009) demonstrated the genetic difference between Scott Reef and Rowley Shoals through special
autocorrelation analysis and hypothesize that the shape of Scott Reef and the effects this surface has on
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other oceanic factors has a clear role in altering how coral populations can disperse between sites and
broad versus local recruitment.
Using the data previously discussed, Underwood et al. (2009) concluded that there were
differences in gene flow and larvae recruitment between Rowley Shoals and Scott Reefs in both A. tenuis
and S. hystrix. A close examination of the special autocorrelation analysis revealed that the two reef
systems had varying dispersal distances and different x-intercepts. The corals at Scott reef had a much
smaller x-intercept than the corals from Rowley Shoals: S. hystrix is 10 times greater at Rowley Shoals
than Scott Shoals, and A. tenuis is nearly two times greater (note the logarithmic distance scale for Fig. 5).
Rowley Shoals recruits larvae from a much larger distance than Scott Reef, meaning that gene flow is less
restricted at Rowley Shoals.
The difference between Rowley Shoals and Scott reefs can be found in the different levels of
gene flow: Rowley shoals had limitations at the reef-to-reef scale, but Scott Reef had limitations within
the reefs, from site-to-site. Scott reef is south of Rowley Shoals and is larger and of a semicircular
structure (Fig. 7). The unique shape of this reef “is likely to modify water circulation patterns by
increasing friction and therefore reducing circulation on the northern side of the reef and creating
recirculating flows and eddies,” (Underwood et al., 2009). This modification of water circulation could
result in a higher retention rate of larvae to their parent reefs, which could cause significant genetic
differences between sites in the same reef. Note that the data for the hypothesis is resolved from this one
study and that the authors acknowledge that further studies on local circulation patterns and temporal
genetic data are required to test and verify the hypothesis. The conclusion that the shape of the island and
the location of reefs relative among other systems is critical in developing Marine Protection Areas
(MPA), a conservation effort to maintain diverse fisheries and protect important marine species. By
knowing the relationship between the shape and location of different reefs, better designed MPAs may be
established and help further the conservation effort.
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Fig. 7: the location of the 3
systems from Underwood et al.
(2009). Scott Reef is in the
upper left quadrant
The purpose of coral population studies is not to only genetically analyze coral speciation and
gene flow, but to gather data about these important organisms to improve conservation efforts and to
design more effective plans to protect and rehabilitate reefs. Today’s conservation efforts have shifted
with the times, as illustrated by Pinzón et al. (2013), with their results comparing morphological and
genetic species classification. Improved conservation efforts fueled by studies like Underwood et al.
(2012) and Whitaker (2006), which focus on genetic dispersal and local recruitment, have also caused a
modification in MPAs. Through a combination of the aforementioned studies and other similar
publications, scientists have come to identify a general pattern in coral and other marine organisms’ gene
flow through their respective species differentiation and larvae dispersal. Preserving the most threatened
species and those vital to gene flow and genetic diversity is a vital step to rehabilitating and protecting
marine environments; however, scientists need to continue studying marine organism classification, to
verify and align morphological and genetic identities prior to advocating conservation efforts for certain
organisms. Comparisons of larvae recruitment between reef systems has also helped scientists identify
how nature maintains genetic diversity and by identifying key systems, scientists may help advance the
recovery of reefs that rely on local recruitment. Knowing the importance of local recruitment via sexual
and asexual reproduction is critical as Whitaker (2006) proved in her study when she found a significant
number of corals maintain genetic diversity through asexual reproduction. The geographical effects of
reef systems and oceanographic factors are also subjects that need to be further investigated, as
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Underwood et al. (2009) mentioned in their study whilst comparing genetic diversity between Rowley
Shoals and Scott Reefs. The combination of these results points to the implementation of Marine
Protected Areas (MPAs) as being one of the most promising conservation techniques. The summative
case study, Underwood et al. (2012), affirms that “Marine Protected Area planners must seek to protect
the reproductive capacity of populations within each system…[and] that networks designed for the
smaller scale dispersers should provide adequate protection for the larger scale dispersers.” While MPAs
and no-take zones may protect certain locations, these are in no way applicable to all environments
around the world. The research that was conducted to gather data which helped designed MPAs is very
particular (i.e., Pinzón et al. (2013), Underwood et al. (2009), and Whitaker (2006) all involve regions in
and around the coast of NW Australia); the findings in one location can vary rarely be transferred to
another location. Underwood et al. (2012) recognized this, and purported that “depending on the taxa
studied in the first location, basic information from one study, such as mean dispersal distances, may be
used to model another region, however, this model will still need to be ground truthed and this requires
the methods such as hydrodynamic modeling and genetic analysis described above.” In conclusion, the
results of studies on population genetics are promising when applied to conservation efforts, however
these results cannot be used on a global scale and take a lot of time and effort to conduct, assimilate with
other studies, and then to be applied to the environment as conservation programs.
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Works Cited
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