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Processes Regulating CoralCommunities

R. van WoesikDepartment of Biological Sciences,Florida Institute of Technology, Melbourne,Florida, USA

While coral reefs support more species than any other marine system,coral reef ecology bo"ows heavily from theoretical advances in low-diversity te"estrial systems. This article reviews recent developments inecology on coral reefs and weaves together the relevant informationwithin a theoretical framework that aims toward predictive modeling ofcoral populations and communities. The author begins with a historicalperspective, involving arguments that shaped modern community theory,and introduces coral communities within this context. The majorparameters that shape coral community structure are outlined and thequestion of whether competition between corals and disturbancefrequency actually drives diversity and local community structure i.fdiscussed. Within the context of metapopulation modeling, involvingcolonization and extinction events, the author discusses reef connectivityand postsettlement processes and argues for a neutral model with highdiversity as the default system. The article concludes with a briefdiscussion on deficiencies in coral community data and future modelingdirections.

Keyword\":

Many thanks are extended to A~w Baird. Mark Bush. and Sandra van Woesik forstimulating comments on the manuscript of this article.

Address conespondence to R. van Woesik. Depanment of Biological Sciences. FloodaInstitute of Technology. ISO West University Boulevard. Melboome. FL 32901-6988. USA.

E-mail: rvw@fit.edu

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Many questions in coral reef ecology remain unresolved. For example, whatmechanisms and processes regulate coral community diversity, and how isthat diversity related to different features of the environment? Are coralcommunities niche assembled or driven by dispersal processes? Arecommunities consistently interrupted by disturbance or simply assembledby competitive interactions? Do the community patterns we see on coral reefsarise from random allocation of space controlled by forces outside the localsystem? Just as we were beginning to answer some of these questions and tounderstand the processes that shape coral reefs, reefs have begun to degradeworldwide. This makes modeling even more pertinent because reliableforecasting and predictive models reduce the risk of laissez-faire manage-ment Accurate models have the potential to alert managers to the source ofspecific problems and encourage implementation of appropriate policies andmanagement strategies.

REVISITING AN OLD ARGUMENT

Are communities built up over time in accordance with specific assemblyrules, with competition as the underlying process? Clements (1916) arguedfor the importance of biotic interactions among species largely affect theirdistribution, while Gleason (1917) regarded communities as loose assem-blages shaped by the physical environment. Indeed, the question as towhether environmental variability can promote species diversity by destab-ilizing a stable equilibrium has challenged theoretical and field ecologistsfor decades.

Hutchinson (1953, 1957) suggested that spatially high site variabilitymight be.sufficient to maintain high regional species diversity. Hutchinson(1961) showed that a stable equilibrium was not necessary for coexistence aslong as environmental change was sufficiently frequent to changecompetitive superiority. May (1973), however, contended that environmentalvariability was insufficient to maintain species coexistence. May's theoryinvolved linearized Lotka-Volterra competition equations (Lotka, 1927),which required stable equilibriums for both species to coexist. Environmentalvariability was thought to disturb the numbers leading to the extinction of oneor more species.

Sale (1977) proposed a new theoretical doctrine, originating from his workon coral reef fishes, in which he argued that models of competition betweencoral reef fishes in patchy environments contain an element of randomnessreminiscent of a lottery. Because random space allocation for the individualplays a role in the processes modeled. He suggested that recruitment to a sitemay be independent of the resident fish community structure and hencecontrolled by forces outside the local system. Sale (1977) did not treat hishypothesis numerically, but suggested borrowing competitive polarityconstructs (Horn and MacArthur 1972; Slatkin 1974). Chesson and Warner

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Modeling Processes Regulating Coral Communities 203

(1981) disagreed. They asserted that random migration and random allocationof space was sufficient to describe lottery competitive systems. This wassimilar to Hutchinson's (1953) idea of environmental variability promotingcoexistence, where environmental variability is regarded spatially (at time t),not integrated over time (t, t+ 1). In other words, variability is not disturbancedriven, where high diversity is maintained by intermittent removal ofdominant species, as in Paine and Vadas (1969) and Connell (1978), butrather driven by habitat variance.

Caswell (1976) distinguished randomness from neutrality, whereby theformer is just one path to reach neutrality. Neutrality can also be achievedthrough nonrandom selection by physical forces. Caswell (1976) clearlyshowed that community patterns remain intact even when biotic interactionsare eliminated in the neutral model. In other words, neutral theory downplaysthe role of competitive interactions shaping communities-"diversity ofnatural communities may be maintained in spite of, rather than because of,such interactions" (Caswell 1976). Roughgarden (1998) concurred, reasoningthat the more species there are present in a community (of the samefunctional guide), the less connected they are, and the probability that anyone species is a keystone species is low. Along different lines but drawing thesame conclusion, Hubbell (1997, 2001) excluded competitive argumentsfrom his neutral theory of biogeography and biodiversity involvingtrophically similar species. He contended for neutrality at the individuallevel and suggested that high species diversity systems are organized simplyby equal probability of recruitment and local extinction, with mortality onlydependent on relative abundance. There is no argument that competitionexists, especially between corals on diverse coral reefs, but demonstratingcompetition and then inferring that competition drives the processes deter-mining community composition is tautological (Stone, Dayan et al. 1996).

DOES COMPETITION STRUCTURE CORALCOMMUNITIES?

Community theory emerged from arguments over the regulatory effects ofpopulation density (Gause 1934; Caswell 1982). Niche theory suggests that inorder to avoid competition in species rich environments, species must differto some degree in the way they use limiting resources. But is competitionbetween corals driving the community patterns we observe? Considerabletime and energy has been spent on competition-based research on corals oncoral reefs (Lang 1973; Buss and Jackson 1979). These studies showed thatalthough competitive interactions are often severe between coral species,there is little evidence for consistent hierarchical patterns.

Tanner et al. (1996) analyzed Connell's three-decade data set, the longestrunning monitoring program on coral reefs. They showed. through Markov orsemi-Markov transition probability matrix models (where the state distribution

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of a rnabix of transition probabilities of time t becomes dependent on thedisbibution at time t - I). that there was a lack of competitively dominantcoral taxa. The transitions were based on rates of colonization. persistence.and species replacement. They noted that all broad taxonomic groups (whichthey called species groups. and could be more appropriately called life fonDS)used in the study underwent reciprocal transitions in a single time interval.indicating the lack of a single competitively dominant coral.

A corollary is that interspecific interactions among corals may haveminimal influence on macro-scale disbibution and abundance patterns oncoral reefs and define only zonal variability (if a coral reef zone is defined asa locality on a reef at a consistent depth and exposure regime). Furthennore.since the backbone of cellular automaton models is competitive interactionsbetween and among individuals in adjacent cells. and if competitiveoutcomes are nonhierarchical. then competitive interactions between coralsin these models may be best parameterized as low. and emphasis should betoward other processes. Consequently. there is no evidence that competitiveinteractions structure local coral communities and interspecific interactionsare weak detenninants of local diversity.

CORAL COMMUNITIES-OLD AND NEW

To what extent does the taxonomic composition of a coral communityreflect the habitat and available species pool? Pandolfi and Jackson (2001)assessed 2 km of ancient. uplifted coral reefs (i.e., Pleistocene, 1.8 million to11,000 years ago) in the Caribbean for variation in coral composition. Theydemonstrated consistent variation in coral composition between environ-ments, but the composition was nonrandom within similar environments.These results suggest that species associations occur in characteristicabundance for extensive periods. Yet there has been a change in thecomparative constancy in coral community composition in the last 30 years.This sudden change has been attributed to warming oceans.

The roots of community definitions are often based on an understanding ofprocesses that have led to their formation. On the one hand, a (coral)community can be defined simply as a group of nonrandom populations of(coral) species, from some regional species pool that happens to tolerate thesame environment but where the species are not necessarily reliant on eachother nor tightly integrated as a coevolving unit (Buzas and Culver 1994;van Woesik and Done 1997). On the other hand, there may be selection ofentire communities, and the selective units are subcommunities that maintainsome degree of individuality and have heritable variation (Johnson andBoerlijst 2002). Undoubtedly, a gradient exists; other definitions are locatedsomewhere between these extreme cases.

Clearly a coral community, in any given habitat. is the net result of eachhabitat's (environmental and biological) selective forces imposing selection

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for local acclimatization that are regulated by internal constraints of species'inheritance. These characteristics are reflected in traits such as coralmorphology, growth rates, reproductive schedules, and tolerance toenvironmental parameters. From a regional and modeling perspective, coralcommunities are noticeably organized in an array of nested subsets of a muchlarger species pool, where groups of species with successively lower speciesrichness tend to be subsets of more diverse assemblages (van Woesik andDone 1997). This may be especially clear along environmental stress

gradients.To model this system, and if a community is regarded as an ensemble of

coral colonies constituting two or more species occupying a set of sites, thenthe dynamics of the number of species supported at anyone site can beexpressed as a simple differential equation, for example

(van Woesik 2000), where S is the number of species at a site, t is time, Ip isthe immigration of species already present, In is the immigration of newspecies, and E is extinction rate at that site. Clearly, the dynamics of localextinction and colonization processes control the number of species in a givencommunity, but what are the processes that select against colonies survivingat anyone region, location or habitat-or, in other words, what forces E!

FORCING FUNCTIONS

Brown (1995) states that all range boundaries are ultimately set by abioticconditions and proximate limits may be set by biotic interactions. In anygiven ocean, the number of coral species decline on a north/south (N/S) axis,from the equator, in direct correlation to sea surface temperature (SST).Fraser and Currie (1996) found that the best environmental predictor ofdiversity in the oceans was mean annual ocean temperature, which suggeststhat available energy limits regional diversity. They found little evidencesupporting other ecological scenarios, including the hypotheses thatdisturbance or environmental stability regulated diversity.

Veron and Minchin (1992) used multivariate exploratory data analysisand regression analysis techniques to examine patterns of scleractiniancoral distribution along the southern Japanese archipelago. The composi-tional data strongly reflected sea surface temperatures, with species richnessdecreasing with latitude. There was no replacement of coral species, speciessimply dropped out with increasing latitude or decreasing temperature.A caveat is that simple latitudinal correlations are irrelevant if habitatvariety is ignored. For example, the reefs around the southern Japanese

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islands of Ishigaki and lriomote, Japan, support over 350 coral species.A lagoon with numerous habitats joins these two islands. In contrast, UotsuriIsland, at the same latitude, supports only 37 species; habitats are few onUotsuri Island.

Assuming no recruitment limitation, the probability of a coral successfullyoccupying space is determined partially by relative fitness, involvingdifferential reproductive rates, partially by chance and partially by heritabletraits of environmental tolerance. Few coral species tolerate harsh environ-ments for long, even though they recruit into these harsh environments(van Woesik et al. 1999), while in benign environments few species areselected against. In this scenario, high diversity is regarded as the defaultsystem (van Woesik 2000) and the number of species supported at a site isdriven by selective mortality (while recruitment limited sites occur only onvery isolated reefs). Therefore, coral species diversity at anyone site shouldbe traceable to the environmental parameters that have forced the selectivepressures, in turn allowing each environmental variable to potentiallyrepresent an agent for natural selection.

DO DISTURBANCF$ REGULATE DIVERSITY?

Disturbances and mortality are an integral part of coral reefs and it hasbeen proposed that high diversity is maintained by intermittent removal ofdominant species through intermittent disturbance (Connell 1978). Sequentialanalysis of community structure off the west coast of Hawaii shows thatvariation of wave energy and storm frequency clearly affects communityorganization in time and space (Dollar 1982). Hunter (1993) showed that thegenotypic diversity in six populations of the endemic Hawaiian reef coral,Porites compressa, was directly related to habitat-disturbance history. Thehighest diversity, or the lowest amount of clone proliferation, was found inintensely or recently disturbed populations. In an undisturbed, protectedhabitat, lower genotypic diversity was a result of high asexual budding (i.e.,clone replication) of established genotypes.

Disturbances in a broad sense include predation effects. Acanthasterplanci is a voracious coral predator. Large aggregations of A. planci havebeen reported in 16-year cycles on the Great Barrier Reef since the 1960s(Lourey et al. 2000). It seems that A. planci populations on the Great BarrierReef become density dependent and naturally die out through starvation oncethe prey corals are eaten. In contrast, A. planci populations appear steady andchronic in the southern Japanese archipelago. Collection and eradication hasbeen aUempted only in Japan. If viewed as Lotka-Volterra equations,removal of predators, when they are in "outbreak" numbers, may havenegative impacts on corals in the long term by reducing the stable equilibriumand reducing their oscillation amplitude (Roughgarden 1998). In other words,removal of some predators may lead to a relative increase in available prey

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that subsequently sustains the predator population. While theoreticallytractable, these ideas have not been tested in the field.

In the Caribbean, Hughes (1989) showed that history played a major rolein shaping the coral communities. Similarly, in the Red Sea, Stone, Eilamet at. (1996) modeled the dynamics of corals based on field data fromYossi Loya's laboratory, which showed poor recruitment and low coralabundances. The model demonstrated high fragility in the face ofdisturbances and predicted relatively high species extinctions with mildhabitat destruction. On the Great Barrier Reef, Tanner et at. (1994) examinedcommunity succession and dynamics through analysis of Leslie projectionmatrix models using transition probabilities of "species" replacements. Theyshowed high diversity in climax communities on reef crests of Heron Island,where the study was conducted, suggesting that the "intermediate disturbancehypothesis," proposed by Connell (1978) does not necessarily apply as aregulatory process shaping these communities. They further add that recenthistory had no effect on community dynamics and structure. They illustratethat the rapid turnover of corals and algae on shallow reef crests masked theeffect of disturbance history.

Hubbell et al. (1999) also questioned the role of disturbances driving thestructure of tropical forests. They clearly showed no relationship betweendisturbance history and local species richness. They argued that disturbancesplaya relatively neutral role in maintaining species diversity and recruitmentlimitation is the principal mechanism determining local species richness oftrees (where recruitment limitation is defined as the failure of a species torecruit in all possible sites within the region that are favorable for theirsurvival and growth). However, on coral reefs most corals broadcast theirgametes into the water column, which facilitates long-distance dispersal andinterreef genetic connectivity. Therefore, most reefs show no sign ofrecruitment limitation (Hughes et al. 1999; van Woesik et al. 1999).

REEF CONNECTIVITY

While it is widely acknowledged that broadcast spawning coral speciesfonn panmictic populations on the Great Barrier Reef, and larval dispersal issufficient to maintain moderate levels of gene flow among reefs, some recentgenetic evidence shows high genetic variation among sites within reefssuggesting restricted gene flow (Ayre and Hughes 2000). Similarly, researchon darnselfish and wrasses emphasizes a high percentage of local retention ofrecruits onto natal reefs (Jones et al. 1999; Swearer et al. 1999) (on both theGreat Barrier Reef and the Caribbean).

Cowen et al. (2000) modeled the downstream advection of larvae in agroup of reefs in the Caribbean and showed mortality rate in the plankton hadbeen underestimated. Even a low mortality exponent dramatically changesthe degree of reef connectivity, suggesting that reefs are not as highly

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connected as previously thought. A study on coral-associated stomatopods(i.e., mantis shrimp) shows rare dispersal events over 400km in the Java Sea(Barber et al. 2<XX».

Over larger scales, Benzie (1999) revealed inconsistencies between geneflow patterns and present-day ocean circulation patterns across the Indian andPacific Oceans. Benzie postulated that the genetic variations of present daypopulations are the result of occasional (pulsed) dispersal events associatedwith range expansion during sea-level fluctuations (during glacial andinterglacial events). Therefore, in general terms, coral reefs are connectedover moderate distance (tens to hundreds of kilometers) over tens to hundredsof years, while genetic mixing occurs over thousands of kilometers and overthousands of years (Palumbi 1992; Benzie 1999).

POSTSETTLEMENT SURVIVAL IS DEPENDENTON HABITAT

While the supply of coral larvae and hydrodynamic connectivity betweencoral reefs is a factor regulating the dynamics of a community. coral reefs areoften saturated with recruits (van Woesik 2000). When a coral dies. a gap iscreated and a new individual takes its place. via either asexual or sexualpropagation. A recruiting coral mayor may not be the same species. Onecoral species may not necessarily disappear because of the arrival ofpresumably a more competitive coral. but because another coral species hasdisappeared or suffered a major decrease in abundance. Yet some localsettlement patterns are often influenced by coral larvae actively responding tolight (Mundy and Babcock 1998) and chemical compounds (Morse et al.1988).

Survival after settlement is dependent on physical tolerance to theprevailing conditions and resistance to interference. Indeed. the intensity oflocal extinction determines how many species a site will support and plays animportant role in structuring coral communities. van Woesik et al. (1999)showed inconsistencies between recruitment patterns and adult communitieson the Great Barrier Reef. Hughes et al. (1999) showed a similar phenomenonin a study extending along the entire Great Barrier Reef. They found similarcoral cover between regions despite a 100-fold variation in density ofrecruits. This suggests that postsettlement mortality is lower in some regions.

Bellwood and Hughes (2001) stressed that habitat availability was alsocrucial in determining large-scale biodiversity patterns on coral reefs. Theyassessed distribution patterns of scleractinian corals and fishes throughout theIndian and Pacific oceans. Five independent variables were tested againstspecies diversity in a stepwise regression model. and habitat area explainedthe highest percentage of variation. Although amassing proof that habitatavailability is important, Bellwood and Hughes (2001) only semiquantita-tively assessed habitat area (area of shallow water less than 50 m was either

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[a] greater than 20%, [b] 20% to 3%, or [c] 2% to 0%, taken at 6OOkmfrom each study site using navigational charts). Incorporating continuousindependent variables into predictive models is a more rigorous appro..-h(Peters 1991) but often ~sults in less significant outcomes. Further problemsinvolve the use of multiple data sets from diffe~nt authors. For example,Acropora, or staghom corals, are the most diverse and ubiquitous group ofcorals in the Indian and Pacific oceans. Two ~nowDed authorities haverecently written books on Acropora. Wallace (1999) described 103 Acroporaspecies, while Veron (2(xx» described 170. Variation in diversity at anyoneplace was in accordance with preferred systematic schema.

SPATIAL PA n'ERNS AND MODELS

Exploratory nonlinear multi-variate techniques have long been used tointerpret complex data sets. Recent advances by De'ath and Fabricius (2<XX»successfully used linear regression trees to tease apart large-scalebiogeographical patterns of soft coral communities. Simple linear regressionanalyses still provide useful and predictive models. van Woesik et aI. (1999)showed a strong negative relationship between coral species diversity andchlorophyll a concentrations in the water column, suggesting that a usefulpredictor of coral survival relates to water-column productivity. These data,when integrated with remote imagery (specifically SeaWiFs, which detectschlorophyll a concentrations), provide a predictive platfonn to model coralcommunity diversity over large geographic areas.

Indeed, one of the main concerns of biodiversity conservation is topredict the number of habitats, patches, or reefs a particular species isoccupying at anyone time, and whether that number is being reduced byhuman influences. We can predict the probability of occupancy using ametapopulation model, which is a population spreOO over various patcheswith a shifting balance between local extinction and colonization. Thefundamental question posed by metapopulation analyses involves the numberof habitats supporting species i, while metacommunity analyses q~tion howmany species are supported at site k. There has been considerable resurgencein metamodeling (Hanski 1998; Hanski and Ovaskainen 2<XX», with rootsstemming from studies by MacArthur and Wilson (1967), Levins (1969), andLevins and Culver (1971). Both approaches involve generic immigration andextinction exponents and emphasize the role of migration between patches orhabitats and extinction rates once established.

A general metapopulation model traces the change in the number ofoccupied habitats in a region through differential equations involving thecolonization rate minus the extinction rate of a population (Levins 1969). Anexample is

dp-;ji=mp(h-p)-ep, (2)

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where p is the fraction of habitats occupied by a species, t is time, m is thecolonization rate (or the rate, or probability, at which a species from anoccupied habitat sends a colonist to an unoccupied habitat), h is the numberof suitable habitats or patches, and e is the extinction rate (or probability thata species becomes locally extinct in a given area). Therefore, dp / dt is thederivative of p with respect to t and informs us of the change in the fractionof habitats occupied by, say, a coral over time. Roughgarden (1998) redefinedthe metapopulation model as

where p, m, h, and e are as already defined. Irrespective of modelpreference, it is obvious that the probabilities of m (sending out recruits)and e (extinction) are driving both models, and the extent of habitatoccupancy can be positively related to variability in rate of establishment(recruitment) and extinction (or p = I - t5/h, where t5 is the ratio of extinctionand colonization rates). Low extinction rates and high probabilities ofsending out recruits have a positive feedback effect, driving up abundancelevels.

There are, however, some problems with the generic nature of m and e.For example, each site may have a slightly different rate of local extinctionthat varies in accordance with the environmental conditions at each site, orcolonization (m) may be dependent on distance to an important site thatsupplies the majority of coral recruits. In other words, metapopulationmodels, due to their generic nature, cannot be used to analyze spatiallyexplicit patterns.

Hanski and Ovaskainen (2000) resolve this issue by deriving the "meta-population capacity" concept. which is the ranking of different landscapes interms of their potential to support a given species. While h in the models justdescribed assumes spatial similarity in patches, Hanski and Ovaskainen(2000) introduce AM in its place. This is the leading eigenvalue of anappropriate landscape matrix that incorporates landscape structure, whichderives a weighted average of p. Incorporated into the extinction andcolonization equation is area of patch. The colonization equation includes anegative exponential relating to distance between patches and averagemigration distance. Conceivably, AM increases with decreasing distancebetween patches (i.e., when connectivity between patches is high). Thisapproach combines metapopulation theory with landscape ecology into apractical framework. While the former has a strong theoretical framework,the parameters are generic and often region-specific criteria are lost. whereasthe latter is based on real-world phenomenon but lacks a theoreticalframework.

R. van Woesik

dp'dt = (mh - e){l - p/[(mh - e)/mJ}p, {1)

CONCLUSIONS AND FUTURE DIRECTIONS

I have argued that coral reefs do not appear to be recruitment limited, andhabitats supporting diverse corals are not a direct function of differentialcompetitive abilities of corals, nor are they driven by the intensity andfrequency of disturbance. Instead, high-diversity habitats are the "defaultsystem," and low-diversity habitats are merely the outcome of differentialmortality driven by environmental variables. This argument concurs withneutral theory constructs (Caswell 1976; Hubbell 1997,2001). and researchemphasis should be directed away from competition and intermediatedisturbance type studies believed to equilibrate high-diversity coralcommunities.

Juxtaposed on this theme is the increase of human pressure on coral reefsystems. for example. via land-use changes and river discharge. Modelingland-use changes and associated river discharge effects on coral reefs ispertinent and infrequently attempted, in part because of the scale of theproblem (West and van Woesik 2001). Indeed, the scale at which to addressan issue is still the central problem in coral reef ecology (Levin 1992). It isalso conceivable that coral reef modeling may broaden the path opened byHanski and Ovaskainen (2000) by amalgamating landscape structure matricesand transition probability matrices within the metapopulation framework.

However. taking a dynamic transition matrix approach requires a changein emphasis on the way data is collected on coral reefs. Considerable timeand money is being spent on collecting data on percentage cover of variousreef taxa, which tell us little about the ecological relevance of the organismson the reefs. even less about their life history and their relative fitness. andconsiderably less about the future direction of the populations. Data on coralcolony size and spatial abundance are invariably more informative thanestimates of percentage coral cover.

We have little understanding of processes generating differential relativeabundance. For instance, it is unknown whether differential mortality of coralrecruits is driven by innate differences in species tolerance or whetherrelative abundance is a consequence of initial number of recruits settling (i.e.,implicit in the latter is equal probability of mortality). For example. rarecorals. such as Acropora lovelli. propagate fewer offspring than commoncorals. such as Acropora digitifera or Acropora nasuta in the PacificOcean. resulting in relatively low survival of the former. Whether relativeabundance is directly related to habitat tolerance at different life-historystages requires testing to attain a more solid consensus of processesstructuring coral communities.

Clearly. human pressures are causing relative shifts in coral speciesabundance. which vary in accordance with regional setting. The extent of theshifts is also dependent on the composition and abundance of the resident

Modeling Processes Regulating Coral Communities 211

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coral populations. the degree of reef connectivity. the environmental setting,and the frequency and intensity of the (human) pressure. Modeling theseprocesses is pertinent in light of global wanning and rising sea surfacetemperatures because the models encourage implementation of appropriatepolicies and management strategies that can ameliorate adverse effects.

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