Multivariate Analysis of Reef Community Structure in the Belize Barrier Reef Complex

BULLETIN OF MARINE SCIENCE, 69(2): 745–758, 2001

MULTIVARIATE ANALYSIS OF REEF COMMUNITY STRUCTURE IN THE BELIZE BARRIER REEF COMPLEX

M. D. McField, P. Hallock and W. C. Jaap

ABSTRACT The Belize barrier reef complex includes approximately 250 km of barrier reef and three off-shelf atolls up to 40 km east of the barrier reef. Multivariate analysis techniques are being tested for their ability to discriminate patterns of geographical zonation in reef community structure. A stratified, haphazard video-based monitoring scheme has been established at 17 windward fore-reef sites. This preliminary community classification and ordination provides a baseline description of reef communities and indicates a significant difference (1) between atoll versus barrier reef sites, and (2) between southern, northern and central barrier reef sites, despite a relatively high degree of similarity. Two pairs of sites indicate there are significant differences in community structure between ‘impacted’ and ‘non-impacted’ sites. In addition, the key taxa responsible for these differences (based on the Bray-Curtis similarity matrix) were identified and include Agaricia tenuifolia and macro algae. Most previous studies have examined stony coral species in such analyses. Because non-coral biota are normally the major community components on Caribbean reefs, they should be included in multivariate analyses of reef communities. Reanalysis of these data using either major benthic substrate categories or only stony coral species produces less discriminating results and illustrates the importance of using a community approach with as much taxonomic detail as possible. Understanding the underlying similarities and differences in biological communities throughout this large reef area is the first step towards the goal of linking these patterns to environmental and management-linked influences.

The Belize reef system includes the largest barrier reef in the Western Hemisphere (approximately 250 km), three well developed off-shelf atolls, numerous inner patch reefs and unusual rhomboid shaped reefs (faroes). While there have been major studies of the geology and morphology of Belize’s reefs and sediments (Stoddart, 1962; Stoddart 1963; and others), they have not provided a quantitative measure of reef community structure. Burke (1979) described seven transects from Gallows Point Reef to Queen Cayes (near Pompion Caye, see Fig. 1), recording bottom proﬁles, zonation of substrates and organisms, but giving few qualitative and no quantitative visual estimates of benthic community cover. Detailed taxonomic descriptions of reef biota and qualitative descriptions of reefs have been made near the Smithsonian Institution’s research station at Carrie Bow Cay (Rutzler and Macintyre, 1982). Aronson et al. (1994) and Aronson and Precht (1997) have also recorded quantitative community descriptions in the vicinity of Carrie Bow Caye. There have also been quantitative community descriptions in the vicinity of Wild- life Conservation Society’s research station on Glovers Reef Atoll (McClanahan and Muthiga, 1998) but little is published about the remainder (~90%) of the reef complex. An integrated coastal zone management program was initiated in 1991, which includes numerous measures aimed at coral reef conservation (Gibson et. al., 1998). Establish- ment of a long-term coral monitoring program is critical to the evaluation of these management efforts and the health of the Belize reef system (McField et al., 1996). Our study represents the ﬁrst reef-wide, quantitative description of reef community structure throughout the Belize Barrier Reef Complex (Fig. 1). The database created through this project,

745 746 BULLETIN OF MARINE SCIENCE, VOL. 69, NO. 2, 2001 including archived CD-ROM images, will serve as a baseline for future monitoring efforts. These data can be requested through the first author or through the Coastal Zone Management Institute, P.O. Box 1884, Belize City, Belize, Central America. Although numerous scientific investigations have been conducted in Belize, most have been isolated studies, with little continuity or comparison between projects, and with little col- laboration with national organizations involved in reef management (Wells, 1997). Thus there is an urgent need for scientific data to guide current management efforts in Belize and to evaluate the effectiveness of those efforts. This work applies a multivariate community approach to discriminating among geographic regions, identifying key discriminant species, and, in the future, will be used to determine the relative importance of environmental and management-linked influences. It is hypothesized that reef communities along the 250 km barrier reef will be differenti- ated among northern, central, and southern sites (Fig. 1), based on a general zonation proposed by Burke (1979). Furthermore, the atoll sites are expected to have different communities than the barrier reef sites, due to the isolated, more oceanic locations of the atolls. Two sets of geographically paired sites are examined in this study: (1) Hol Chan (HolNbr) and Tackle box (TacNbr), off Ambergris Caye are separated by about 8 km, and (2) Gallows reef (GalCbr) and Goffs Caye (GofCbr), near Belize City are separated by approximately 15 km (Fig. 1). It is hypothesized that these geographically paired sites are naturally more similar to each other than to the other sites. An alternate hypothesis is that the two sites located in closest proximity to the major developed areas in Belize (TacNbr near the tourist resort of San Pedro and GalCbr near the major city, Belize City) would be more similar to each other than to their geographically paired sites if their biotic communities were in fact ‘impacted’ by these developments. Lastly, this work compares different hierarchical (taxonomic) levels of analysis. It hypothesized that analyses based on the lowest taxonomic classification available, including different hierarchical levels for different substrate categories, have the greatest ability to distinguish between geographic regions.

METHODS

The sampling scheme utilized a stratified (windward fore-reef spurs), haphazard video transect- based design, similar to that of several other current monitoring programs (Aronson et al., 1994; Wheaton et al., 1996). During the summer of 1997, 17 reef sites (Fig. 1) were assessed with 10 replicate 25 m transects conducted at each site, using the procedure described in Aronson, et al (1994). Transects were oriented along individual reef spurs near the reef slope in a depth range of 12 to 19 m. This relatively deep fore reef zone was selected because it is a zone of major reef development, it provides comparable communities throughout the reef system, and less is known about this reef zone. This zone is also critical for reef accretion and is also of primary management concern since tourist activities are focused in this area. Sites were selected to give full geographic coverage consistent with barrier reef regions as defined by Burke (1979) and Wantland and Pusey (1971). Hi-8 video was taken beside each transect line with the camera held 25 cm above the substrate with a scaled reference bar giving a swath width of approximately 25 cm. Two 30 w ultra- bright lights were used for illumination. This analysis includes the 12 sites for which data have been fully analyzed (Fig. 1). Additional data on species richness, rugosity and fish communities, were collected at each site but are not included in this analysis which is based on the multivariate abundance data (proportional cover). MCFIELD ET AL.: ANALYSIS OF REEF COMMUNITY STRUCTURE IN BELIZE 747

Figure 1. Location of Study Sites in Belize. 748 BULLETIN OF MARINE SCIENCE, VOL. 69, NO. 2, 2001

Image analysis followed protocols developed by the EPA Florida Keys National Marine Sanctu- ary monitoring project (Wheaton et al., 1996). Fifty video images per transect (500 per site) were frame-grabbed, processed (de-interlaced, sharpened, enhanced) and saved onto CD-ROM. These digital images are thus available for other analyses (sponges, algae, disease, etc.) and serve as a permanent archive. PointCount for Coral Reefs software developed by the Dustan Lab, University of Charleston (Wheaton et al., 1996) was used with Image Pro„ software to generate 10 random points on each image and to offer a menu selection of coral species and other community categories for each point. Organisms found under each point were then identified. When possible stony corals (Scleractinia and Milleporina) were identified to species. Unidentifiable specimens were called ‘Scleractinia’. The ‘macro algae’ category corresponds to algal specimens with blades large enough to be distinguished on the video. The ‘substrate’ category contains smaller turf algae, encrusting coralline algae and bare rock. Additional categories are ‘Porifera’, ‘Octocorallia’, and ‘sand’. Points that fell on the scale bar or transect line were called ‘equipment’ and those that could not be classified within one of these groups were put in a ‘no count’ category. The percentage cover of each organism or category was calculated from the total 500 points per transect. Approximately 25 h of image analysis time was required to analyze each site (10 transects). The community data set, based on proportional cover of each species or category, was compiled into a matrix and imported into PRIMER ecological statistics software package (Clarke and Warwick, 1994; Clarke, 1993) for multivariate analysis. Raw biotic data values (proportional cover) ranged from 0.000226 to 0.489 and were thus square-root transformed. This square-root transformation appropriately weights the less abundant stony coral species, allowing variations in species compo- sition to play an important role while still incorporating changes in other major community components such as macro algae, Porifera, and substrate categories. Sites were first classified with hierarchical clustering (CLUSTER) using Bray-Curtis group average linkage (Clarke, 1993; Bray and Curtis, 1957) and then ordinated using non-metric multidimensional scaling (MDS) plots. Site labels correspond to geographic regions: northern (Nbr), central (Cbr), and southern (Sbr) barrier reef and atoll (Ato) sites (Fig. 1). Significant differences between groups of sites were tested using PRIMER’s multivariate equivalent of an ANOVA called ANOSIM for ‘analysis of similarities’ (Clarke and Green, 1988; Clark, 1993). Likewise ‘impacted’ sites located close to major coastal developments (TacNbr and GalCbr) were tested with ANOSIM for differences between neighboring ‘non- impacted’ sites (HolNbr and GofCbr), located further from the developments. Both global and pairwise tests are available in ANOSIM. The risk of Type I error is greatly reduced by the high number of replicates (10) per site. This test was based on 5000 permutations and has no built in assumptions about the data distribution. The key taxa responsible for differences between groups of sites were determined using PRIMER’s SIMPER routine (Clarke, 1993).

RESULTS

The mean percent cover of the major community components/categories was summa- rized for each of the 12 sites analyzed to date (Table 1). Coral cover ranged from 14.6% at Middle Caye, Glovers reef atoll to 43.6% at Half Moon Caye, Lighthouse Reef atoll, with an overall mean of 28.2%. Macro algal cover ranged from 9.4% at Half Moon Caye to 31.5% at South Water Caye, with an overall mean of 18.1%. The general ‘substrate’ category ranged from 36.6% at South Water Caye to 54.6% at Nicholas Caye, with an overall mean of 42.8%. Overall, 1.2% of the original data points (5000 points per site) were not included in the community analysis because they were classified as ‘equipment’ (0.7%) or were unidentifiable ‘no-counts’ (0.5%). These categorical data were used to group sites by hierarchical clustering or classification (Fig. 2A) and by multi-dimensional scaling (MDS) ordination (Fig. 2B), both of which are based on the underlying Bray-Curtis similarity matrix. The classification of MCFIELD ET AL.: ANALYSIS OF REEF COMMUNITY STRUCTURE IN BELIZE 749

Table 1. Percent cover of major reef community categories by site (n = 10). Ceoral Seubstrat Maacroalga Oactocoralli Pdorifer Zdoanthi San 1n. BacNbr M7ea 384. 411. 147. 50. 10. 00. 0. S1E 20. 35. 18. 02. 00. 00. 0. 2n. TacNbr M5ea 245. 410. 206. 68. 12. 00. 0. S3E 26. 32. 29. 05. 01. 00. 0. 3n. HolNbr M6ea 399. 387. 147. 32. 10. 00. 0. S1E 24. 16. 11. 15. 00. 00. 0. 4n. GalCbr M7ea 225. 400. 255. 63. 21. 02. 0. S6E. 10. 27. 12. 15. 01. 02. 0. 5n. GofCbr M9ea 327. 309. 196. 48. 11. 01. 0. S8E 12. 29. 17. 04. 00. 01. 0. 6n. SwaCbr M2ea 262. 356. 361. 71. 20. 00. 0. S4E 16. 12. 19. 05. 00. 00. 0. 7n. PomSbr M9ea 264. 437. 103. 131. 21. 07. 0. S7E 25. 20. 18. 05. 01. 06. 0. 8n. NicSbr M1ea 262. 544. 172. 89. 12. 00. 0. S9E 13. 24. 18. 04. 01. 00. 0. 9n. HmcAto M6ea 463. 348. 96. 56. 20. 03. 0. S4E 29. 12. 16. 05. 00. 02. 0. 1n0. CalAto M0ea 274. 452. 113. 68. 93. 06. 3. S7E 19. 10. 17. 09. 02. 05. 1. 1n1. MidAto M6ea 164. 465. 159. 180. 71. 09. 1. S5E 12. 11. 27. 00. 11. 06. 0. 1n2. SngAto M6ea 293. 458. 165. 73. 30. 00. 1. S7E 14. 18. 16. 06. 00. 04. 0.

M2ean 288. 412. 198. 62. 31. 07. 0. S5EM 25. 19. 17. 08. 00. 03. 0.

M6in 164. 346. 94. 30. 10. 00. 0. M6ax 463. 554. 301. 181. 93. 06. 3. R0ange 209. 118. 262. 78. 83. 06. 3.

sites based on broad categorical data did not clearly differentiate sites by geographic distribution, although geographically based clusters can reasonably be applied to the MDS ordination of these data (Fig. 2B). With this limited data set similarity was almost 90% among all sites. The analysis was repeated using the full community data set (classifying stony corals by species and other components by categories) (Fig. 3A,B). In this analysis, both classification and ordination produced three main groups of sites: atoll sites, southern barrier reef sites, and a combined group of northern/central barrier reef sites. Similar- ity was approximately 80% among all sites. The data set was then restricted to stony coral species and the same analyses were conducted (Fig. 4A,B). The stony coral community classification (Fig. 4A) is similar to the full community classification (Fig. 3A) but fails to clearly differentiate the atoll sites from the Northern and Central barrier reef sites. However, the geographic clusters can be more clearly distinguished in the MDS ordination (Fig. 4B). The overall similarity among sites based on stony coral community was approximately 70%. 750 BULLETIN OF MARINE SCIENCE, VOL. 69, NO. 2, 2001

Figure 2A. Classification of sites based on major benthic categories (proportional cover)

Figure 2B. MDS Ordination of sites based on major benthic categories (proportional cover) MCFIELD ET AL.: ANALYSIS OF REEF COMMUNITY STRUCTURE IN BELIZE 751

Figure 3A. Classification of sites based on full reef community structure (proportional cover)

Figure 3B. MDS Ordination of sites based on full reef community structure (proportional cover) 752 BULLETIN OF MARINE SCIENCE, VOL. 69, NO. 2, 2001

Figure 4A. Classification of sites based on stony coral community (proportional cover)

Figure 4B. MDS Ordination of sites based on stony coral community (proportional cover) MCFIELD ET AL.: ANALYSIS OF REEF COMMUNITY STRUCTURE IN BELIZE 753

Table 2. Results of ANOSIM significance tests for differences between sites.

Seites Compared Gllobal R valu Significance leve A8toll vs Barrier reef 0%.24 0.0 S0outh vs Central barrier reef 0%.58 0.0 S6outh vs North barrier reef 0%.45 0.0 N2orth vs Central barrier reef 0%.10 0.0 '4Impacted' vs 'Non-impacted' 0%.25 0.0 (based on 5,000 permutations, n = 10 replicates per site) The ANOSIM tests (Table 2) based on the 10 replicate transects per site, revealed sig- niﬁcant differences between atoll and barrier reef sites, between southern, northern and central barrier reef sites, and between sites selected as ‘impacted’ (near coastal developments) and their neighboring ‘non-impacted sites’. The results of the SIMPER analysis (Table 3) indicated that Agaricia tenuifolia and Montastrea annularis, and ‘macroalgae’ are important taxa for discriminating among all groups of sites. Other taxa, like the ‘Porifera’ and ‘Octocorallia’, are important for discriminating between atoll vs barrier reef sites and southern vs northern sites, respectively (Table 3).

DISCUSSION

Multivariate analysis of video-based abundance (proportional cover) community data can discriminate significant differences between sites grouped by geographic regions and impact status, within the approximately 250 by 50 km Belize Barrier Reef Complex. The methodology described requires less time in the field than traditional quantitative methods and provides a permanent data archive capable of multiple analyses for various pur- poses. Another recognized benefit of video-based sampling is that the larger actual sampling units (spatial coverage) possible with video greatly reduces the sensitivity to small scale heterogeneity (Carleton and Done, 1995). High quality images (preferably digital) are required to identify organisms to species or other taxonomic levels. Traditional parametric univariate and multivariate analyses often utilize categorical data, such as provided in Table 1. In our analysis, some differences can be found between groups of sites (or geographic settings) based on general community categories. For ex- ample, the ‘Porifera’ category clearly has a higher abundance at atoll sites than at barrier reef sites. However, most categories are less discriminating. Both the highest and the lowest coral cover values are found in atoll sites, and high and low macro algae values are found along the barrier reef. The classification (Fig. 2A) and ordination (Fig. 2B) of these categorical data do dot clearly differentiate among the hypothesized geographic zona- tions. However, the sites with highest coral cover/lowest macro algal cover group to- gether, as do those with the highest macro algal cover (potentially impacted sites). Possi- bly such coarse resolution data can effectively discriminate between impacted and non- impacted sites, if the impact involves a shift between major community categories, like a coral to macro algal conversion. Aronson and Swanson (1997) were able to detect significant differences between an impacted site (from a ship grounding) and reference sites using separate parametric analysis (MANOVA) of stony coral communities and of algal categories. 754 BULLETIN OF MARINE SCIENCE, VOL. 69, NO. 2, 2001

Table 3. Identification of key discriminating taxa among groups of sites.

Sypecies/Category % of dissimilarit 1 Mean abundance2 Altoll vs barrier reef sites (mean dissimilarity 20.3%) Artol Barrie Agaricia tenuifolia 90.9% 04.0 0.0 Porifera 76.5% 02.0 0.0 S%and 72.4 00.0 0.0 Montastrea annularis 63.9% 00.1 0.1 M%acroalgae 65.3 00.1 0.2

Shouth vs north barrier reef (mean dissimilarity 21.37%) Shout Nort Agaricia tenuifolia 99.36% 03.0 0.0 Montastrea annularis 85.58% 02.0 0.1 O%ctocorallia 60.64 05.1 0.0 M%acroalgae 63.46 00.1 0.2 S%ubstrate 51.87 00.5 0.4

Shouth vs central barrier reef (mean dissimilarity 21.84%) Slout Centra Agaricia tenuifolia 192.93% 01.0 0.0 M%acroalgae 93.15 04.1 0.2 Montastrea annularis 75.28% 01.0 0.1 S%ubstrate 61.54 09.5 0.3 Montastrea cavernosa 50.43% 02.0 0.0

Nlorth vs central barrier reef (mean dissimilarity 14.67%) Chentra Nort M%acroalgae 74.51 00.2 0.2 Agaricia tenuifolia 61.63% 03.0 0.0 Colpophyllia natans 50.20% 03.0 0.0 Montastrea annularis 51.05% 02.1 0.1

Impacted vs non-impacted3 (tmean dissimilarity 15.4%) Itmpac Non-impac Agaricia tenuifolia 81.2% 04.0 0.0 M%acroalgae 66.7 05.2 0.2 Montastrea annularis 68.6% 02.0 0.1 Porites porites 51.8% 02.0 0.0 1Based on Bray Curtis Similarity 2Abundance in proportion of total benthic cover 3Impact sites (TacNbr, GalCbr) vs non-impacted (HolNbr, GofCbr)

The higher resolution fully multivariate reef community data enable the discrimination of large-scale geographic patterns (Fig. 3A,B), despite the overall high similarity among sites. The Bray-Curtis classification of sites (Fig. 3A) indicates that the southern barrier reef sites do differ from the northern and central barrier reef sites and the ANOSIM permutations find these differences to be significant (P = 0.0%) with the highest r values (Table 2). The atoll sites also differ significantly (P = 0.0%; Table 2) from the barrier reef sites, although one site (HmcAto) is more similar to northern barrier reef sites than the other atoll sites. MDS ordination (Kruskal, 1964), presents another graphical interpreta- tion of the relationships among sites (Fig. 3B) and is considered the preferred representation (Clarke, 1993). The relatively low stress (0.08) indicates a good 2-dimensional representation of the multidimensional data. This ordination also clearly separates the sites by geographic region and while maintaining the highest similarity between GalCbr and MCFIELD ET AL.: ANALYSIS OF REEF COMMUNITY STRUCTURE IN BELIZE 755

TacNbr, as discussed later. The ANOSIM results indicate there is a significant difference between northern and central regions (P = 0.0%; Table 2) although the r value is very low (r = 0.102) and the MDS ordinations do not clearly separate these sites. The significant result may be partly attributable to the high number of replicates per site (10) and should be interpreted with caution (Clarke, 1993). Overall, the postulated differences between geographical regions appear to be valid, although the difference between the northern and central regions is less than convincing. In addition to looking for overall geographic distinctions in reef community structure, four sites were chosen to test for potential impacts of coastal development. Both TacNbr and GalCbr are potentially ‘impacted sites’ due to their close proximity to the two major coastal developments in Belize; San Pedro Town and Belize City. These ‘impacted’ sites exhibited the highest similarity (92%, Fig. 3A) of any two sites in all three analyses (Figs. 2a–4a), despite being separated by approximately 55 km. TacNbr and HolNbr were among the closest sites in this study (separated by about 8 km), but have a lower similarity value of 82% (Fig. 3A), while GalCbr and GofCbr are separated by about 15 km and have a similarity of about 87% (Fig. 3A). The differences between the two ‘impacted’ sites (TacNbr and GalCbr) and the two ‘non-impacted’ sites (HolNbr and GofCbr) are significant (P = 0.0%) based on the ANOSIM permutations, although the R value is rather low (Table 2). While it is interesting that the ‘impacted’ sites had the highest similarity and varied significantly from their neighboring ‘non-impacted’ sites, there can be no conclusions re- garding the cause of the community similarity or the validity of this ‘impact’ status as- signed to these sites. However, as additional sites are analyzed and more such paired sites are included the strength of our inferences may increase and assist in the design of more experimentally based tests. A. tenuifolia and M. annularis are the scleractinian species most responsible for discriminating between sites. Their abundances are often in inverse proportions, probably related to wave energy. The unsheltered oceanic atoll environments support less of the more fragile A. tenuifolia and more of the physically robust M. annularis (Table 3). Both corals are more abundant in non-impacted vs. impacted sites, indicating a potential influence of other environmental gradients (e.g., nutrients). Similarly, the macro algae category contributes to the differentiation among all sites, but is particularly important at discriminating between the central and other barrier reef sites and between impacted vs. non-impacted sites. The Porifera category is useful for discriminating between atoll vs barrier reef sites, but not among barrier reef regions. Octocorallia are more abundant in the southern province and help differentiate southern from northern barrier reef sites. The SIMPER analysis technique has the potential to identify important indicator species, which account for the differences between sites. Specific physiological studies could then be designed to determine what environmental factor(s) could explain the observed biotic gradients. If such indicator species (or the lack thereof) can be linked to specific environmental stressors, then the presence/absence or low abundance of these specific organisms would be useful in rapid ecological assessments. Published multivariate analyses are less common for reef communities than for many other marine communities. In general, reef community data is also notoriously ambigu- ous, with many studies reporting no spatial patterns due to the high variability of the data. However, most multivariate studies in reef communities analyze only data for stony corals (Murdoch and Aronson, 1999) or other restricted community components (e.g., gorgonian species in Marquez et al., 1997). Such an approach may provide answers to ques- 756 BULLETIN OF MARINE SCIENCE, VOL. 69, NO. 2, 2001 tions relating specifically to the taxa being examined but would probably not adequately address the multiple interactions and complexities characteristic of reef community dynamics. Since the major players in reef community dynamics include corals and other functional groups, like macro algae and the Porifera, it is important to include these members of the community in the analysis. By including the highest resolution biological data available, one would expect to gain a higher resolution in the biotic community classification, as seen in this study. Further increased resolution of the community data will be attained in future analyses for this project by separating the large ‘substrate’ category into further divisions such as; coralline algae, algal turf, sediment mats, recently dead coral, etc. To illustrate the point that analysis including functional groups is highly effective, multivariate analysis was repeated using only stony coral species. Classification of sites (Fig. 4A) produced groupings that were similar but less distinctly grouped into spatial/ geographical patterns than for the full community analysis (Fig. 3A). Interestingly, the MDS ordination of the coral community (Fig. 4B) is more similar to that of the full reef community (Fig. 3B), indicating that this representation of the relationship between sites is more robust and appropriate than cluster or classification analysis, as suggested by Clarke (1993). Analysis of the differences between these three classification/ordination schemes may provide further insight into responses of different elements of the reef community, which should potentially be helpful at identifying stressors and indicator species. If possible other researchers could re-analyze their multivariate data, including non-coral classifications, to determine if this additional information leads to a more discriminating spatial pattern. Corals are arguably the most important members of the community due to their ability to create structural complexity and given their recent decline in abundance. They are also sensitive environmental indicators, with some species having much greater tolerances than others for certain environmental conditions. Although analysis of community data based upon mixed taxonomic levels may seem inappropriate to some, the combination of stony coral species and other functional community categories appears to discriminate effectively between highly similar sites or groups of sites. Fortunately, most reef community data are initially recorded at the species level for stony corals (in the Caribbean) and at functional /morphological levels for other biotic components. It is therefore straight- forward to use the highest level of taxonomic resolution available within multivariate analyses and is somewhat surprising that this approach has not been used before.

CONCLUSIONS

Scientists are now faced with growing pressure from managers and conservationists to understand not only how reef ecosystems normally function, but also how they respond to natural and anthropogenic alterations including the short-term effects of management and the long-term effects of global climate change. Through actions which alter the natural environment and regulatory reactions which attempt to control these alterations, hu- mans are manipulating natural ecosystems and conducting large-scale experiments. Un- fortunately, quantitative observations of reef community structure are rarely being recorded coincident with these manipulations. Management efforts are largely based on theoretical notions often derived from case studies in disparate regions of the world in- MCFIELD ET AL.: ANALYSIS OF REEF COMMUNITY STRUCTURE IN BELIZE 757 volving reefs with vastly different environmental histories. However, new approaches are being developed to quantify and interpret ecological communities in the context of ad- dressing management needs (Clarke and Ainsworth, 1993; Done, 1995; DeVantier et al., 1998). The second phase of this work, which is in progress, involves the analysis of environmental and management linked influences to determine which influences best explain the observed biotic community patterns. This approach will ultimately provide a mecha- nism to evaluate the success of current reef management practices in Belize and indicate which environmental factors have the greatest influence on Belize’s reefs.

ACKNOWLEDGMENTS

M. McField’s research is supported by the ISRS/CMC Reef Ecosystem Science Fellowship and the Elsie and William Knight, Jr Fellowship from the Department of Marine Science, USF. This project received logistical support from the Belize Coastal Zone Management Project, the Fisheries Department, Wildlife Conservation Society, UCB Marine Research Center, Belize Audubon Soci- ety, Pelican Beach Resort, Rum Point Inn, and Sea Sports Belize. Thanks to the following individu- als for assistance with data collection (ﬁsh populations): I. Majil and D. Gomez (Bacalar Chico National Park and Marine Reserve), A. Pott (Hol Chan Marine Reserve), J. Jarrell (USF), D. Will- iams (USF), W. Heymen (TNC/PROARCA); and general ﬁeld assistance: M. Allamia, M. Paz, A. Avilez, J. Searle Jr., K. Holterman, H. Gamboa and A. Williams. M. Patterson, M. Brill and P. Dustan also provided advice and assistance in image processing and analysis.

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ADDRESS: Department of Marine Science, University of South Florida,140 Seventh Ave. S., St. Peters- burg, Florida 33701. CORRESPONDING ADDRESS: (M.D.Mc.) P. O. Box 512, Belize City, Belize, Central America.