Ecological Archives A21-064-A1

Jessica Melbourne-Thomas, Craig R. Johnson, Tak Fung, Robert M. Seymour, Laurent M. Chérubin, J. Ernesto Arias-González, and Elizabeth A. Fulton. 2011. Regional-scale scenario modeling for coral reefs: a decision support tool to inform management of a complex system. Ecological Applications 21:1380–1398.

Appendix A. The local-scale ecological model.

The regional-scale Coral Reef Scenario Evaluation Tool (CORSET) we describe and evaluate comprises multiple instantiations of a local-scale mean-field model of ecological dynamics (Fung 2009) that are connected by larval transport (Fig. 1 in main text). The local model is defined by seven differential equations which have been parameterized using available data for shallow coral reef habitats (~ 5 m – 20 m depth). In the CORSET implementation of the local-scale model, we distinguish between brooding and spawning corals, so that the model system comprises eight differential equations (Equations A.1 – A.8). CORSET uses discrete-time (difference equations) approximations of these differential equations, which were derived using Euler’s method. Details of the model development and clarification of assumptions are provided below. Mathematical analyses of the behavior of the local model and derivations of generic parameter ranges that apply to reefs worldwide are available in Fung (2009). The parameter ranges used in this paper, which apply to the western Atlantic (Table A1), are derived using the same approach as in Fung (2009).

Local-scale model development and assumptions

Benthic variables followed in the CORSET implementation of the local-scale model are the proportional covers of brooding corals (Cb), spawning corals (Cs), hard corals (C = Cb + Cs), macroturf (T), macroalgae (M) and grazed epilithic algal communities or EAC (E = 1 – CbCsTM). These proportional covers can be converted into percentage covers, as in the main text. The model represents key ecological processes that determine competition for space between corals, macroturf, macroalgae and grazed EAC. Other sessile organisms are not modeled and are assumed to have non-significant effects on coral-algal dynamics, and to take up a relatively small constant component of the benthos on average. The dynamics of brooding and spawning coral are modeled identically except for recruitment dynamics, as detailed in the main text (brooded coral larvae are assumed to settle locally while spawned larvae disperse in the plankton).

Corals experience background mortality that may be enhanced by human activities such as coastal development. Coral larvae may settle onto grazed EAC or macroturf (Birrell et al. 2005, Birrell et al. 2008), but the settlement rate onto macroturf is lower than the rate onto grazed EAC (Birrell et al. 2005). Settlement of coral larvae onto macroalgae is assumed to be non-significant (Nugues and Szmant 2006, Birrell et al. 2008). Corals can grow laterally over grazed EAC (which is assumed not to impede the growth of corals) and over macroturf (either through competitive superiority or shading and overgrowth by branching corals; McCook et al. 2001). The growth of macroturf is predominantly vertical, and hence there is no lateral growth of macroturf over grazed EAC. However, if EAC is left ungrazed then it grows into macroturf at a fixed rate. There is no overgrowth of corals by macroturf (based on findings from Jompa and McCook 2002, Jompa and McCook 2003, Birrell et al. 2008).

The local-scale model includes a term that represents overgrowth of corals by macroalgae (based on evidence from De Ruyter van Steveninck et al. 1988, McCook et al. 2001, and Jompa and McCook 2002), but this can be set to zero for cases where macroalgae are not competitively superior to corals (e.g. Nugues and Bak 2006). The growth rate of macroalgae over corals is less than that over grazed EAC, based on evidence that corals can reduce the growth rate of macroalgae at the coral-algal interaction fringe (De Ruyter van Steveninck et al. 1988, Jompa and McCook 2002). The model also includes a term that represents a reduction of coral growth rates over grazed EAC and macroturf due to the presence of nearby macroalgae (Lirman 2001, Jompa and McCook 2002). Macroturf recruitment is not modeled explicitly; instead, it is assumed that macroturf grow readily from grazed EAC because of basal portions that remain after grazing and/or because of a ready supply of macroturf propagules from the reef environment (Hay 1991, Diaz-Pulido and McCook 2002). Macroalgal recruitment is not modeled due to a lack of knowledge of supply-side dynamics (McCook 1999, Diaz-Pulido and McCook 2004). Similarly, background mortality of algal groups (macroalgae and macroturf) is not modeled because of a lack of available information regarding these dynamics on coral reefs. Thus, the main sources of mortality for macroturf are assumed to be grazing (the trophic flux from algae to herbivores is one of the largest on coral reefs, McCook 1999) and overgrowth by macroalgae (Mumby et al. 2006) and corals. The main source of mortality for macroalgae is assumed to be grazing (McCook 1999).

Consumer variables followed in the local-scale model are the biomasses of herbivorous fish (H), small-to-intermediate piscivorous fish (Ps), large piscivorous fish (Pl) and sea urchins (U). The process of growth is modeled differently for herbivorous fish and piscivorous fish.  Herbivorous fish grow by consuming macroturf and macroalgae (the grazing rate on macroalgae can be lower than on macroturf since macroalgae can be chemically defended against grazing by secondary metabolites; Hay 1991). The realized grazing pressure exerted by herbivorous fish (see Equation A.3b) determines the amount of available algal cover which is consumed and converted into energy (which is used for growth).  Realized grazing pressure depends on the accessibility of the algal food source to herbivorous fish, where accessibility is a proxy for foraging ability and reef rugosity. At high rugosity, more individuals per unit planar area are needed to achieve a given grazing pressure, due to the greater benthic surface area per unit planar area (i.e. algal resources are effectively less accessible). The realized grazing pressure for fish also includes exploitative competition from herbivorous sea urchins (Hay 1984, Carpenter 1990). Somatic conversion rates for herbivorous fish grazing on macroalgae, macroturf and EAC are assumed to be equal given a lack of information on relative rates at which the different types of modeled algal covers are converted by grazers into somatic biomass.

Piscivorous fish grow by consuming herbivorous fish and smaller piscivorous fish. In the local-scale model, the growth rate of piscivorous fish is a function of prey biomass and is assumed to follow a Holling Type-III response with an exponent of two. The Holling Type-III response means that at low and high prey biomasses the rate of increase of the realized growth rate is slow. At low prey biomasses this reflects the difficulty of prey capture due to low encounter rates, while at high prey biomasses the Type-III functional response reflects prey saturation, such that predation (and therefore growth) is no longer significantly limited by the availability of prey. The model assumes that a certain proportion of small-to-intermediate piscivorous fish transition to the large piscivorous fish functional group at each timestep, due to growth.

All fish groups suffer morality due to fishing, predation, and natural processes excluding predation (such as senescence). Fishing decreases the fish biomass of each group through time and the amount of fish caught depends on fishing pressure, the standing stock fish biomass and the accessibility of each type of fish to fishermen (Kramer 2007). Fishing pressure is represented as the maximum fish biomass which can be caught, and is related to the number of fishing hours and the technology (type of fishing gear) used. Accessibility is a proxy for the technology used and the structural complexity of the coral reef habitat.

Sea urchins, like herbivorous fish, grow by consuming macroturf and macroalgae. The available algal cover grazed is determined by the realized grazing pressure exerted by sea urchins (see Eq. A.3c), which includes exploitative competition from herbivorous fish (Hay 1984, Carpenter 1990). It is assumed as a simplification that growth accumulation parameters for sea urchins are proportional to those for herbivorous fish. For sea urchins, mortality occurs due to predation by invertivorous fish (not modeled explicitly) and other natural processes.

Local-scale model equations and parameters

The change in proportional cover of brooding corals () is given by


where all parameters (, ,  etc.) are defined in Table A1, as are all parameters used in the following equations. Similarly, for the proportional cover of spawning corals ()


and macroturf ()


where q  is the grazing term given by


Grazing by herbivorous fish () and sea urchins () is scaled by competition between these two groups such that


The change in proportional cover of macroalgae () is given by


and in the biomass of herbivorous fish () by


Here, ‘other mortality’ refers to mortality from processes other than predation and fishing. Similarly for the biomass of small-to-intermediate piscivorous fish ()


large piscivorous fish ()


and sea urchins ()


TABLE A1. Local model parameter definitions and values derived for the western Atlantic. Parameter values are derived using the same parameterization methodology as detailed in Fung (2009). Where possible, parameters were derived using data just from the western Atlantic. In cases where western Atlantic data were not available, data were taken from the Indo-Pacific region. Mathematically derived parameter restrictions detailed in the footnotes are required to keep state variables within a realistic biological range, i.e., in the range 0 – 1 for benthic covers, and ≥ 0 (but not tending to infinity) for consumer biomasses (see Fung 2009 for detailed derivations).



Derived value(s)


Benthic Parameters

The background mortality rate of brooding and spawning corals.

0.02 – 0.1 yr-1

1, 2, 3

The growth rate of existing coral over grazed EAC.

0.04 – 0.2 yr-1

4, 5, 6, 7, 8

The growth rate of coral over macroturf, relative to its growth over grazed EAC.

0 – 1


The recruitment rate of coral onto macroturf, relative to the rate onto grazed EAC.

0.05 – 0.15



The recruitment rates of brooding and spawning corals.

Modeled externally to the local model


The maximum rate (per unit of grazing pressure) at which existing macroturf is grazed down.

5 – 15 yr-1

10, 11

The rate at which grazed EAC grows into macroturf.

2 – 20 yr-1

11, 12

The maximum rate (per unit of grazing pressure) at which existing macroalgae is grazed down.


10, 11, 13, 14, 15

The growth rate of macroalgae over grazed EAC.

0.05 – 0.4 yr-1


Coral growth is inhibited by the presence of nearby macroalgae and this is represented as depression of  by the factor .

0.4 – 0.9 yr-1

4, 5, 6, 7, 8, 17, 18

The growth rate of macroalgae over coral, relative to its growth over grazed EAC.

0 – 0.9

4, 8, 16, 17, 19

The growth rate of macroalgae over macroturf, relative to its growth over grazed EAC.

0 – 0.9

4, 8, 16, 17, 19

Consumer parameters

A parameter that measures the accessibility of algae (turf and macroalgae) to herbivorous fish grazing.

3 × 103 – 5 × 105 kg/km2

16, 20, 21, 22, 23

A parameter that measures the accessibility of herbivorous fish to predation by piscivorous fish.

7 × 103 – 1 × 104 kg/km2

8, 20, 24–40

A parameter that measures the accessibility of herbivorous fish to fishermen.

7 × 102 – 1 × 103 kg/km2

8, 20, 24–40

The mortality rate of herbivorous fish from all factors other than predation by piscivorous fish and fishing.

 – 2 yr-1



The herbivorous fish biomass accumulated from grazing on 100% cover of macroalgae, macroturf and EAC respectively, and which contributes to somatic growth of herbivorous fish.

60 –  kg km-2 yr-1

30, 31, 42, 43, 44

The proportion of the total fishing pressure which acts on herbivorous fish.

0 – 1, with



The recruitment rate of herbivorous fish.

Modeled externally to the local model


A parameter that measures the accessibility of small-to-intermediate piscivorous fish to predation by large piscivorous fish.

7 × 103 – 1 × 104 kg/km2

8, 20, 24–40

A parameter that measures the accessibility of small-to-intermediate piscivorous fish to fishermen.

7 × 102 – 1 × 103 kg/km2

8, 20, 24–40

The mortality rate of small-to-intermediate piscivorous fish from all factors other than predation and fishing.

– 2 yr-1


The maximum predation rate of small-to-intermediate piscivorous fish on herbivorous fish.

1 – 2 yr-1


The proportion of consumed biomass which is used for somatic growth, for small-to-intermediate piscivorous fish.

0.035 – 0.105

31, 43, 44

A parameter which measures the rate at which small-to-intermediate piscivorous fish biomass becomes large piscivorous fish biomass due to predation and subsequent growth.

0 – 10


The proportion of the total fishing pressure which acts on small-to-intermediate piscivorous fish.

0 – 1, with



The recruitment rate of small piscivorous fish.

Modeled externally to the local model


A parameter that measures the accessibility of large piscivorous fish to fishermen.

7 × 102 – 1 × 103 kg/km2

8, 20, 24–40

The mortality rate of large piscivorous fish from all factors other than predation and fishing.

– 0.9 yr-1


The maximum predation rate of large piscivorous fish on herbivorous fish.

0.25 – 0.75 yr-1


The proportion of consumed biomass which is used for somatic growth, for large piscivorous fish.

0.03 – 0.09

31, 43, 44

The predation rate on small-to-intermediate piscivorous fish by large piscivorous fish, relative to that on herbivorous fish.

2 – 4


The proportion of the total fishing pressure which acts on large piscivorous fish.

0 – 1, with



The maximum fish biomass which can be caught.

0 – 5 × 103 kg km-2 yr-1

45, 46, 47, 48

The linear mortality rate of urchins.

– 1 yr-1

49, 50, 51


The quadratic mortality rate of urchins.

1 × 10-6 yr-1



A parameter that measures the accessibility of algae (turf and macroalgae) to urchin grazing.

 – 3 × 106 kg/km2

16, 21, 22, 23, 52

A parameter that measures the biomass accumulated by urchin grazing and which contributes to somatic growth relative to that for herbivorous fish grazing.

1 – 10

31, 43, 44, 50, 53


The recruitment rate of urchins.

Modeled externally to the local model


A parameter that determines the competitiveness of herbivorous fish relative to urchins.

0.6 – 1


A parameter that determines the competitiveness of urchins relative to herbivorous fish.

Equal to


* Sources: 1Bythell et al. (1993), 2Lirman (2003), 3Nugues and Roberts (2003), 4Edmunds (2007), 5Langmead and Sheppard (2004), 6Huston (1985), 7Chornesky and Peters (1987), 8García-Salgado et al. (2006), 9Birrell et al. (2005), 10Hughes et al. (2007), 11Mumby et al. (2006), 12McClanahan (2002), 13Bellwood et al. (2006), 14Russ and St. John (1988), 15Hay (1991), 16Mumby et al. (2005), 17Lirman (2001), 18Box and Mumby (2007), 19Nugues and Bak (2006), 20Williams et al. (2001), 21Ostrander et al. (2000), 22Edmunds (2002), 23Miller and Gerstner (2002), 24Sandin et al. (2008), 25Mumby and Dytham (2006), 26Williams and Hatcher (1983), 27Letourneur et al. (1998), 28McClanahan et al. (1996), 29Arias-González et al. (1997), 30Arias-González (1998), 31Van Rooij et al. (1998), 32Friedlander and DeMartini (2002), 33Gribble (2003), 34Kramer (2003), 35Arias-González and Morand (2006), 36Newman et al. (2006), 37Craig et al. (2008), 38Tsehaye and Nagelkerke (2008), 39Aliño et al. (1993), 40McClanahan et al. (1999), 41Froese and Pauly (2004), 42Gardner et al. (2003), 43Johnson et al. (1995), 44Opitz (1996), 45Stevenson and Marshall (1974), 46Koslow et al. (1994), 47Halls et al. (Halls et al. 2002), 48Arias-González et al. (2004), 49Karlson and Levitan (1990), 50Levitan (1989), 51Ebert (1975), 52Carpenter (1986), 53Levitan (1988), 54Hay (1984).

П Recruitment terms () are modeled externally to the local model, based on matrices defining connectivity between reef cells as detailed in the main text. Parameters used for modeling larval production and post-settlement processes are detailed in Appendix B.

. Here, .

§ , where .



¥ Estimated values for  presented in Table A1 are based on published values for the western Atlantic. In the two scenarios presented in our study,  was zero or varied over time.


Δ Quadratic mortality of sea urchins, , is included in the regional implementation of the local ecological model to prevent uncontrolled population explosions in this functional group. This term is a proxy for consumption of sea urchins by fish and invertebrate predators (Randall et al. 1964, Harborne et al. 2009).



Aliño, P. M., L. T. McManus, J. W. McManus, C. L. Nañola, M. D. Fortes, G. C. Trono, and G. S. Jacinto. 1993. Initial parameter estimations of a coral reef flat ecosystem in Bolinao, Pangasinan, northwestern Philippines. Pages 252–258 in D. Pauly and V. Christensen, editors. Trophic Models of Aquatic Ecosystems. ICLARM Conference Proceedings 26. The WorldFish Center, Penang.

Arias-González, J. E. 1998. Trophic models of protected and unprotected coral reef ecosystems in the south of the Mexican Caribbean. Journal Of Fish Biology 53:236–255.

Arias-González, J. E., B. Delesalle, B. Salvat, and R. Galzin. 1997. Trophic functioning of the Tiahura reef sector, Moorea Island, French Polynesia. Coral Reefs 16:231–246.

Arias-González, J. E., and S. Morand. 2006. Trophic functioning with parasites: a new insight for ecosystem analysis. Marine Ecology Progress Series 320:43–53.

Arias-González, J. E., E. Nuñez-Lara, C. González-Salas, and R. Galzin. 2004. Trophic models for investigation of fishing effect on coral reef ecosystems. Ecological Modelling 172:197–212.

Bellwood, D. R., T. P. Hughes, and A. S. Hoey. 2006. Sleeping functional group drives coral reef recovery. Current Biology 16:2434–2439.

Birrell, C. L., L. J. McCook, and B. L. Willis. 2005. Effects of algal turfs and sediment on coral settlement. Marine Pollution Bulletin 51:408–414.

Birrell, C. L., L. J. McCook, B. L. Willis, and G. A. Diaz-Pulido. 2008. Effects of benthic algae on the replenishment of corals and the implications for the resilience of coral reefs. Oceanography and Marine Biology: an annual review 46:25–63.

Box, S. J., and P. J. Mumby. 2007. Effect of macroalgal competition on growth and survival of juvenile Caribbean corals. Marine Ecology Progress Series 342:139–149.

Bythell, J. C., E. H. Gladfelter, and M. Bythell. 1993. Chronic and catastrophic natural mortality of three common Caribbean reef corals. Coral Reefs 12:143–152.

Carpenter, R. C. 1986. Partitioning herbivory and its effects on coral-reef algal communities. Ecological Monographs 56:345–363.

Carpenter, R. C. 1990. Mass mortality of Diadema antillarum 2. Effects on population densities and grazing intensity of parrotfishes and surgeonfishes. Marine Biology 104:79–86.

Chornesky, E. A., and E. C. Peters. 1987. Sexual reproduction and colony growth in the scleractinian coral Porites astreoides. Biological Bulletin 172:161–177.

Craig, P., A. Green, and F. Tuilagi. 2008. Subsistence harvest of coral reef resources in the outer islands of American Samoa: modern, historic and prehistoric catches. Fisheries Research 89:230–240.

De Ruyter van Steveninck, E. D., L. L. Vanmulekom, and A. M. Breeman. 1988. Growth-inhibition of Lobophora variegata (Lamouroux) Womersley by scleractinian corals. Journal of Experimental Marine Biology and Ecology 115:169–178.

Diaz-Pulido, G., and L. J. McCook. 2002. The fate of bleached corals: patterns and dynamics of algal recruitment. Marine Ecology Progress Series 232:115–128.

Diaz-Pulido, G., and L. J. McCook. 2004. Effects of live coral, epilithic algal communities and substrate type on algal recruitment. Coral Reefs 23:225–233.

Ebert, T. A. 1975. Growth and mortality of post-larval Echinoids. American Zoologist 15:755–775.

Edmunds, P. J. 2002. Long-term dynamics of coral reefs in St. John, US Virgin Islands. Coral Reefs 21:357–367.

Edmunds, P. J. 2007. Evidence for a decadal-scale decline in the growth rates of juvenile scleractinian corals. Marine Ecology Progress Series 341:1–13.

Friedlander, A. M., and E. E. DeMartini. 2002. Contrasts in density, size, and biomass of reef fishes between the northwestern and the main Hawaiian islands: the effects of fishing down apex predators. Marine Ecology Progress Series 230:253–264.

Froese, R., and D. Pauly. Editors. 2004. FishBase. World Wide Web electronic publication.Version (10/2008), available online at:

Fung, T. C. 2009. Local scale models of coral reef ecosystems for scenario testing and decision support. PhD Thesis in Modelling Biological Complexity. University College London, London, UK. Available online at

García-Salgado, M. A., T. L. Camarena, M. G. Vasquez, Gold B., G. G. Galland, Nava M., G. D. Alarcón, and V. M. Ceja. 2006. Baseline of the Status of the Mesoamerican Barrier Reef Systems: Results of Synoptic Monitoring from 2004 and 2005, Volume 1. Project for the conservation and sustainable use of the Meso-American Barrier Reef System (MBRS), Project Coordinating Unit, Belize – Guatemala – Honduras – Mexico, Belize City.

Gardner, T. A., I. M. Cote, J. A. Gill, A. Grant, and A. R. Watkinson. 2003. Long-term region-wide declines in Caribbean corals. Science 301:958–960.

Gribble, N. A. 2003. GBR-prawn: modelling ecosystem impacts of changes in fisheries management of the commercial prawn (shrimp) trawl fishery in the far northern Great Barrier Reef. Fisheries Research 65:493–506.

Halls, A. S., R. W. Burn, and S. Abeyasekera. 2002. Interdisciplinary Analysis for Adaptive Co-Management Final Technical Report. Fisheries Management Science Programme, London, UK.

Harborne, A., P. Renaud, E. Tyler, and P. Mumby. 2009. Reduced density of the herbivorous urchin Diadema antillarum inside a Caribbean marine reserve linked to increased predation pressure by fishes. Coral Reefs 28:783–791.

Hay, M. E. 1984. Patterns of fish and urchin grazing on Caribbean coral reefs - are previous results typical? Ecology 65:446–454.

Hay, M. E. 1991. Fish-seaweed interactions on coral reefs: effects of herbivorous fishes and adaptations of their prey. Pages 96–119 in P. F. Sale, editor. The Ecology of Fishes on Coral Reefs. Academic Press, San Diego, California, USA.

Hughes, T. P., M. J. Rodrigues, D. R. Bellwood, D. Ceccarelli, O. Hoegh-Guldberg, L. McCook, N. Moltschaniwskyj, M. S. Pratchett, R. S. Steneck, and B. Willis. 2007. Phase shifts, herbivory, and the resilience of coral reefs to climate change. Current Biology 17:360–365.

Huston, M. 1985. Variation in coral growth rates with depth at Discovery Bay, Jamaica. Coral Reefs 4:19–25.

Johnson, C., D. Klumpp, J. Field, and R. Bradbury. 1995. Carbon flux on coral reefs - effects of large shifts in community structure. Marine Ecology Progress Series 126:123–143.

Jompa, J., and L. J. McCook. 2002. Effects of competition and herbivory on interactions between a hard coral and a brown alga. Journal of Experimental Marine Biology and Ecology 271:25–39.

Jompa, J., and L. J. McCook. 2003. Contrasting effects of turf algae on corals: massive Porites spp. are unaffected by mixed-species turfs, but killed by the red alga Anotrichium tenue. Marine Ecology Progress Series 258:79–86.

Karlson, R. H., and D. R. Levitan. 1990. Recruitment-limitation in open populations of Diadema antillarum - an evaluation. Oecologia 82:40–44.

Koslow, J. A., K. Aiken, S. Auil, and A. Clementson. 1994. Catch and effort analysis of the reef fisheries of Jamaica and Belize. Fishery Bulletin 92:737–747.

Kramer, D. B. 2007. Adaptive harvesting in a multiple-species coral-reef food web. Ecology and Society 13:17.

Kramer, P. A. 2003. Synthesis of coral reef health indicators for the Western Atlantic: results of the AGRRA program. Atoll Research Bulletin 496:1–58.

Langmead, O., and C. Sheppard. 2004. Coral reef community dynamics and disturbance: a simulation model. Ecological Modelling 175:271–290.

Letourneur, Y., M. Kulbicki, and P. Labrosse. 1998. Spatial structure of commercial reef fish communities along a terrestrial runoff gradient in the northern lagoon of New Caledonia. Environmental Biology of Fishes 51:141–159.

Levitan, D. R. 1988. Algal urchin biomass responses following mass mortality of Diadema antillarum Philippi at Saint John, United States Virgin Islands. Journal of Experimental Marine Biology and Ecology 119:167–178.

Levitan, D. R. 1989. Density-dependent size regulation in Diadema antillarum: effects on fecundity and survivorship. Ecology 70:1414–1424.

Lirman, D. 2001. Competition between macroalgae and corals: effects of herbivore exclusion and increased algal biomass on coral survivorship and growth. Coral Reefs 19:392–399.

Lirman, D. 2003. A simulation model of the population dynamics of the branching coral Acropora palmata: effects of storm intensity and frequency. Ecological Modelling 161:169–182.

McClanahan, T. R. 2002. The near future of coral reefs. Environmental Conservation 29:460–483.

McClanahan, T. R., A. T. Kamukuru, N. A. Muthiga, M. G. Yebio, and D. Obura. 1996. Effect of sea urchin reductions on algae, coral, and fish populations. Conservation Biology 10:136–154.

McClanahan, T. R., N. A. Muthiga, A. T. Kamukuru, H. Machano, and R. W. Kiambo. 1999. The effects of marine parks and fishing on coral reefs of northern Tanzania. Biological Conservation 89:161–182.

McCook, L. J. 1999. Macroalgae, nutrients and phase shifts on coral reefs: scientific issues and management consequences for the Great Barrier Reef. Coral Reefs 18:357–367.

McCook, L. J., J. Jompa, and G. Diaz-Pulido. 2001. Competition between corals and algae on coral reefs: a review of evidence and mechanisms. Coral Reefs 19:400–417.

Miller, M. W., and C. L. Gerstner. 2002. Reefs of an uninhabited Caribbean island: fishes, benthic habitat, and opportunities to discern reef fishery impact. Biological Conservation 106:37–44.

Mumby, P. J., and C. Dytham. 2006. Metapopulation dynamics of hard corals. Pages 157–203 in J. P. Kritzer and P. F. Sale, editors. Marine Metapopulations. Elsevier, London, UK.

Mumby, P. J., N. L. Foster, and E. A. G. Fahy. 2005. Patch dynamics of coral reef macroalgae under chronic and acute disturbance. Coral Reefs 24:681–692.

Mumby, P. J., J. D. Hedley, K. Zychaluk, A. R. Harborne, and P. G. Blackwell. 2006. Revisiting the catastrophic die-off of the urchin Diadema antillarum on Caribbean coral reefs: fresh insights on resilience from a simulation model. Ecological Modelling 196:131–148.

Newman, M. J. H., G. A. Paredes, E. Sala, and J. B. C. Jackson. 2006. Structure of Caribbean coral reef communities across a large gradient of fish biomass. Ecology Letters 9:1216–1227.

Nugues, M., and A. Szmant. 2006. Coral settlement onto Halimeda opuntia: a fatal attraction to an ephemeral substrate? Coral Reefs 25:585–591.

Nugues, M. M., and R. P. M. Bak. 2006. Differential competitive abilities between Caribbean coral species and a brown alga: a year of experiments and a long-term perspective. Marine Ecology Progress Series 315:75–86.

Nugues, M. M., and C. M. Roberts. 2003. Coral mortality and interaction with algae in relation to sedimentation. Coral Reefs 22:507–516.

Opitz, S. 1996. Trophic interactions in Caribbean coral reefs. International Center for Living Aquatic Resources Management Technical Report 43. ICLARM, Makati City.

Ostrander, G. K., K. M. Armstrong, E. T. Knobbe, D. Gerace, and E. P. Scully. 2000. Rapid transition in the structure of a coral reef community: the effects of coral bleaching and physical disturbance. Proceedings of the National Academy of Sciences (USA) 97:5297–5302.

Randall, J. E., R. E. Schroeder, and W. A. Starck. 1964. Notes on the biology of the echinoid Diadema antillarum. Caribbean Journal of Science 4:421–433.

Russ, G. R., and J. St. John. 1988. Diets, growth rates and secondary production of herbivorous coral reef fishes. Pages 37–43 in Proceedings of the 6th International Coral Reef Symposium. 6th International Coral Reef Symposium Executive Committee, Townsville, Australia.

Sandin, S. A., J. E. Smith, E. E. DeMartini, E. A. Dinsdale, S. D. Donner, A. M. Friedlander, T. Konotchick, M. Malay, J. E. Maragos, D. Obura, O. Pantos, G. Paulay, M. Richie, F. Rohwer, R. E. Schroeder, S. Walsh, J. B. C. Jackson, N. Knowlton, and E. Sala. 2008. Baselines and degradation of coral reefs in the Northern Line Islands. PLoS ONE 3:e1548.

Stevenson, D. K., and N. Marshall. 1974. Generalisations on the fisheries potential of coral reefs and adjacent shallow water environments. Pages 147–158 in Proceedings of the 2nd International Coral Reef Symposium. The Great Barrier Reef Committee, Brisbane, Australia.

Tsehaye, Y., and L. A. J. Nagelkerke. 2008. Exploring optimal fishing scenarios for the multispecies artisanal fisheries of Eritrea using a trophic model. Ecological Modelling 212:319–333.

Van Rooij, J. M. 1998. High biomass and production but low energy transfer efficiency of Caribbean parrotfish: implications for trophic models of coral reefs. Journal Of Fish Biology 53.

Williams, D. M., and A. I. Hatcher. 1983. Structure of fish communities on outer slopes of inshore, mid-shelf and outer shelf reefs of the Great Barrier Reef. Marine Ecology Progress Series 10:239–250.

Williams, I. D., N. V. C. Polunin, and V. J. Hendrick. 2001. Limits to grazing by herbivorous fishes and the impact of low coral cover on macroalgal abundance on a coral reef in Belize. Marine Ecology Progress Series 222.

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