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NOVA SOUTHEASTERN UNIVERSITY OCEANOGRAPHIC CENTER
A predictive habitat model for the reef fish,
rainbow parrotfish Scarus guacamaia
Ethan G.P. Machemer
Submitted to the Faculty ofNova Southeastern University Oceanographic Center
in partial fulfillment of the requirements for the degree of Master of Science with a specialty in
Marine Biology
Nova Southeastern University
Date: TBD
1. Introduction
A. Life History of the Rainbow Parrotfish
Rainbow parrotfish Scarus guacamaia is the largest herbivorous fish in the
Atlantic Ocean and Caribbean Sea and is found in both mangrove and coral reef habitats
(Mumby 2006). The rainbow parrotfish is large, heavy-bodied, and a somewhat laterally
compressed fish. It has a fusiform body shape with dull orange fins possessing streaks of
green extending into the dorsal and anal fins; median fin margins are blue in color with
the dental plates appearing a blue-green. In this species there appears to be no obvious
color differentiation based on sex (Cervigón 1994). Rainbow parrotfish are behaviorally
cautious in nature, though it sometimes may be found in schools of up to thirty
individuals (Dunlop and Pawlik 1998).
It has a limited daily home range (Smith 1997), and occupies varying depths up to
twenty-five meters. It possesses a dependence on corals for shelter and living space
(Cole et al. 2008) and seeks shelter under ledges at night or when threatened, and the
species has been shown to use the angle of the sun as an aid in returning to these shelters
(Smith 1997). Rainbow parrotfish are herbivorous fish that, like most members of the
Scaridae family, feeds mainly by scraping macro-algae from coral structure (Bellwood et
al. 2004). However, it has also been observed to feed directly on coral (Rotjan and Lewis
2006) and gut content analyses have revealed spicules from feeding on sponges (Dunlop
and Pawlik 1998).
Rainbow parrotfish life history characteristics are reasonably well known. It is a
protogynous hermaphrodite, meaning individuals in this species undergo a sex change
2
between their initial phase, where they are generally female and terminal phase, where
they are male. Terminal phase male rainbow parrotfish defend a territory and a harem of
females, and when the male dies, the most dominant female will become the dominant
male, with her ovaries becoming functional male testes (Streelman et al. 2002). Like
other species in this family, peak spawning occurs primarily in warmer summer seasons
from May to August, but can occur year-round, and there is an active period of fish
recruitment occurring around February in this region (Haus et al. 2000). Spawning is
found to take place generally around dusk, and may correlate to either the lunar cycle or
the high tide, as this is an optimal time for egg dispersal. The initial phase is composed
of females while the terminal phase is composed of sexually mature males. Rainbow
parrotfish aggregate into territories that contain a group of females with the dominant
male pair-spawns almost exclusively (Munoz and Motta 2000).
Rainbow The rainbow parrotfish is a relatively larger reef fish, compared to most
species of reef fishes in the Caribbean, which and can achieve a maximum length of 120
cm (TL). The estimated with a K value (l/y) of 0.293 equatesing to a minimum
population doubling time of approximately four and a half to fourteen years (Robins and
Ray 1986; Randall 1962). Observations of rainbow parrotfish have been made in waters
with temperatures ranging from 12-36 °C, salinities ranging from 23.74 to 39.1 ‰ (parts
per thousand), and dissolved oxygen concentrations ranging from 2.4 to 14.07 ‰ (Serafy
et al. 2003). The species’ wide range of tolerances to these factors is most likely an
adaptation to the wide range of its known habitats. These habitats range from estuaries to
offshore areas, both of which are subject to large pulses of freshwater and storm events.
The varied thermal and oxic conditions cannot be exploited by less tolerant species and
3
may be beneficial in providing refuge from predators, foraging grounds or potential
nursery areas (Rummer et al. 2009).
The diet of rainbow parrotfish has been shown to be variable across life stages
and habitats. In the Dunlop and Pawlik (1998) study, sponge spicules were found in
higher masses in the individuals collected from the mangrove sites as compared to those
from coral reefs, suggesting there are shifts in diet preference based on the food sources
available. A secondary food source is coral as rainbow parrotfish has been classified as a
facultative corallivore based on direct observations, meaning coral can be either a
majority of their diet or only a minor component. These fish impose more permanent and
chronic pressures on scleractinian corals, those that generate a hard skeleton such as
Montastrea and Porites species, meaning there is repeat scraping activity on these corals,
and the damage caused is longer lasting. However, chronic predation may play a factor
in regulating distribution, abundance and fitness of certain prey corals (Cole et al. 2008).
Though not fully known, this corallivory may be part of an ontogenetic diet shift,
meaning coral is only an important food source for part of their lives, accounting for less
than five percent of their bites. Along with this diet selectivity comes the ability to cause
significant damage to corals by biting off growing tips or large portions of skeletal
material, which means they are capable of having a disproportionately large impact on
the physical structure of Caribbean reefs (Cole et al. 2008). It has also been observed that
grazing reduced the density of zooxanthellae and increased the severity of a bleaching
event in Belize (Cole et al. 2008). Rainbow parrotfish use a feeding method of scraping
or grinding algae from the coral or other rocky substrate, and sometimes inadvertently
ingests coral animals as well. The hard coral substrate is broken down through its
4
digestive system, and the excretion of this limestone material is one of the main sources
in the creation of the sand surrounding coral reefs in the Caribbean.
Parrotfishes are known to become progressively important upon reaching a certain
key size around 15-20 cm, at which point they become ‘functionally mature’ (Lokrantz et
al. 2008) and their actions provide a significant impact on the coral reef. This impact
increases exponentially as there is a non-linear relationship between body size and
scraping function, as calculations suggest that up to 75 individuals with a size of 15 cm
are required to functionally compensate for the loss of a single 35 cm individual, and a
50% decrease in body size can result in a 90% loss of function (Lokrantz et al. 2008). In
addition, grazing impact in mangrove systems is also a power function of body length. A
conservative estimate places the home range of S. guacamaia at 1600 m3, which is larger
than that of many other scarids. Rainbow parrotfish also represents approximately 14%
of the total grazing intensity measured for mangrove depauperate systems (Mumby
2008).
The main part of the rainbow parrotfish diet consists mostly of short epilithic turf
algae, cropped algae, red coralline and filamentous algae (Mumby 2008), and they feed
heavily upon Halimeda opuntia, a green calcareous alga. Juvenile scarid abundance has
also been shown to be positively related to the percent cover of Dictyota spp. algae at site
level in the Florida Keys (Kuffner et al. 2009). Similar parrotfish species have been
observed consuming whole pieces of the thallus rather than grazing on the attached
epiphytes, and taking more bites from H. opuntia and fewer bites from coral than would
be expected from the percent cover of different microhabitats (Munoz and Motta 2000).
While not quantitatively known for rainbow parrotfish, a mean home range for similar
5
parrotfish species in the Florida Keys was observed to be 4371.5 +/- 5869.5 m2 (Munoz
and Motta 2000), with a high standard error due to a low number (n = 7) of study sites.
Due to microhabitat and foraging overlap of various parrotfish species there are
occurrences of interspecific aggression when one species attempts to use the defended
resources to the detriment of the defending species. This aggression involves vigorous
chasing over comparatively large distances, as well as biting, and the benefits gained
from this resource defense outweighed the cost. Aggression has also been observed to be
greater when encountering other parrotfish species as opposed to non-parrotfish species
and rainbow parrotfish were instigated into these aggressive encounters most often by the
focal species Scarus aurofrenatum (Munoz and Motta 2000).
Scarus guacamaia is most closely related phylogenetically to S. coelestinus and S.
iseri, with Scarus clades having root nodes at between 2 and 3 million years ago, thus
implying that most Scarus species are recent products of recent speciation. This
speciation occurred around the likely date of the complete closure of the Isthmus of
Panama at approximately 3.1-3.5 million years ago. The pantropical distribution and the
relatively recent ages of the divergence of the four main clades of Scarus imply that
fluctuations in sea level and patterns of differential cooling of the oceans during the
Pliocene and Pleistocene may be the driving forces behind the rapid radiation in this
genus, that which is today largely restricted to the complex reefs built by hard corals.
Alternatively, processes of ecological speciation and divergence due to sexual selection
remain a possible explanation for the rapid radiation of parrotfishes, which all have
pelagic larval phases and highly similar morphology. In addition tThe protogynous
mating system of parrotfishes, where species aggregate and have male-dominated
6
haremic systems organized by color recognition, has also been proposed as a possible
driving force for speciation via sexual selection mechanisms (Smith et al. 2008). The
phylogeny of parrotfish also suggests a gradual shift from browsers living in seagrasses
to excavators inhabiting rock and/or coral reefs to scrapers found exclusively in
association with coral, with Sparisoma being the transitional genus (Streelman et al.
2002). It can be assumed that the Scarus genus has always had a habitat association with
coral reefs as the Scarus genus is the third radiation off of the Sparisoma lineage.
Of the parrotfishes, S. guacamaia is the only species that possesses an obligate
and functional dependence on the mangrove habitats (Nagelkerken 2007; Mumby 2006).
This dependency has been shown quantitatively in the Mumby et al. (2004) study in
which the species suffered local extinctions that corresponded with the removal of
mangrove stands, and the extent of mangrove coverage in a region is one of the dominant
factors in structuring reef communities. Mangrove connectivity enhances the biomass of
rainbow parrotfish on neighboring coral reefs, because grazing influences the cover of
macroalgae on reefs and high levels of parrotfish grazing has been shown to lead to a
twofold increase in recruitment of Porites and Agaricia corals in the Bahamas (Mumby
2008). Biomass of rainbow parrotfish more than doubled when the reefs were connected
to rich mangrove resources, defined as having at least 70 km of fringing Rhizophora
mangle within a region of 200 km2, equating to coverage of 35% (Mumby 2006).
Juveniles of this species, those less than 30 cm total length (TL), are observed almost
exclusively in mangrove habitats, while all individuals observed on the coral reef were
greater than 25 cm total lengthTL were observed on the coral reef (Dorenbosch 2006). ,
and aAverage sizes have been recorded of 10.1 cm and 14.6 cm total lengthTL have been
7
recorded in mangroves and seagrass beds, respectively (Nagelkerken et al. 2000). The
species of juvenile reef fishes that utilize mangroves and seagrass beds do so because of
the high food availability, the presence of shade and shelter that the mangroves provide,
and a reduced risk of predation due to the plant and root configurations and lessened
chance of interaction with predator species as well as low predator abundance and
efficiency (Verweij et al. 2006). Shallow water habitats such as mangroves and
seagrasses, are believed to contain less piscivores than the reef (Verweij et al. 2006)
possibly because the energetic costs of chasing the smaller fish in these habitats outweigh
the gains of catching one of the prey fish. The turbidity of the water can also negatively
affect predator efficiency due to scattering and reduction of light by suspended particles
(Verweij et al. 2006). There is significant interannual variability in species composition
that may be expected in mangrove fish communities, but spatial factors have been found
to contribute more to differences in fish community structure than seasonality (Robertson
and Duke 1990).
Verweij et al. (2006) tested the effects of plant structure, shade, and food upon
rainbow parrotfish foraging behavior using artificial seagrass leaves and artificial
mangrove roots. Rainbow parrotfish showed the same trends as those of pooled
herbivores, being highly significant (p<0.001) for the tested variables ofin structure, food,
structure times *food, and blocked location. In this study, 72 individuals were observed
ranging in size from 7.5-15.0 cm. The behavior observed was broken down into 2.8% of
individuals resting (spaced evenly throughout the water column), 91.7% foraging, and
5.6% swimming. Eighty-four percent of the rainbow parrotfish observed foraging in the
study were found in the artificial mangrove roots, with six percent foraging on artificial
8
seagrass leaves and it was determined that the presence of higher surface area on the root
structure provided more substrate for algae which allowed for diurnal feeding on the
fouling algae and epiphytes in mangroves and seagrass beds. Rainbow parrotfish
observed in this study were also found to be preferential to experimental units with the
highest structural complexity. Caribbean mangroves and seagrass beds function as
foraging habitats, but are not used continuously as shelter during the daytime (Verweij et
al. 2006). The value of these habitats is diminished with decreased water clarity from
turbidity originating from terrestrial run-off (Freeman et al. 2008), leading to population
declines in this and other species. Seagrass minimum light requirements differ between
species and systems. Halodule and Syringodium seagrass pecies often require more than
24-37% surface light intensity, yet they are consistently an order of magnitude higher
than terrestrial plants or other photosynthetic marine organisms. Reduced subsurface
light intensity has caused seagrass declines and the subsequent re-suspension of
unstabilized sediments has impeded recovery of these seagrass systems, increasing the
pressure placed on species such as the rainbow parrotfish that depend on them (Freeman
et al. 2008).
However, presence of preferential habitat is not the only contributing factor
determining abundance. It is possible that habitat configuration has an influence on the
connectivity between mangroves, seagrasses, and coral reefs and this configuration in
terms of providing pathways and connections to the reef affects the composition of the
fish assemblage, species richness, fish density and fish size (Dorenbosch et al. 2007).
Local recruitment can play a major role. In one study, juvenile densities on the reef were
comparable to those in seagrass beds, suggesting that this species can also use the coral
9
reef as a nursery (Dorenbosch et al. 2004). Dorenbosch et al. (2007) concluded that for
rainbow parrotfish, migration among these habitats most likely takes place along the
coastline. The presence of seagrass-mangrove bays along the coasts of these islands
strongly influences the distribution pattern of this species on the coral reef, and reduced
density of several of these nursery species on the coral reef is related to the absence of
seagrass beds and mangroves (Dorenbosch et al. 2004). For island sites, this migration
was observed to occur on the sheltered or leeward shores, where most adult individuals
were observed on coral reefs between 0 and 10 km from mangroves. However, no
significant linear relationship was present between mean total density of rainbow
parrotfish on these reefs and the distance to the nearest stands of mangroves (Dorenbosch
et al. 2006). There was also reduced density or complete absence of rainbow parrotfish
on the coral reefs that were farther than nine kilometers from the mangrove and seagrass
habitats used by fish of juvenile ages.
The density of these species is additionally regulated on local scales by variable
habitat structural complexity and the community of vegetation. Herbivory was highest at
the maximum habitat complexity site, which suggests that the increased shelter and food
abundance provided by denser seagrass beds may have increased fish abundance
resulting in these higher levels of herbivory (Unsworth et al. 2007). Herbivory was found
to increase away from patchy seagrass areas whilst increasing distance from a reef
reduced the rate of herbivory due to a reduction in fish migration. Observed high levels
of herbivory, however, may only be a short-term effect of irregular grazing by shoals of
juvenile and sub-adult scarids (Unsworth et al. 2007).
10
Rainbow parrotfish migrate across habitats in accordance with its life history
stage, and will grow as large as possible before moving on to the next habitat. Utilization
of intermediate nursery habitats has been hypothesized to increase survivorship of small
fish (Mumby 2004). The intermediate nursery stages between mangroves, seagrass beds,
and patch reefs serve the function of alleviating predatory bottlenecks in early demersal
ontogeny (Mumby 2004). The presence of seagrass beds has also been linked to
significantly higher densities of rainbow parrotfish on coral reefs (Dorenbosch et al.
2006) while other studies (Gonzalez-Salas et al. 2008) have found differing results with
respect to these nursery habitats. Noting high abundance of juveniles and adult members
of S. guacamaia in coral reef habitats and a total absence in mangrove stands, it appears
that mangroves in certain regions do not function as obligate habitats and that seagrass
and coral rubble become the primary alternative for nursery, growth, and reproduction
(Gonzalez-Salas et al. 2008). It is possible that with removal of mangrove forests the
rainbow parrotfish are adapting to utilize other habitats that offer similar survival
benefits. The reduced benefits of these marginal habitats may not provide rainbow
parrotfish with the resources necessary to survive across their entire life history, allowing
only temporary survival through one life stage or another (Rummer et al. 2009). This
selective use, which is defined as use of a particular habitat patch disproportionately
relative to its availability, can be exhibited either seasonally or spatially, and proximity
rather than suitability has been found as the dominant pattern of habitat use (Faunce and
Serafy 2008). Mangrove shorelines across broad spatial scales are not equivalent in their
value as fish habitats due to the inherent patchiness within the ecosystem. A measure of
total habitat area will may therefore overestimate the amount of functional habitat utilized
11
by these fishes. In addition, species richness and total number of fishes collected
adjacent to mangrove shorelines has been shown to decline with increasing inland
distance from creek mouths and oceanic inlets, with water depth greatly related to fish
use (Faunce and Serafy 2008).
Rainbow parrotfish are valuable members of the communities with which they are
associated. The grazing activities of these parrotfish are beneficial in preventing algal
overgrowth and enhance coral reef resilience to algal blooms and other competitor
species (Hughes et al. 2007). The species also facilitates settlement and survival of corals
by scraping and bioeroding the hard dead coral substratum and are crucial for the
regeneration and maintenance of coral reefs (Lokrantz et al. 2008). Rainbow parrotfish
and other scarid species not only take up carbon into the food chain through direct
seagrass consumption, but also make an important indirect contribution to the detrital
food chain through the export of decaying seagrass material, which potentially results in
the widespread dispersal of seagrass material into surface waters. Detached seagrass may
also be cast onto the shore where it decays and may re-enter the system as detritus
(Unsworth et al. 2007). Rainbow parrotfish may be equally important in influencing
seagrass export from the system by the high rates of material discarded during
consumption. This material is subsequently removed from the system by weather and
currents, estimated to be as high as 11% of seagrass growth, on top of which herbivory
causes the loss of at least 16% of the seagrass growth each day (Unsworth et al. 2007).
In spite of their ecological role and importance, S. guacamaia populations are
thought to be in decline and to have been fished to ecological extinction in Brazil, as well
as similar to many other areas of the Caribbean (Floeter 2006). Rainbow parrotfish has
12
been listed as vulnerable on the IUCN Red List. This designation means the species is
facing a high risk of extinction in the wild based on one or more of the following five
criteria: reduction of population size, shrinking geographic range or occupancy, a
population with fewer than 10,000 mature individuals, restricted population extent, or
quantitative analysis showing the probability of extinction in the wild is at least 10%
within 100 years; the full explanation of which are detailed in the 2004 IUCN criteria (,
version 2.3, (Roberts 1996). Given this information and the role the species occupies
within this multi-part ecosystem, developing a model that details occurrence and
abundance characteristics provides a new means in which to assess the health and
function of this parrotfish in this region. In addition, one may apply the methods not only
throughout the range of this species, but it may be possible to apply this model to other
parrotfish species and similar families.
B. Characteristics of the Biscayne Bay and Florida Reef Tract Region
Biscayne Bay is a downstream receptor of larvae and juveniles from offshore
spawning adults and as a source point for adults to migrate to the reef tract (Wang et al.
2003) and the region contains some of the most pristine habitat within the Florida Keys
(Ishman 1997). The coastal shelf of the Florida Keys is characterized by shallow and
highly variable topography, where currents are influenced by tides, wind, and the very
energetic offshore Florida current system (Haus et al. 2000). The eddies and meanders of
the Florida Current make it possible for upwelling and larval transport to occur across the
shelf, and the scale of these perturbations can vary from slow moving mesoscale gyres to
faster moving, sub-mesoscale eddies (Haus et al. 2000). Velocities of these eddies can
13
range from 0.53 m/s to 0.80 m/s along the inshore edge of the Florida Current (Haus et al.
2000) and the variability of those velocities can have an impact on dispersal and the
resulting end locations of larvae.
Patch reefs in this region occupy a significant portion of the water column,
leading to variability in the water depth and have the potential to change the strength and
direction of the tidal flow. The northern Florida Keys contain over 4,000 patch reefs,
composed generally of cemented reef (47.3 +/- 2.2% cover) and pavement (20.1 +/-
2.1%), with varying amounts of rubble, boulders and sand (Kuffner et al. 2009). The
benthic community observed on these patch reefs is largely dominated by macrophytes,
encrusting invertebrates, and “suitable settlement substratum” found beneath a substantial
canopy of gorgonian s, or (“soft”) corals (Kuffner et al. 2009). Macroalgae occupies a
large portion of space on the reefs, especially Dictyota spp. (15.4 +/- 0.8% cover) and
Halimeda tuna (11.7 +/- 0.6% cover). Live scleractinian corals account for only 5.8+/-
0.6% of the benthos (Kuffner et al. 2009).
The tides are generally weak, with a semidiurnal height range of approximately
0.5 m, while although flows through tidal channels however, are strong enough to cause a
nodal point in the along-shelf tidal flow (Haus et al. 2000). As measured in Caesar
Creek, tidal velocity can exceed 25 cm/s, while current measurements within the inlets
have shown peak tidal velocities in excess of 0.5 m/s (Haus et al. 2000). These channels,
commonly referred to as the “ABC Channels” because of their names --– Angelfish
Creek, Broad Creek, and Caesar Creek --– form the main outlet from the southern end of
Biscayne Bay onto the Florida reef tract. The ABC Channels convey large oscillating
tidal flows and wind driven flows between the bay and the ocean, and transport through
14
these corridors predominantly shows a semi-diurnal cycle with amplitudes of 500 m3/s,
300 m3/s, and 250 m3/s respectively (Wang et al. 2003). Based on observations, there is a
net outflow at Angelfish and Caesar Creek, but an inconsistent inflow in Broad Creek
(Wang et al. 2003). With the tidal flows and the input of freshwater, the residence times
of the water varies widely from several months in the more enclosed Barnes Sound, and
circulation restricted Card Sound (Ishman 1997) to about a month in the western parts of
South Biscayne Bay, and nearly zero in the vicinity of the ocean inlets (Wang et al.
2003).
The area encompassing Biscayne Bay south to Card Sound and Barnes Sound
forms a barrier island lagoon system that exhibits estuarine characteristics near points of
freshwater inflow during the wet and early dry season (Wang et al. 2003). This lagoon
system leads to broad salinity regimes that vary throughout the year, and greatly across a
relatively small area of only several kilometers due to high freshwater input through
canals as opposed to groundwater, and limited tidal flushing. Salinity variations in
Biscayne Bay primarily result from canal discharges through gated control structures, as
well as smaller freshwater exchanges in the Bay driven by overland runoff, rainfall, and
evaporation (Wang et al. 2003) and upwelling from groundwater (Ishman 1997). The
greatest salinity fluctuations occur near canal mouths in Barnes Sound and along the
western margin of Biscayne Bay, and smallest ranges were observed near ocean inlets
(Wang et al. 2003), where the vertical variations of salinity in the water column ranged
from less than 0.2 ‰ to a maximum salinity change of 0.8 ‰ from top to bottom in the
vicinity of the inlet mouth (Haus et al. 2000). In the Pelican Bank region of Biscayne
Bay (see Figure 20) good circulation results in regular flushing and average salinities
15
range from 33 to 35 ‰ (Ishman 1997). Also determining water flow characteristics in
this region are a network of drainage canals completed for agricultural and industrial
purposes, as well as to control flooding, which has greatly altered the distribution of
freshwater within the watershed, as well as the quantity, quality, and timing of freshwater
discharges to Biscayne Bay (Wang et al. 2003). This has lead to greater pulses with
larger peak discharges in the wet season and less freshwater reaching Biscayne Bay in the
dry season, due to reduced terrestrial storage and lowered groundwater levels (Wang et
al. 2003). Increased runoff not only affects salinity conditions in coastal waters, but also
can be a mechanism for increased nutrient loading (Rudnick et al. 2006). There also
exists a coastal ridge, bisecting the Bay, which acts as a groundwater divide, with water
west of the ridge flowing toward Florida Bay. The outputs of freshwater from the canals
have punctured massive holes through the ridge, changing the direction and
characteristics of the flow, and the qualities of the watershed (Wang et al. 2003).
This region also is characterized by large coverage of submerged aquatic
vegetation such as seagrasses, and wide availability of phytoplankton, microalgal and
macroalgal species. Florida Bay is approximately 2000 km2 in total surface area,, with
95% bottom coverage of seagrasses, characterized by sparse, patchy beds of Thalassia
testudinum interspersed with locally abundant Halodule wrightii (Fourqurean and
Robblee 1999). However, in the spring of 1991, Florida Bay exhibited a shift from a
system characterized by clear water to one of extensive and persistent turbidity and
phytoplankton blooms, which limit the ability of the seagrass to grow and function
properly, by reducing penetration of light in the water column (Fourqurean and Robblee
1999). This seagrass die-off was not accompanied or preceded by noticeable decreases in
16
water clarity or increases in colonization by epiphytes, however. and hHypothesized
causes for this die-off include hypoxia and sulfide toxicity, along with loss of the
estuarine nature of the system over many decades; overdevelopment of the seagrass beds;
chronic hypersalinity; in-filling of the bay due to lack of severe storms; and abnormally
warm late summer and fall temperatures (Fourqurean and Robblee 1999).
The problem this presents for rainbow parrotfish and other species of fishes is that
fish abundance and diversity is highly correlated with seagrass abundance and species
composition in Florida Bay (Fourqurean and Robblee 1999). D, and die-off events of
these seagrasses often result in causes a lack of suitable habitats, changes in trophic
position for various species, an altering of food webs, and a lessening of species biomass
due to variations in water level and salinity.
Algal blooms also present problems for S. guacamaia in the south Florida
ecosystems. Algal blooms are most commonly composed of cyanobacteria (formerly
blue-green algae) such as those of the genus Synechocystis and Synechococcus, the most
recent of which was likely initiated by an increase in total phosphorus (Rudnick et al.
2006). Southern Biscayne Bay typically has low phytoplankton biomass and low
productivity, in large part because of low phosphorus availability, these; concentrations
of total phosphorous normally ranging range from 0.006 mg/L to very rare high values of
0.02 mg/L; , yet during the 2005 bloom event, total phosphorous reached levels of 0.1
mg/L (Rudnick et al. 2006). Chlorophyll-a Cconcentrations of chlorophyll-a, which are
an indicator of phytoplankton biomass, typically have a value of 0.4 microgramsmg/ L
liter and rarely exceed 2 microgramsmg/ Lliter, but when the blooms occurred, values
reached 8 mg/ L micrograms/liter for chlorophyll-a (Rudnick et al. 2006). Factors
17
causing this bloom event are thought to be linked to road construction along U.S. Route 1
between the Florida mainland and Key Largo, and the hurricane impacts in the 2005
season, which were exacerbated by water management operations, diverting water
through canals as opposed to groundwater, and other anthropogenic means, such as
development that also disrupts natural groundwater flow. Similar to the seagrass die-offs,
algal blooms this affects the rainbow parrotfish, in that the by algal blooms reduceing the
available suitable habitat, alters altering the physical parameters of the ecosystem outside
of the utilizable range, and by reduces reducing the available corridors for movement
among nearshore and offshore ecosystems across the various life history stages of the
species.
C. Previous Studies and Statement of Problem
Prior work has detailed the importance of the rainbow parrotfish to the coral reef
communities of the Caribbean, Sea. hoHowever, these studies, many of which are cited
above, generally only examined rainbow parrotfish as part of a group of species with
similar functional traits, as opposed to a detailed study with a focus solely on this species.
Other studies have taken place either on sites in the Windward Islands, or in the
Bahamas, and while these reefs may be physically structured similarly, they are not
exactly the same as the coral reefs of the Florida Reef Tract. Two studies, the Mangrove
Visual Census and Reef Visual Census have taken place in this region, and this work
expands on the conclusions from their data.
D. Statement of Significance
18
This research has taken point count data of the rainbow parrotfish from Biscayne Bay and
Upper Florida Bay and developed a model predicting the occurrence of this species in
other similar areas and regions where such data collection has not taken place. The
Biscayne Bay and Upper Florida Bayse locations provide good examples of shoreline
mangrove forests, islands and barrier reefs, and how they are affected by anthropogenic
means in a highly developed region. As is the case with many species of reef fishes,
there is an ontogenetic shift in habitat utilization with S. guacamaia, and this ontogenetic
difference in habitat use may result from predation rate, or juveniles selecting lower
predation risk habitats such as seagrass beds (Nakamura and Tsuchiya 2008).
Thise relationship between developmental stage and habitat utilization has been
examined and quantified in greater detail. Regression and occupancy models based on
biological, physical, and anthropogenic factors were constructed to provide a numerical
representation of abundance and occurrence of the rainbow parrotfish in relation to the
life history of this species. This research gives graphical evidence to support and expand
the known habitat and life history information for this fish, information that can be
applied to similar species found in similar habitats to allow for more detailed
management and conservation decisions for this and other unstudied species of reef fish
in the future.
While there is significant information about the habitat preferences of the rainbow
parrotfish, there is not readily accessible information that substantiates the importance of
a specific location to the species, or how dependent this fish is on the oceanographic
characteristics, such as (e.g., bottom substrate), of a given site. The development of a
model for these habitat characteristics has provided numerical evidence for the
19
probability of occurrence of this fish in a particular habitat and a ranked importance of
the habitat type. Rainbow parrotfish has a functional importance and dependence within
these mangrove and reef habitats of Biscayne Bay and Upper Florida Bay, suggesting that
it makes a better study subject than a species with less of an impact. In addition to
providing a more detailed picture of habitat utilization by rainbow parrotfish across its
life stages, this model allows one to make more accurate management decisions,
particularly as they relate to human expansion and influence on this fish’s habitat.
E. Objectives
Hypothesis 1: Mangrove habitat is essential to the location of rainbow parrotfish.
It has been well established that there is a functional dependency of juvenile fish
of this speciesrainbow parrotfish on mangrove habitat (Mumby et al. 2004). However,
absence of mangroves does not automatically equate with absence of the species
(Gonzalez-Salas et al. 2008). The extent of this importance of the mangrove habitat
needs to be quantified, particularly in areas that are subject to high human development.
Characteristics such as percent vegetative cover per square kilometer, and pressures such
as population density per square kilometer were used in assessing the suitability of the
habitat to this fish. Regression and occupancy models were used to quantify habitat
locations and they were ranked for suitability. Finally, they were ranked separately for
abundance of rainbow parrotfish.
Hypothesis 2: Mangrove density is a larger factor in rainbow parrotfish survival rather
than simply mangrove presence.
20
Mangroves provide this species of parrotfish with structure that in turn provides
shelter, shade, and sources of food. However, simply the presence of mangroves may not
be enough to support occupancy by rainbow parrotfish. The distance that mangrove
habitat extends from the shore was measured and correlated to parrotfish density. A
gradient corresponding to this distance was incorporated into the model to determine the
density of mangrove forests required to host a stable population of parrotfish. Based
upon this relationship, one can make suggestions about the relative importance of density
to presence and survival of this fish.
Hypothesis 3: Type of bBottom substrate plays a role in abundance and occurrence of
rainbow parrotfish.
Bottom substrate affects the plant biota present, as well as relating to the presence
of available shelter. Seagrasses grow where the bottom type tends to be sandy, whereas
encrusting algae need a hard or coralline substrate on which to attach. Rainbow
parrotfish are generally herbivorous and tend towards eating encrusting algae as noted by
scars on similar textured corals and sponges (Dunlop and Pawlik 1998). The
predominant bottom substrate type was correlated with the abundance and occupancy
results between the bottom substrate and the presence and viability of parrotfish to
determine if there is a correlation.
Hypothesis 4: Presence of preferred diet species determines location
While there is some plasticity in the diet preferences of this species of parrotfish,
there appears to be a hierarchy in the nutrient benefit provided by the different sources of
21
prey. Comparison of the locations preferred by the diet species with the predictions
provided by the model of the highest occurrence numbers of parrotfish was measured to
show if there is a correlation between diet location and abundance of rainbow parrotfish.
Hypothesis 5: Dissolved oxygen (DO) concentration is the most important abiotic factor
determining presence or absence of parrotfish in a particular location.
Rainbow parrotfish was observed across a range of temperatures that varied 24
°C, and salinity, that varied 16 ‰, while the range for DO varied less than 12 ‰. One
could then assume that a change in DO would have a much greater consequence than
would a change in one of the other factors. This change was modeled statistically, by
altering the DO numbers in the model and determining how it affects the abundance and
occurrence numbers. A literature review was conducted to determine how algal blooms
affect these abiotic factors and how these blooms might affect this fish.
2. Materials and Methods
To evaluate these hypotheses, a predictive model was developed to explain the
occurrence of S. guacamaia in a given area. The rRainbow parrotfish was chosen as the
study species because of its role as the largest herbivorous fish in the Caribbean region
and because its population numbers are in decline and , its with an IUCN listing as
vulnerable. The rainbow parrotfish was also selected because it had broad observation
coverage across the two datasets described below, and there has been limited work done
with this species using data from the Florida Keys and Biscayne Bay region, unlike
22
species such as sailor’s choice Haemulon parra and gray snapper Lutjanus griseus.
These are two species appearing in the datasets that have been studied in greater detail as
more work has been done in the region on grunts and snappers.
The datasets used in developing this model are the Mangrove Visual Census and
the Reef Visual Census. Data primarily come from the Mangrove Visual Census (MVC)
conducted over the years 1998-2007, as detailed in Serafy et al. (2003). This ongoing
study examined the fish assemblages along two types of mangrove-lined shoreline using
a visual ‘belt-transect’ census method over consecutive seasons in Biscayne Bay and the
Upper Florida Bay. This method entails snorkeling 30 m long transects parallel to the
shore and recording identity, number, and size-structure (minimum, mean and maximum
total length) of fishes observed. The width of each belt-transect was 2 m, giving an area
of 60 m2 per transect. Visual surveys were conducted between 09:00 and 17:00, thereby
minimizing visual identification problems associated with low light conditions. Censuses
were conducted during consecutive wet and dry seasons (i.e., July to September and
January to March, respectively) and transect locations were chosen at random each
season. Measurements of water quality and depth were obtained for each fish census.
Water temperature, salinity and dissolved oxygen were measured using a Hydrolab®
multi-probe instrument. Depth was measured along each transect at intervals of 15 m
using a 2 m long polyvinyl chloride pole marked at 2 cm intervals (Serafy et al. 2003).
This work examined both ontogenetic shifts for various fishes from mangroves to reefs,
and studied the trophic roles of varying shoreline habitats (Serafy et al. 2003).
Secondary sets of data were used from the Reef Visual Census (RVC), which was
begun in 1979 and was conducted through 2005. This study occurred on the reef tract
23
parallel to the Florida Keys and involved sampling fish community structure in virtual
cylinders with a radius of 7.5 m around randomly selected, stationary points (Bohnsack
and Bannerot 1986). Divers in this study began each sample site by facing in one
direction and listing all fish species within the field of view. When no new species were
noted, new sectors of the cylinder were scanned by rotating in one direction for the
duration of the five-minute period slated for each site. After the initial five minutes, data
were then collected on the abundance and minimum, mean, and maximum lengths for
each species sighted. An “all-purpose tool” (APT; a ruler connected perpendicularly to
the end of a meter stick) was utilized as a reference device to reduce potential
magnification errors in fish size estimates. Species with few individuals were counted
and their size estimated immediately. Highly mobile species, such as sharks and
carangids, unlikely to remain in the area were tabulated when first observed and then
ignored (Bohnsack and Bannerot 1986).
The Mangrove Visual Census measured a wide range of physical parameters, but
is limited temporally in that it was only begun in 1999. The Reef Visual Census covered
a much longer timeframe, but also recorded fewer physical data in the observations.
These datasets are beneficial since they both employ similar methods and occurred
concurrently (for at least part of the studies). In addition, both studies were performed in
the same region using low impact assessment methods. The drawbacks in using these
censuses are that there are limited data for the sand flats, seagrass beds, and the channels
that link these two habitats. The sampling locations are both a benefit and a drawback
because it provides coverage across a large range of area, but the sites selected were
random, and a more accurate picture might have been obtained in limiting the size of the
24
sampling area. Human error is also involved, leading to measurements and observations
that will not be absolutely accurate in situ. The use of different observers over the course
of the surveys will present slight problems, too, due to the inherent differences between
each observer’s individual technique and abilities. The fact that the MVC used
snorkeling methods and RVC used SCUBA is not a limitation as the methods reflected
the differences in depth of the survey sites. In using both of these studies, it is possible to
analyze and compare traits such as ontogenetic shifts, migration and habitat utilization
that would not be possible with analyses using only one dataset.
The model was set up initially in Microsoft Excel (Microsoft Corporation,
Version 12.0.6214.1000) and included the following parameters: temperature, dissolved
oxygen, salinity range/regime, average depth, distance from corridors, and mangrove
density. Habitat type, mangrove cover, substrate type, and shoreline development were
researched and used for comparison, but not incorporated into the model. The
parameters, such as mangrove cover and substrate type, not included in the original data
sets were primarily derived from available GIS map coverage data from agencies such as
the Florida Fish and Wildlife Conservation Commission and the United States Geological
Survey. The value for mangrove cover/density is defined as the distance of continuous
mangrove cover extending from the shoreline. Using the programs R (The R Foundation
for Statistical Computing, Version 2.6.0) and SAS (SAS Institute, Version 9.2), this set-
up was evaluated by a logistic multiple regression. Occupancy probability models were
run in program Mark (Gary C. White, Colorado State, Version 5.1) that incorporates
Bayesian methods as detailed in MacKenzie et al. (2003). This gives probability of
occurrence and detection under imperfect or incomplete conditions, within a set
25
timeframe. In other words, this allows the model to estimate occupancy over a given
amount of time, while not needed to be present to observe every individual.
Logistic regression was chosen because this analysis is used to predict the
probability that an event of interest will occur as a linear function of one or more
continuous and/or dichotomous independent variables (Karp 2001). Regression modeling
used to relate the variations in large-scale distributions to key habitat variables is the
approach of habitat association modeling (Freckleton et al. 2006). It also goes that
maximum likelihood estimators in logistic regression are approximately normally
distributed, with little or no bias (Ragavan 2008), but in the same study we might often
need at least two types of models: one for description/interpretation and another for
prediction (Shtatland et al. 2001). The corresponding informational outputs and
regression values, the numerical values that resulted from the model’s initial setup
parameters, would then be ranked according to habitat, abundance, and size and plotted
spatially on a GIS map using ArcGIS (ESRI, Version 9.2).
3. Results
The data sets used for this work consisted of 1,812 sites in the Mangrove Visual
Census (MVC), of which 1,798 were used, and 13,443 sites in the Reef Visual Census
(RVC), of which 764 points were used. Sites from the MVC were omitted if there was
one or more physical parameter for which there was no data and sites from the MVC
were omitted if there was not rainbow parrotfish observed at that site. In the MVC
rainbow parrotfish was observed at 107 of the 1,798 sites, consisting of a total of 533
26
individuals. In the RVC rainbow parrotfish was observed at 764 of the 13,443 sites,
consisting of a total of 1,499 individuals. Of these individuals, 57 were of mature size in
the MVC and 688 were of mature size in the RVC (refer to Table 1). This gives naïve
occupancy, a measure of total observed individuals divided by the total number of
locations, of 0.3052 for the MVC, and naïve occupancy of 0.1115 for the RVC.
Using the GPS-based positions points included in the respective data sets, the
locations of the rainbow parrotfish individuals were plotted on a map using ArcGIS. ,
fInitiallyirst, all observed individuals (Figure 1) were plotted, and then these individuals
were broken down into groups by size of 0-100 mm, 100-200 mm, 200-300 mm, and
greater than 300 mm (Figures 3, 4, 5, 6). Each of these maps were further separated by
number of individuals at each site, in groups corresponding to 1-5 individuals, 6-15
individuals, or 16-80 individuals. These groups were represented on the maps by with
points of increasing size, ; the breakdown of these numbers is shown in Table 2.
These numbers values are visualized shown in Figure 7, which depicts the
size distribution for the rainbow parrotfish individuals, and Figure 8, which shows the
size-frequency distribution for the rainbow parrotfish individuals. With this size
information, the sites were mapped again, broken down into the locations of observed
juvenile and mature individuals for the MVC (Figure 18) and RVC (Figure 19).
Next, a logistic regression analysis was performed using the variables in the MVC
of temperature, dissolved oxygen, salinity, average depth, and the distance from island
channels. Distance from the island channels was not included in the initial measurements
of the data set but rather was calculated by taking the GPS location in the center of each
27
of the eight channels (Figure 2) and measuring the distance to each site using the
equation:
Distance = R*(acos((sin(lat1/r)*sin(lat2/r))+(cos(lat1/r)*cos(lat2/r)*cos((lon2-lon1)/r)))),
where R = 6370, ( Earth’s radius (in kilometers) and r = (360/(2*πpi)).
The closest distance from each point to the channel opening was the value used.
The RVC data were omitted because the environmental (?) variables, except for other
than depth were not recorded, and depth was not taken recorded at any study sites where
a rainbow parrotfish was not observed. To set up the regression analysis, the five
aforementioned values were measured against the presence (1) or absence (0) of Scarus
guacamaia individuals at each site. Logistic regression analyses were then performed for
each of the five variables individually against presence or absence. The total regression
was found to be significant with a Pr > Chi-square values of < 0.0001 and salinity,
average depth, and channel distance were found to be significant with Pr > Chi-square
values of 0.0014, <0.0001, and 0.0001, respectively. Temperature and dissolved oxygen
were found to not be significant with Pr > Chi-square values of 0.8359 and 0.7855,
respectively.
These results coincide with the results of the ROC curve, a measure of sensitivity
versus specificity, better termed as a representation of the trade off between the false
negative and false positive rates for every possible value. An ideal test has a value of 1.0
indicating 100% sensitivity and specificity, meaning the false negative rate is high and
the false positive rate is low. When the ROC curve follows a diagonal path from the
28
lower left hand corner to the upper right hand corner this means that every improvement
in false positive rate is matched by a corresponding decline in the false negative rate, and
the area under the curve is closer to 0.5 indicating 50% sensitivity and 50% specificity.
For the total regression, the area under the ROC curve was a value 0.921, for temperature
it was a value of 0.544, for dissolved oxygen it was a value of 0.599, for salinity it was a
value of 0.774, for average depth it was a value of 0.821, and for distance from channel
openings, it was a value of 0.886.
The results of the logistic regression indicate that using the five variables together
is the best predictor of presence or absence; salinity, depth and distance from channel
openings are adequate predictors of presence or absence, while temperature and dissolved
oxygen are not significant in predicting presence or absence. Inflection points of the
logistic regression curves for salinity occurred at 36.4 ‰ with a predicted Y1 of 0.100
(Figure 9), 103.5 cm average depth with a predicted Y1 of 0.150 (Figure 10) and 3.5 km
distance from the closest channel opening, with a predicted Y1 of 0.11633 (Figure 11).
Out of the 1,798 sites in the MVC, 414 were above the inflection point for salinity values,
148 were above the inflection point for average depth values, and 316 were above the
inflection point for channel distance values. Table 3 shows the complete breakdown of
the predicted Y1 regression values for all of the five variables, as well as the total for the
three significant values.
The total predicted Y1 values are mapped out for the Biscayne Bay region, seen
in Figure 12, as well as for temperature (Figure 13), dissolved oxygen (Figure 14),
salinity (Figure 15), and average depth (Figure 16).
29
Table 1. Percentages of Scarus guacamaia at mature size for mangrove and reef study
sites. Number is given by individuals at mature size out of total number of individuals,
and Site is given by number of sites where mature individuals were observed out of the
total number of study sites with observations of Scarus guacamaia.
Scarus guacamaia
Mangrove (#): 10.31%
Mangrove (Site): 8.41%
Reef (#):45.90%
Reef (Site): 35.99%
(Individuals/Total)(57/553)
(Sites/Total)(9/107)
(Individuals/Total)(688/1,499)
(Sites/Total)(275/764)
30
Table 2. Number of study sites in the Mangrove Visual Census and Reef Visual Census
broken down by the size and the number of Scarus guacamaia individuals observed.
Mangrove Visual Census Reef Visual CensusNumber of Individuals: 1-5 6-15 16-80 1-5 6-15 16-800-100 mm 3 0 0 11 0 0100-200 mm 40 11 0 41 0 0200-300 mm 31 12 2 96 3 1300+ mm 4 3 1 578 27 7
31
Table 3. Number of study sites within each range of predicted Y1 regression values.
Temperature Range: 1 = 0-0.04, 2 = 0.04-0.045, 3 = 0.045-0.05, 4 = 0.05-0.055, 5 =
0.055-0.06, 6 = 0.06-0.065, 7 = 0.065-0.07, 8 = 0.07-0.075, 9 = 0.075 and greater.
Dissolved Oxygen Range: 1 = 0-0.025, 2 = 0.025-0.035, 3 = 0.035-0.045, 4 = 0.045-
0.055, 5 = 0.055-0.065, 6 = 0.065-0.075, 7 = 0.075-0.085, 8 = 0.085-0.095, 9 = 0.095-
0.105, 10 = 0.105-0.115, 11 = 0.115-0.125, 12 = 0.125-0.135 and greater.
Salinity Range: 1 = 0-0.02, 2 = 0.02-0.04, 3 = 0.04-0.075, 4 = 0.075-0.12, 5 = 0.12-0.16,
6 = 0.16-0.2, 7 = 0.2-0.233, 8 = 0.233-0.267, 9 = 0.267 and greater.
Average Depth Range: 1 = 0-0.01, 2 = 0.01-0.033, 3 = 0.033-0.067, 4 = 0.067-0.1, 5 =
0.1-0.133, 6 = 0.133-0.167, 7 = 0.167-0.2, 8 = 0.2-0.25, 9 = 0.25-0.3, 10 = 0.3-0.35, 11 =
0.35-0.45, 12 = 0.45-0.55, 13 = 0.55-0.6, 14 = 0.6-0.65, 15 = 0.65 and greater.
Channel Distance Range: 1 = 0=0.05, 2 = 0.05-0.1, 3 = 0.1-0.15, 4 = 0.15-0.2, 5 = 0.2-
0.25, 6 = 0.25-0.3, 7 = 0.3-0.333, 8 = 0.333-0.367, 9 = 0.367 and greater.
Total (Salinity + Average Depth + Channel Distance) Range: 1 = 0-0.05, 2 = 0.05-0.1, 3
= 0.1-0.15, 4 = 0.15-0.2, 5 = 0.2-0.25, 6 = 0.25-0.3, 7 = 0.3-0.35, 8 = 0.35-0.4, 9 = 0.4-
0.45, 10 = 0.45-0.5, 11 = 0.5-0.55, 12 = 0.55-0.6, 13 = 0.6-0.65, 14 = 0.65-0.7, 15 = 0.7
and greater.
Temperature Regression ValuesRange 1 2 3 4 5 6 7 8 9
32
Number 11 65 202 377 255 273 404 182 29Dissolved Oxygen Regression ValuesRange 1 2 3 4 5 6 7 8 9 10 11 12Number 17 95 267 432 393 256 139 114 60 18 4 3Salinity Regression ValuesRange 1 2 3 4 5 6 7 8 9Number 604 292 255 388 153 61 28 9 8Average Depth Regression ValuesRange 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Number 32 807 516 171 97 57 35 38 18 6 9 8 2 1 1Channel Distance Regression ValuesRange 1 2 3 4 5 6 7 8 9Number 1242 196 86 62 41 86 54 12 19Total Regression ValuesRange 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Number 389 393 244 184 129 88 74 61 76 71 39 21 13 7 9
Figure 1. Location and Size size of observed Scarus guacamaia individuals from
Mangrove Visual Census (black) and Reef Visual Census (orange) data.
33
Figure 2. Location and Names of Channels along Florida Keys involved in study sites.
34
Figure 3. Location of observed Scarus guacamaia individuals sized 0-100 mm from
Mangrove Visual Census and Reef Visual Census data.
35
Figure 4. Location of observed Scarus guacamaia individuals sized 100-200 mm from
Mangrove Visual Census and Reef Visual Census.
36
Figure 5. Location of observed Scarus guacamaia individuals sized 200-300 mm from
Mangrove Visual Census and Reef Visual Census.
37
Figure 6. Location of observed Scarus guacamaia individuals sized greater than 300 mm
from Mangrove Visual Census and Reef Visual Census.
38
Figure 7. Rainbow pParrotfish Ssize Ddistribution.
39
Rainbow Parrotfish Size Distribution
0
50
100
150
200
250
300
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85
Size (cm)
Num
ber
of In
divi
dual
sMangrove Data
Reef Data
mature
40
Figure 8. Rainbow Parrotfish parrotfish Sizesize-Frequency frequency
Distributiondistribution.
Rainbow Parrotfish Size-Frequency Distribution
0
0.05
0.1
0.15
0.2
0.25
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85
Size (cm)
Freq
uenc
y (a
s %
of t
otal
)
Mangrove Data
Reef Data
mature
41
Figure 9. Logistic rRegression for Ssalinity, with salinity values in parts-per-thousand
(‰) on x-axis.
.
Logistic regression of Y1 by X1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50
X1
Y1
Active Model
Low er bound (95%) Upper bound (95%)
42
43
Figure 10. Logistic Regression regression for Average average Depthdepth, with average
depth values (cm) on x-axis.
Logistic regression of Y1 by X1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 50 100 150 200
X1
Y1
Active Model
Low er bound (95%) Upper bound (95%)
44
Figure 11. Logistic Regression for Channel Distance, Channel Distance (km) on x-axis.
Logistic regression of Y1 by X1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50
X1
Y1
Active Model
45
Figure 12. Map of study sites for Scarus guacamaia color-coded for predicted logistic
regression values combined from salinity, water depth, and distance from channels.
46
Figure 13. Map of study sites for Scarus guacamaia color-coded for predicted logistic
regression values for temperature measurements.
47
Figure 14. Map of study sites for Scarus guacamaia color-coded for predicted logistic
regression values for dissolved oxygen measurements.
48
Figure 15. Map of study sites for Scarus guacamaia color-coded for predicted logistic
regression values for salinity measurements.
49
Figure 16. Map of study sites for Scarus guacamaia color-coded for predicted logistic
regression values for average depth measurements.
50
Figure 18. Location of observed Scarus guacamaia individuals from Mangrove Visual
Census data separated by size into juveniles and mature individuals.
51
Figure 19. Location of observed Scarus guacamaia individuals from Reef Visual Census
data separated by size into juveniles and mature individuals.
52
Figure 20. Biscayne National Park Map, detailing locations names used in study. From:
http://lib.utexas.edu/maps/national_parks/bisc_95.jpg,
53
http://www.nps.gov/PWR/customcf/apps/maps/showmap.cfm?
alphacode=bisc&parkname=Biscayne%20National%20Park
4. Discussion
54
This study has shown that in using the five aforementioned variables, it is possible
to significantly predict the occurrence of rainbow parrotfish individuals. Furthermore,
the variables of salinity, average depth, and distance from channel opening are each
significant in predicting the occurrence of rainbow parrotfish, while temperature and
dissolved oxygen are not. Dissolved oxygen was initially hypothesized to be a more
important factor than salinity, because the measurements taken of this variable were
across a smaller range than variables such as temperature and salinity, which turned out
not to be the case. Temperature and dissolved oxygen can vary greatly across very small
distances, and variations can be highly localized. The ability of this species for
movement across daily ranges of up to several thousand cubic meters means adjusting for
slight variations in temperature or dissolved oxygen to more suitable conditions would
not be a limitation. Salinity would present more of a problem of avoidance for rainbow
parrotfish should conditions become unfavorable. The problem occurs as salinity
gradients are more gradual, but fluctuations have the potential to spike drastically and
persist for greater time periods over larger areas. The inflection point for salinity
occurred at 36.4 ‰, with a predicted Y1 of 0.100, meaning that there is a lower than 10%
chance of occurrence at any site where salinity is below that value. With these values,
occurrence is much more likely to occur in waters than have salinities in the range of 35-
40 ‰, corresponding with the clear, warm, natural oligotrophic waters of the Florida reef
tract. The clear, shallow waters of coastal estuaries from Biscayne Bay to Barnes Sound
possess natural salinities near saltwater strength, providing the optimal salinity conditions
as nursery grounds and transition habitats.
55
Average depth is a significant variable probably due to several reasons. The
inflection point for this regression analysis was 103.5 cm, meaning a water depth of about
a meter is the critical value for predicting occurrence. The rainbow parrotfish diet
consists of benthic turf algae with incidental corallivory and it has also been shown
(Verweij et al. 2006) that plant structure is preferred by rainbow parrotfish. In depths of
water less than a meter, there is less available space for swimming, foraging and shelter,
and conditions at that depth may be suboptimal for epiphytic plant and algal growth.
Halimeda species have shown optimal photosynthesis at depths of one meter (Häder et al.
2008) and Caulerpa species have shown optimal photosynthesis at depths of five meters
(Häder et al. 1997). The Häder et al. (1997) study also showed that exposure to solar
radiation at the surface caused a drastic decline in the effective photosynthetic quantum
yield, and to a smaller extent nonreversible photodamage. Much of the coral substrate of
the Florida reef tract on which rainbow parrotfish inhabits is greater in depth than a
meter, generally depths of five to greater than ten meters (Duffy 2007), so it becomes a
question of necessity that to find suitable habitat, inhabiting depths of greater than a
meter is required. The deeper waters are also less subject to changes in sediment loads,
which can affect bay water clarity leading to changes in the benthic algae cover, as well
as seagrass and drifting macroalgal communities, which comprise most of the submerged
aquatic vegetation.
Distance from channel opening is significant due to the separate juvenile and
mature life history stages that take place in the mangrove communities, and on the coral
reef, respectively because to there needs to be a pathway for this transition to take place,
and the closer an individual is to these channels, reduces the costs due to predation,
56
energy expended, and search for food. Rainbow parrotfish is known to have a large
home range with an ability to swim over great distances, but the less time spent
transitioning between suitable habitat allows for allotting less energy on avoidance,
swimming, and escape, and more on foraging and reproduction.
The maps of predicted regression values for the Biscayne Bay region illustrate
these points. Mangrove-lined shorelines of the leeward keys in Biscayne Bay and Upper
Card sound have the highest predicted Y1 values. Here, the mangrove density and
coverage is the greatest and substrate coverage is hardbottom, as well as a large
proportion being part of Biscayne National Park. The next tier of Y1 values could be
found on the selected windward sites outside of Biscayne National Park, and in the areas
of Card Sound and Upper Florida Bay, where mangrove coverage is high near where the
Overseas Highway enters onto the Keys.
The lowest predicted values are found on the mainland shorelines. In this area,
there is low mangrove coverage, and low density of mangroves back from the shoreline.
The, and bottom coverage is also composed of seagrass, rather than hard substrate,
further limiting available diet resources for rainbow parrotfish. In addition, predators
such as barracuda, sharks, snappers and grunts are high in numbers in this area (MVC
data), and the anthropogenic influence is higher due to continued development in South
Florida. Sediment cores from Manatee Bay show a history of mangrove peat deposition
followed by a progressive increase in marine mud and sands. In contrast, Card Sound
and Pelican Bank show evidence of peat and high vegetation accumulation in their early
history followed by an increase in marine and or carbonate clastic deposition (Ishman
1997). The normal bottom coverage has been disrupted because of removal of natural
57
flora in the area has impeded biophysical cycling regimes, resulting in sub-optimal
habitat. Often activities such as feeding, reproduction, and resting occur in different
habitat types, and the home range consists of two areas joined by a narrow movement
path (Kramer and Chapman 1999). This reduced viability of hardbottom banks between
mangrove and reef habitats limits the effectiveness of transitioning between life stages.
The mainland edge consists of freshwater wetlands, which contain fringing,
riverine, and basin mangrove communities, separated from marine habitats in certain
places by a mud embankment that impedes freshwater runoff. Natural freshwater input
from rainfall and runoff is now disrupted as water flows through artificial drainage canals
as opposed to natural channels and circulation. This has lead to a variable freshwater
flow in many near shore areas of Biscayne and Florida Bays, such that downstream
salinity regimes are suboptimal for freshwater, brackish, and marine organisms. Rainbow
parrotfish are pelagic spawners, leaving larvae settlement subject to flow regimes and
currents. Larval development is thus impaired in areas that are meant to function as
nursery grounds by the compounding problems of lack of suitable habitat and increased
distance from adult coral reef habitats. Greater numbers of S. guacamaia individuals are
found on the northern edge of the Florida reef tract where suitable mangrove stands are
present as opposed to farther south, where development has left much of the windward
and leeward shores absent of mangrove stands.
Rainbow parrotfish is listed as vulnerable under IUCN criteria, a designation
given due to not only a reduction in suitable habitat, but also reduced size of individuals.
Reduced individual size leaves fewer numbers of those that are functionally mature and
have a significant impact on their ecosystem. Rainbow parrotfish and other similar
58
species need to be looked at in greater focus, as to how their loss will impact the
Caribbean region. In most parts of the Caribbean, parrotfishes are a major component of
reef and subsistence fisheries, especially where their slower-growing predators have long
been depleted (Hughes et al. 2007).
Rainbow parrotfish have several crucial roles in the dynamics of tropical reefs:
they graze fleshy seaweeds that compete with juvenile and adult corals for space; , they
erode dead coral skeletons and generate reef sediments, and they are an important trophic
link between their natural predators and algal primary producers (Hughes et al. 2007).
Parrotfish density will vary spatially and temporally in response to local rates of
recruitment and mortality (Hughes et al. 2007) while habitat suitability varies spatially,
allowing populations to persist only when the habitat quality exceeds some threshold,
thus an increase in average habitat quality leads to simultaneous increases in average
densities within occupied areas, as well as the total area that is habitable (Freckleton et al.
2006).
Implementation of an adequate marine reserve in this region could help to ensure
the viability of not only this species, but also the biodiversity present across these
habitats. The Florida Keys are protected by a National Marine Sanctuary, multiple state
parks, and National Wildlife Refuges farther south than the scope of this study.
However, within these boundaries, very little area is designated as ecological reserve, and
only small, individual reefs are designated as sanctuary preservation areas. Reserves can
only protect fish species if movement of individuals remains within a localized home
range, contained fully within the reserve boundaries, during at least part of their life cycle
(Kramer and Chapman 1999). This, which is not the case for rainbow parrotfish and
59
many other reef fish species. Home range size has been shown to be a power of body
size (Kramer and Chapman 1999), so without an adequately sized preserve area, rainbow
parrotfish may face pressure or even inability to reach maximum or functional size. In
addition, on fringing coral reefs, where habitat zonation parallels depth contours, the
home ranges of larger species are considerably longer in the dimension parallel to the
depth contours than in the dimension perpendicular to it (Kramer and Chapman 1999).
This illustrates the need for not only adequately sized reserves, but also properly shaped
ones as well. Relocation of the home range is one possibility, which involves selection
for and movement to a novel habitat patch. This can occur as a response to changes in a
despotic distribution, one with a dominant male and a harem of submissive females,
either by competition with other parrotfish species or with sex change within a harem. In
this case, however, the costs of relocation will increase with the investment required to
learn the characteristics of the home range, which may be larger for species such as S.
guacamaia that use the complex substrate for feeding and refuge (Kramer and Chapman
1999).
Solutions proposed in other marine regions are “no-take” areas and networks of
Marine Protected Areas or MPAs. These MPA networks can function to sustain resident
populations both by local replenishment and through larval dispersal from other reserves
(Planes et al. 2009). Protecting spawning areas of reef fishes spills over and replenishes
neighboring areas of coral reef and related habitats, and larval subsidies from a single
reserve may contribute to the resilience of subpopulations at other reserves within a
network of MPAs (Planes et al. 2009). This has been shown to be effective for protecting
grouper spawning aggregations, but may prove difficult with rainbow parrotfish, and a
60
broader coverage net would most likely be necessary. In studies by Mumby et al. (2006),
it was found that biomass of parrotfish was reduced by 30-–60% on adjacent reefs,
compared with biomass in the no-take area., and In another study,along with the
elevated biomass of parrotfish in a no-take area resulted in an, estimated grazing intensity
that was six times higher, and the cover of seaweed within the park was five times lower
(Hughes et al. 2007).
Proper stewardship of marine parks by local communities can enhance grazing
and help to prevent regime shifts from coral- to algal-dominated systems. M, however
many marine parks have been established by central governments or foreign NGOs, but
they remain ineffective because they lack local support or adequate management (Hughes
et al. 2007). In the Florida Keys, estimates range that 33-75% of local income is due to
diving and tourism, with an additional 5-8% coming from commercial fishing (National
Marine Sanctuaries website), and to limit this use of offshore areas would put a great
strain on the residents of these communities. However, marine parks and protected areas
have shown to be effective in preserving species such as rainbow parrotfish and total
biodiversity in other regions while not impinging on the local livelihoods. In the Mumby
et al. (2006) study, populations had not leveled off even after the marine park had been in
existence for over twenty years, implying that results, no matter what is done, may not be
seen immediately. In not revising the situation, as it currently exists, and developing a
marine protected area that ensures future biodiversity and sustainable resident
populations would be to lose not only the aims of preservation, but also the livelihood
that depends on them. A concerted effort needs to be undertaken to create self-sufficient
marine preserves that incorporate mangrove and reef habitat as well as connecting
61
corridors, based first on solid science, and one that incorporates the needs of all the
stakeholders.
62
References
Bellwood D.R., Hughes T.P., Folke C., Nyström M. 2004. Confronting the Coral Reef Crisis.
Nature. 429 (2004): 827-833.
Bohnsack J.A. and Bannerot S.P. 1986. A stationary visual census technique forquantitatively assessing community structure of coral reef fishes. Miami (FL): National Marine Fisheries Service. NOAA Technical Report NMFS. 41: 15 p.
Cervigón, F. The Marine Fish of Venezuela, Volume 3. Caracas: Fundación CientíficaLos Roques, 1994.
Cole A.J., Pratchett M.S. and Jones G.P. Diversity and functional importance of coralfeeding fishes on tropical coral reefs. Fish and Fisheries. 9 (2008): 286-307.
Dorenbosch M., Verberk W.C.E.P., Nagelkerken I., van der Velde G. Influence of habitatconfiguration on connectivity between fish assemblages of Caribbean seagrass beds, mangroves and coral reefs. Marine Ecology Progress Series. 334 (2007): 103-116.
Dorenbosch M., Grol M.G.G., Nagelkerken I., van der Velde G. Seagrass beds andmangroves as potential nurseries for the threatened Indo-Pacific humphead wrasse, Cheilinus undulatus and Caribbean rainbow parrotfish, Scarus guacamaia. Biological Conservation. 129 (2006): 277-282.
Dorenbosch M., van Riel M.C., Nagelkerken I., van der Velde G. The relationship of reeffish densities to the proximity of mangrove and seagrass nurseries. Estuarine, Coastal and Shelf Science. 60 (2004): 37-48.
Duffy J.E. 2007. “Coral reefs in Florida.” In: Encyclopedia of Earth. Eds. Cutler J.Cleveland (Washington, D.C.: Environmental Information Coalition, National Council for Science and the Environment). [First published in the Encyclopedia of Earth August 28, 2006; revised February 8, 2007; Retrieved November 4, 2009].
Dunlap M. and Pawlik J.R. Spongivory by parrotfish in Florida mangrove and reefhabitats. Marine Ecology. 19 (1998): 325-337.
Faunce C.H. and Serafy J.E. Selective use of mangrove shorelines by snappers, grunts,and great barracuda. Marine Ecology Progress Series. 356 (2008): 153-162.
Floeter S.R., Halpern B.S., Ferreira C.E.L. Effects of fishing and protection on Brazilianreef fishes. Biological Conservation. 128 (2006): 391-402.
Fourqurean J.W. and Robblee M.B. Florida Bay: A History of Recent EcologicalChanges. Estuaries. 22 (1999): 345-357.
63
Freckleton R.P., Noble D., Webb T.J. Distributions of habitat suitability and theabundancy occupancy relationship. The American Naturalist. 167 (2006): 260-275.
Freeman A.S., Short F.T., Isnain I., Razak F.A., Coles R.G. Seagrass on the edge: Landuse practices threaten coastal seagrass communities in Sabah, Malaysia. Biological Conservation. 141 (2008): 2993-3005.
Gonzalez-Salas C., Aguilar-Perera A., Villegas-Hernández H. Density, biomass, andhabitat association of the rainbow parrotfish, Scarus guacamaia, in Alacranes Reef, Northern Yucatan Peninsula. Poster presented as part of the 11th International Coral Reef Symposium, Fort Lauderdale, Florida, 7-11 July 2008.
Häder D.P., Porst M., Herrmann H., Schäfer J., Santas R. Photoinhibition in theMediterranean Green Alga Halimeda tuna Ellis et Sol measured in situ. Photochemistry and Photobiology. 64 (2008): 428-434.
Häder D.P., Porst M., Herrmann H., Schäfer J., Santas R. Photosynthesis of theMediterranean green alga Caulerpa prolifera measured in the field under solar irradiation. Photochemistry and Photobiology. 37 (1997): 66-73.
Haus B.K., Wang J.D., Rivera J., Martinez-Pedraja J., and Smith N. Remote radarmeasurement of shelf currents off Key Largo, Florida, U.S.A. Estuarine, Coastal and Shelf Science. 51 (2000): 553-569.
Hughes T.P., Bellwood D.R., Folke C.S., McCook L.J., Pandolfi J.M. No-take areas,herbivory and coral reef resilience. TRENDS in Ecology and Evolution. 22 (2007): 1-3.
Ishman S.E. 1997. Ecosystem History of South Florida: Biscayne Bay Sediment CoreDescriptions. U.S. Geological Survey Open File Report 97-437: 15 p.
Karp A.H. Getting Started with PROC LOGISTIC. Proceedings of SAS® Users GroupInternational, SUGI 26, 2001, Long Beach.
Kramer D.L. and Chapman M.R. Implications of fish home range size and relocation formarine reserve function. Environmental Biology of Fishes. 55 (1999): 65-79.
Kuffner I.B., Grober-Dunsmore R., Brock J.C., Hickey T.D. Biological communityStructure on patch reefs in Biscayne National Park, FL, USA. Environmental Monitoring and Assessment. Published Online (April 28, 2009): http://www.springerlink.com/content/708k6175728p176m/fulltext.pdf
Lokrantz J., Nyström M., Thyresson M., Johansson C. The non-linear relationshipbetween body size and function in parrotfishes. Coral Reefs. 27 (2008): 967-974.
64
MacKenzie D.I., Nichols J.D., Hines J.E., Knutson M.G., Franklin A.D. Estimating SiteOccupancy, Colonization and Local Extinction when a species is detected imperfectly. Ecology. 84 (2003): 2200-2207.
Mumby P.J. and Hastings A. The impact of ecosystem connectivity on coral reef resilience. Journal of Applied Ecology. 45 (2008): 854-862.
Mumby P.J. Connectivity of reef fish between mangroves and coral reefs: Algorithms forthe design of marine reserves at seascape scales. Biological Conservation. 128 (2006): 215-222.
Mumby P.J., Edwards A.J., Arias-Gonzalez J.E., Lindeman K.C., Blackwell P.G., GallA., Gorczynska M.I., Harborne A.R., Pescod C.L., Renken H., Wabnitz C.C.C., Llewellyn G. Mangroves enhance the biomass of coral reef fish communities in the Caribbean. Nature. 427 (2004): 533-536.
Munoz R.C. and Motta P.J. Interspecific Aggression between Two Parrotfishes(Sparisoma, Scaridae) in the Florida Keys. Copeia. 3 (2000): 674-683.
Nagelkerken I. Are non-estuarine mangroves connected to coral reefs through fishmigration? Bulletin of Marine Science. 80 (2007): 595-607.
Nagelkerken I., Dorenbosch M., Verberk W.C.E.P., Cocheret de la Morinière E., van derVelde G. Importance of shallow-water biotopes of a Caribbean bay for juvenile coral reef fishes: patterns in biotope association, community structure and spatial distribution. Marine Ecology Progress Series. 202 (2000): 175-192.
Nakamura Y. and Tsuchiya M. Spatial and temporal patterns of seagrass habitat use byfishes at the Ryukyu Islands, Japan. Estuarine, Coastal and Shelf Science. 76 (2008): 345-356.
Planes S., Jones G.P., Thorrold S.R. Larval dispersal connects fish populationsin a network of marine protected areas. Proceedings of the National Academy ofScience. 106 (2009): 5693-5697.
Randall J.E. 1962. Tagging reef fishes in the Virgin Islands. Marathon (FL): Gulf andCaribbean Fisheries Institute. Proceedings of the Gulf and Caribbean FisheriesInstitute. 14: 201-241.
Ragavan A.J. How to use SAS® to fit Multiple Logistic Regression Models. Proceedingsof SAS® Global Forum, 2008, San Antonio.
Roberts, C. 1996. Scarus guacamaia. In: IUCN 2009. IUCN Red List of ThreatenedSpecies. Version 2009.1. <www.iucnredlist.org>. Downloaded on 01 September 2009
65
Robertson A.I. and Duke N.C. Mangrove fish-communities in tropical Queensland,Australia: spatial and temporal patterns in densities, biomass and community structure. Marine Biology. 104 (1990): 369-379.
Robins C.R. and Ray, G.C. 1986. A field guide to Atlantic coast fishes of North America.Boston (MA): Houghton Mifflin Company.
Rotjan R.D. and Lewis S.M. Parrotfish abundance and selective corallivory on a Belizeancoral reef. Journal of Experimental Marine Biology and Ecology. 335 (2006): 292-301.
Rudnick D., Madden C., Kelly S., Bennett R., Cunniff K. Report on Algal Blooms inEastern Florida Bay and Southern Biscayne Bay. 2007 South Florida Environmental Report, Appendix 12-3. South Florida Water Management District. 28 p.
Rummer J.L., Fangue N.A., Jordan H.L., Tiffany B.N., Blansit K.J., Galleher S.,Kirkpatrick A., Kizlauskus A.A., Pomory C.M., Bennett W.A. Physiological tolerance to hyperthermia and hypoxia and effects on species richness and distribution of rockpool fishes of Loggerhead Key, Dry Tortugas National Park. Journal of Experimental Marine Biology and Ecology. 371 (2009): 155-162.
Shtatland E.S., Cain E.M., Barton M.B. The Perils of Stepwise Logistic Regression andhow to escape them using information criteria and the output delivery system.Proceedings of SAS® Users Group International, SUGI 26, 2001, Long Beach.
Shtatland E.S., Kleinman K., Cain E.M. Stepwise Methods in using SAS® PROCLOGISTIC and SAS® Enterprise Miner™ for Prediction. Proceedings of SAS® Users Group International, SUGI 28, 2003, Seattle.
Smith C.L. 1997. National Audubon Society Field Guide to Tropical Marine Fishes of theCaribbean, the Gulf of Mexico, Florida, the Bahamas, and Bermuda. New York (NY): Alfred A. Knopf.
Smith L.L., Fessler J.L., Alfaro M.E., Streelman J.T., Westneat M.W. Phylogeneticrelationships and the evolution of regulatory gene sequences in the parrotfishes. Molecular Phylogenetics and Evolution. 49 (2008): 136-152.
Serafy J.E., Faunce C.H., Lorenz J.J. Mangrove Shoreline Fishes of Biscayne Bay,Florida. Bulletin of Marine Science. 72 (2003): 161–180.
Streelman J.T., Alfaro M., Westneat M.W., Bellwood D.R., Karl S.A. EvolutionaryHistory of the Parrotfishes: Biogeography, Ecomorphology, and Comparative Diversity. Evolution. 56 (2002): 961-971.
66
Unsworth R.K.F., Taylor J.D., Powell A., Bell J.J., Smith D.J. The contribution of scaridherbivory to seagrass ecosystem dynamics in the Indo-Pacific. Estuarine, Coastal and Shelf Science. 74 (2007): 53-62.
Verweij M.C., Nagelkerken I., de Graff D., Peeters M., Bakker E.J., van der Velde G.Structure, food and shade attract juvenile coral reef fish to mangrove and seagrass habitats: a field experiment. Marine Ecology Progress Series. 306 (2006): 257-268.
Wang J.D., Luo J., and Ault J.S. Flows, salinity and some implications for larvaltransport in South Biscayne Bay, Florida. Bulletin of Marine Science. 72(2003): 695-723.
67
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