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Article

Application of Standard Ecological Community Classification (CMECS) to Coastal Zone Management and Conservation on Small Islands

by
Kathleen Sullivan Sealey
* and
Jacob Patus
Coastal Ecology Laboratory, Department of Biology, University of Miami, Coral Gables, FL 33146, USA
*
Author to whom correspondence should be addressed.
Land 2025, 14(10), 1939; https://doi.org/10.3390/land14101939
Submission received: 12 August 2025 / Revised: 17 September 2025 / Accepted: 22 September 2025 / Published: 25 September 2025
(This article belongs to the Special Issue Islandscapes: From Biodiversity Conservation to Ecosystem Services Provision)
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Abstract

Classification of island coastal landscapes is a challenge to incorporate both the terrestrial and the aquatic environment characteristics, and place biological diversity in a regional and insular context. The Coastal and Marine Ecological Classification Standard (CMECS) was developed for use in the United States and incorporates geomorphic data, substrate data, biological information, as well as water column characteristics. The CMECS framework was applied to the island of Great Exuma, The Bahamas. The classification used data from existing studies to include oceanographic data, seawater temperature, salinity, benthic invertebrate surveys, sediment analysis, marine plant surveys, and coastal geomorphology. The information generated is a multi-dimensional description of benthic and shoreline biotopes characterized by dominant species. Biotopes were both mapped and described in hierarchical classification schemes that captured unique components of diversity in the mosaic of coastal natural communities. Natural community classification into biotopes is a useful tool to quantify ecological landscapes as a basis to develop monitoring over time for biotic community response to climate change and human alteration of the coastal zone.

1. Introduction

The differences in scales of ecological processes across space and time have created a longstanding divide between terrestrial and marine research. Yet, the same questions are posed in both settings concerning community dynamics and the effect of global processes on the ecosystem [1]. What defines the difference between the systems is also what leads to the largest differences between them: the presence of seawater. The density and viscosity of seawater have led to the formation of unique ecological communities and organism lifestyles that are not seen on land and the connection with seawater leads to the perception of a continuous ecological connection in the marine environment [2]. Classification of the coastal landscape provides a unique challenge as, by definition, coastal areas incorporate both the terrestrial and the aquatic environment.
Standardized ecological classification schemes are important not only for ecological studies, but are of paramount importance in applications of ecology to the sustainable development and environmental stability of coastal ecosystems [3]. A standardized classification scheme allows for quick and easy dissemination of crucial information regarding substrate, geomorphology, and the status of indicator or protected species linked to ecosystem services to stakeholders. The use of ecological classifications is a crucial part of documenting and quantifying Ecosystem Goods and Services (EGS), a key component for the restoration and management of coastal environments.
The Coastal and Marine Ecological Classification Standard (CMECS) was developed for use in the United States and takes geomorphic data, substrate data, biological information, as well as water column characteristics into account when classifying an area [4]. The CMECS framework was chosen to be applied to the study area of Great Exuma, The Bahamas. The information contained with CMECS classifications will prove useful for generating categories to be used as inputs as well as outputs of attempts to model the spatial distribution of biological communities. The classification of the coastal environment can be used to quantify areas with important ecological function and that provide necessary ecosystem services [3]. CMECS has been used inside and outside the United States and will prove useful for areas in the Caribbean region as a way of identifying and quantifying the landscape in a way that is understandable by a wide audience of coastal managers [5,6,7]. The application of classification systems to the landscape is critical to developing a baseline for and creating an understanding of the changes in community structure and extent over time [8].
The Bahamian archipelago provides an ideal case study for the development of spatial datasets in landscape ecology. First, islands themselves are important study sites for community and population ecology, and drivers of ecology changes. The Commonwealth of The Bahamas as a small-island developing state lacks a national standardized process for ecological classification, but the US Federal Data Standards for Classification of Marine and Estuarine Communities (CMECS) [9] can provide the framework that can be used to develop a natural community inventory for the archipelago. The structure of the carbonate banks that make up the Bahamas, with small islands and cays, aligns much of the reefal habitat in close proximity to the islands. This proximity of reefs to islands renders reefal habitats vulnerable to perturbation by surface water runoff and other anthropogenic dangers.
Development on the islands also threatens the prolonged survivability of local, native plant communities [10]. Reefal and plant communities both provide multiple ecosystem services for the Bahamian coastal ecosystems. These communities both indirectly and directly contribute to the economy of the Bahamas by drawing tourists [11], providing habitats for juvenile and adult fishes [12], and physically stabilizing the coastline against the forces imposed by erosion and natural disasters such as hurricanes [13]. In order to maintain the aforementioned ecosystem services, the diversity of reefal and plant communities in the Bahamas must be conserved. The relationship between biological production (i.e., ecosystem function) and diversity has become a central focus of ecosystem management [8]. Development on the coastline has the potential to impact nearshore marine habitats by amplifying the barriers to successful reproduction, recruitment, and growth of coastal species, including corals, invertebrates, and fishes [10]. Changes in coastal environments have not been systematically tracked and documented, and human alterations to the coast are rarely limited to a single activity.
The application of a standardized ecological classification scheme to the coasts of the Bahamas provides a way to establish a baseline against which changes in the natural capital provided by crucial habitats may be tracked. Changes in the landscape ecology of coastal environments, including species extirpation, habitat loss, and fundamental shifts in nutrient dynamics with water quality change can be tracked and characterized. The aim of this study was to (1) create and characterize the patterns of natural communities around one island (Great Exuma) to understand ecological connectivity to island hydrology and geomorphology; and (2) complete an assessment of coastal vulnerability and risk to sea level rise and flooding events based on ecological characteristics (natural communities). The survey was motivated by two questions: (1) what are the drivers of small island coastal ecology, and how can patterns in beta diversity be explained and used to understand ecosystem function in terms of movement of water and nutrients across the land–sea interface; and (2) how can this ecological information be applied to coastal development planning, particularly in terms of climate change and flood mitigation?

2. Materials and Methods

The island of Great Exuma was selected as a study site based on national interest in both regional planning [14,15] and accessibility of remote sensing and existing datasets on oceanography, benthic surveys, and coastal plant inventories applied using classification guidelines [5]. Development of a classification scheme added to existing information concerning coastal ranking surveys (based on the classification of shorelines into beaches, mangroves, and rocky shores), roads, and coastal development impacts from [10,13]. Great Exuma is the largest island in the Exuma island chain with a population of almost 12,000 residents living in six major settlements. The island is located on the eastern platform margin of the Great Bahama Banks, and the depth increases rapidly (within 2 km) offshore to the constructional canyon of Exuma Sound [16]. Great Exuma has approximately 290 km of shoreline, with the southwestern shore dominated by mangrove wetlands. The coastal development patterns and threats have been extensively studied in previous publications that highlight the ranking of coastal zones based on extent of invasive plant species coverage, proximity of roads and buildings to the shoreline, as well as the grading and sand mining that changes coastal geomorphology.
CMECS describes two types of settings: Aquatic and Biogeographic. The Aquatic setting is a hierarchical classification that is described by the salinity, coastal proximity, and tidal regimes of the zone. The environment is initially divided into three globally recognized systems: Marine, Estuarine, and Lacustrine, and then further into subsystems, such as Nearshore, Offshore, or Oceanic. Furthermore, the Estuarine System and Marine Nearshore Subsystem are divided into shoreline and benthic biotopes (Supplemental S1 illustrates this hierarchical classification). The Biogeographic setting is described by the climate, geology, and evolutionary history of an area, an approach advocated in the description of Marine Ecoregions of the World (MEOWs) [17]. Sea Surface temperatures were taken from the dataset collected by the Caribbean Marine Research Laboratory on Lee Stocking Island, described in [16,18]. Also, there are regional biogeographic classifications for The Bahamas in the Ecoregional Conservation Plan, as well as CARICOMP abiotic data [19].
Great Exuma was visited nine times from 2004 to 2014 to re-survey coastal and nearshore marine sites [10]; sites are listed and classified in Supplemental S2. One of these sites is a mangrove pond and associated wetland that is being actively restored (Victoria Pond, UNESCO Ecohydrology Demonstration Site) [20]. At each of these sites, plant surveys as well as coastal ranking of habitat quality were completed. A combination of data from the coastal and marine site surveys, satellite imagery, and a Digital Elevation Model (DEM) were used for the classification of Great Exuma’s coastal environs. The classification scheme used for the island was hierarchical; it consisted of dividing the island into regimes based on topography as well as energy and salinity of the water column in the surrounding marine system, dividing those regimes into zones based on whether they are terrestrial or marine, and finally dividing those zones into biotopes based on substrate and biota composition.
An area was buffered around Great Exuma and its surrounding cays with a radius of 4 km to outline the boundary of the classification polygons, an arbitrary value based on publications addressing the extent of land-based sources of pollutants in tropical dry islands [21]. On the northern, ocean side of the island, the maximum boundary of the classification polygons was further restricted to the 200 m bathymetric contour of the Great Bahama Bank, upon which the Exuma Cays are situated. The island and surrounding area were initially divided into five regimes: Upland, Inland Open Water, Estuarine, Nearshore Marine—Bank Side, and Nearshore Marine—Ocean Side (Figure 1). Any part of the island that is located at an elevation above 5 m as determined by the DEM made available by CGIAR [21] is classified as being in the Upland regime. Inland Open Water polygon boundaries were determined based on topographical information and through the use of satellite imagery made available by Google Earth [22]. The Estuarine Regime is defined as areas where the coastal zone intersects with the freshwater lenses of the island. The rest of the classification boundary polygons were bisected down the center of the island from northwest to southeast running through the Upland regime; the area to the north of the bisector is classified as Nearshore Marine—Ocean Side and the area to the south of the bisector is classified as Nearshore Marine—Bank Side (Figure 1). The Nearshore Marine regimes were classified as separate regimes because wave energy and exposure to the open ocean are drastically different on either side of the bisector.
For the aims of this study, the Upland and Inland Open Water regimes required no further classification; a natural vegetation classification exists in other publications for upland areas. The Estuarine and two Nearshore Marine regimes were next subdivided into zones. For classification into zones, only two possibilities exist: Shoreline or Bottom. Shoreline polygons are terrestrial polygons and Bottom polygons are areas where the substrate is covered by the water column, including both open ocean and intertidal areas. These polygons were then further subdivided into biotopes based on the substrate and biotic composition of the areas as could be determined by Google Earth imagery viewed at an elevation of 500 m. For a full list of biotope classifications see Supplemental S1.
Ground truthing of the classification polygons was completed during a field expedition shortly after the completion of the first draft of the classification maps. Ground truthing occurred after several iterations of the natural community map to determine the accuracy of the polygon attributes based on aerial photographs and site survey photographs. The goals of the ground-truthing expeditions were to survey coastal areas with which the investigators were less familiar, and to document coastal vegetation characteristics, water quality, and any coastal alterations. Since 2004, 14 field expeditions have been carried out on Exuma for coastal ecology research, totaling over 160 days in the field.

3. Results

3.1. Ground Truthing the CMECS Polygons

Approximately 3.5% of the total area of the polygons classified as Shoreline polygons were ground truthed when there were discrepancies between the interpretations by the authors. After reviewing coastal surveys and on-site photography, 19 of 99 ground-truthed polygons were reclassified (~18.8% of the ground-truthed area). The polygons were reclassified to address three types of discrepancies between the first draft of the classification map and what was observed in the field: (1) incorrect zone classification, (2) incorrect natural community classification, or (3) incorrect biotope classification.
Incorrect zone classifications are errors in classification where a polygon classified as being within the shoreline zone is actually within the bottom zone, or vice versa. The three instances in which this discrepancy was discovered occurred as an artifact of the buffering method used to define shoreline boundaries. A set distance was buffered away from the edge of the base map island polygons (developed from LandSat 6 and 7 imagery) to account for tidal ranges in The Bahamas (unequal, semi-diurnal micro-tides with a maximum range of 1.9 m). In some instances, this buffering needed not to be applied, such as near cliffs.
Natural community classification discrepancies are errors in classification where one type of microhabitat is misidentified as another type based on satellite photography. The most common occurrence of this classification error (three polygons) occurred when what looked like a pocket beach in the satellite imagery was actually a rocky shore. This type of error also occurred due to misinterpretation of human alterations to the shoreline, such as the presence of boat ramps and the clearing of vegetation. As the CMECS classification is a multi-dimensional classification regime, map accuracy does not apply in standard vegetation mapping. Detecting changes in the ecological community requires long-term monitoring to understand broader changes in rainfall, temperature, and storm events that all influence salinity regimes in coastal areas. Human impacts on natural communities are also critical to monitor, not only obvious changes such as land clearing and development, but less obvious impact such as saltwater intrusion to freshwater lenses from wells.
The most common type of classification discrepancy, biotope misclassification, usually occurred when the actual vegetation structure of an area was not represented accurately by the classified polygon. This is expected to be encountered the most because vegetation structure is not easily distinguished using only satellite photography. For example, a new biotope classification was created for areas which are dominated by the invasive Australian pine, Casuarina equisetifolia, which looks similar to other vegetated sandy shore biotopes when viewed via satellite photography but is in reality drastically different in terms of ecology and physical dune structure.

3.2. Coastal Natural Community Diversity for Great Exuma

The natural communities present on Great Exuma, including both shoreline and bottom (benthic) biotopes, illustrate the wealth in coastal resources that are available on just one Bahamian island. In total, sixteen shoreline biotopes were described, ranging from rocky cliffs to mangrove shrublands, and twenty-seven bottom biotopes were described for coastal marine environments to depths of up to 200 m (Figure 2). “Dredged bottom” was also added as a benthic biotope.
An overall description of the occurrence and distribution of natural communities further illustrates the importance of the regime-level of classification in any assessment of coastal marine resources, as each regime has a unique distribution of shoreline and benthic biotopes. The shoreline biotopes are grouped as “beaches”, “rocky shore” or “mangroves” in Table 1 to illustrate the major differences between regimes. The largest area of mangroves (and greatest diversity of mangrove biotopes) occurs in the estuarine regime. The greatest diversity and largest areas of rocky shore and beach biotopes occur in the ocean-side marine regime. The three classified regimes are not similar in their overall total area, but each represents a unique unit of biodiversity in the size, extent, and composition of natural community biotopes (Figure 3). The Nearshore Ocean-side regime is the most diverse regime in terms of the number of different biotopes, and mosaic of biotope polygons.
The Estuarine regime covers approximately 628 km of shoreline, consisting mostly of very shallow, convoluted mangrove creeks and over wash islands, represented by seven shoreline biotopes. The two Nearshore Marine regimes differ dramatically when comparing the Bank Side to the Ocean Side of Great Exuma. The Nearshore Marine—Bank Side regime covered approximately 400 km of shoreline, consisting of nine shoreline biotopes. The Nearshore Marine—Ocean Side regime covers 698 km of shoreline consisting of eleven shoreline biotopes. Though all three regimes have shorelines that are dominated by mangrove biotopes, the beaches and rocky shores are much more prevalent in the Nearshore Marine—Ocean Side regime (Figure 3 and Figure 4).
The ability to classify mangrove communities on a sparsely populated island is critical to documenting the biological diversity captured in unique biotic communities for both management and restoration. In The Bahamas, mangrove forest ecosystems are dominated by four species: black mangroves (Avicennia germinans), red mangroves (Rhizophora mangle), white mangroves (Laguncularia racemosa), and buttonwood (Conocarpus erectus). A. germinans typically are found in high salinity and high sulfide areas and are easily distinguished by their pneumatophores, which oxidize sulfides in the typically anaerobic soils found in mangrove ecosystems. R. mangle is found in the saline environments with less sulfide and are distinguished by their prop roots which extend out from the trunks of the trees.
Mangroves occur within two biotic classes: scrub-shrub wetlands and forested wetlands. A Tidal Mangrove Shrubland is dominated by dwarf (generally less than 6 m in height) mangroves and associates that typically occur on intertidal mudflats in estuarine environments. This includes immature stands of plants or mature trees whose growth has been stunted due to a harsh (i.e., dry or hypersaline) growing environment. Tidal Mangrove Forests are dominated by mangroves and associates that are generally taller than 6 m. These forests occur along sheltered coasts on intertidal mudflats in estuarine environments. The extent to which mangrove shrublands and forests extend inland is influenced by tidal amplitude.
The dominant species present in a community further define CMECS classification of an ecological unit. Shrublands can be dominated by R. mangle or be mixed with A. germinans and/or L. racemosa. There can also be A. germinans-dominated shrublands that are mixed with Batis maritima (saltwort) or Spartina patens (salt meadow cordgrass). Mangrove forests can be dominated by A. germinans, R. mangle, or C. erectus. There are also mixed mangrove forests that consist of R. mangle, A. germinans, and L. racemosa.
(Figure 5). The Estuarine regime is largely intertidal; thus, the area is dominated by shoreline biotopes and a very small area of permanently flooded benthic biotopes comprising submerged aquatic vegetation (i.e., seagrasses and algae) and mud bottoms; only six biotopes are described—this is in contrast to the Nearshore Marine—Ocean Side regime.
Bottom biotopes cover significantly different areas in the three classified regimes: in total, there were twenty-four benthic biotopes with a wide diversity of coral reef, hard-bottom, and seagrass natural communities (See Supplemental S1) The Nearshore Marine—Bank Side regime covered the largest area of very shallow sandy bank, with eleven benthic biotopes described. Of the three regimes, the Nearshore Marine—Ocean Side displays the greatest spatial complexity and diversity in both the shoreline and bottom zones.

4. Discussion

4.1. Application of CMECS to Small Tropical Islands

CMECS is a hierarchical classification system that uses four components to describe the coastal and marine environment, ultimately combining the four components into biotopes, unique combinations of abiotic conditions and the species associated with the habitat created by these conditions. Although the classification can be digitally mapped, the classification goes beyond mapping to include site-specific substrata, oceanography, and species assemblages. CMECS classifications encompass both natural and anthropogenic features, allowing for the representation of human influences on the landscape. Thus, developing a dynamic CMECS map of an island will allow for the documentation of large-scale ecological changes over time, documenting shifts with major storm events, coastal development, or even oil spills [13,23]. The limitations are largely resources and funding; there is the human capacity in young Bahamians already trained in marine sciences and GIS to implement a national mapping initiative.
The structure of a CMECS biotope is described by four components: water column, geoform, substrate, and biotic components. More information collected over time can improve and refine the classification as a critical measure of coastal biological diversity. The coastal ecology of the island is critical for the maintenance of Great Exuma’s tourism-based economy [24]. The extreme oligotrophic (low nutrient) conditions of the nearshore marine systems are maintained by a complex filtering of freshwater runoff through mangrove wetlands and ponds, resulting in the clear, turquoise waters that are prominent in the Bahamas and draw beach-going tourists. Thus, the impacts of development and other aspects of the tourism industry on the ecology can be monitored in a number of ways: coastal water quality assessments, tracking keystone species of plants and animals as well as the assessment of invasive species such as the Indo-Pacific lionfish or the Australian pine in order to develop the most effective coastal management strategies for maintaining both the economy and the ecology of the islands.
There exists a limited dataset which contains information regarding the state of the coast, records of coastal alterations, and a coastal classification for the largest islands in the Bahamas [25]. The existing information is expanded here for the island of Great Exuma to include a more detailed coastal classification based on topography, substrate composition, and geomorphology using the CMECS with the global biogeographic provinces from MEOWs [26]. The establishment of a CMECS dataset system has applications to many ecosystem service quantification projects such as carbon sequestration, water quality monitoring standards, limits on coastal development, and even thresholds for installing Advanced Wastewater Treatment (AWWT). However, these applications would require a national initiative in both adopting a classification scheme as well as a plan for the routine monitoring of coastal and wetland communities.

4.2. Use of CMECS Datasets to Measure Coastal Ecosystem Services and Pollution Impacts

One of the most overshadowing concerns in tropical coastal ecology is that of eutrophication, and while the overall processes and consequences that characterize eutrophication are well understood, there are challenges in determining nutrient thresholds in very oligotrophic conditions such as occur in The Bahamas. A simple definition of eutrophication in aquatic ecosystems is the process by which water bodies are made to have relatively large supplies of nutrients [27]. However, this definition only describes part of the story. The threats of eutrophication can include the effects that those nutrients have on the coastal and benthic communities as well as on the human health from bathing or eating locally caught seafood [28,29,30]. Eutrophication of coastal waters is a global phenomenon which occurs more frequently near areas of high human population density [29] and, for Great Exuma, nitrogen pollution is accumulated in freshwater lens (from dumps and cesspits) that seep into coastal wetlands and mangrove creeks throughout the island.
The resultant brackish water that is found at the nexus of the freshwater lens and the underlying or surrounding marine water creates an incredibly diverse coastal wetland environment, including both mangrove and marsh communities Thus, the location and quality of mangrove wetland habitats on Great Exuma is highly influenced by the location and longevity of freshwater lenses on the island. The state of these wetlands can be tied directly to the state of their corresponding freshwater lenses. Population growth or expanding agriculture in the hot, dry climate lends to saltwater intrusion to the lens, thus impacting both the upland and coastal vegetation. Changes in freshwater lenses impact the estuarine regime as well as tidal wetlands.
Threats to freshwater lenses on Great Exuma include sea-level rise, changes in precipitation patterns, and an increase in impermeable surfaces on the island. Sea level rise will have a reductive effect on the size of freshwater lenses by raising the height of the dense seawater on which the freshwater rests. Changes in precipitation patterns will affect the rate at which freshwater lenses recharge. These threats to the state of the freshwater lenses will thereby have an indirect effect on the location and health of wetland environments across the island. In the absence of groundwater monitoring, vegetation changes through CMECS mapping can highlight these hydrological shifts on the island.
Coastal eutrophication has become a persistent global issue largely due to an increased availability of reactive nitrogen [31]. The increase in anthropogenic reactive nitrogen is estimated to be accompanied by a 1.7-fold increase in the export of reactive nitrogen to coastal areas with projections of up to a 2.3-fold increase by 2050 [32].
Smaller-scale dynamics of reactive nitrogen are seemingly more complex as nitrogen compounds like nitrate and ammonium are estimated to have a global residence time of approximately one day due to rapid assimilation into biological processes [31]. Tracking the nitrogen pollution of coastal waters on islands requires resources as most land-based sources of pollution are non-point, such as storm and rainfall runoff entering nearshore waters [33].
For ecosystems to be properly managed, an inventory of the processes and patterns that occur within the system must exist. The creation of such an inventory may be facilitated by applying an ecological classification to the landscape, especially the shorelines and nearshore marine communities that rapidly change with storm, pollution or development disturbances. The most useful ecological classification schemes should include information about biotic as well as abiotic factors. When this inventory is applied within a spatial framework, the result is a spatial database that provides a snapshot of the ecological processes that are occurring within a landscape as well as the extent to which these processes are occurring. For example, the estuarine regime on the southern side of Great Exuma island had unique mangrove and benthic biotopes found nowhere else around the island. The western third of the island has large freshwater lenses, and is very flat, creating a large wetland area adjacent to a complex mangrove creek system (Figure 1). This spatial patterning of natural communities shows community-level diversity and geographically defined areas of unique hydrological and ecological conditions. The large shallow freshwater lens in this area might be particularly vulnerable to the placement of a large tourism development or placement of a solid waste disposal site (dump) that could easily contaminate the groundwater, and its associated wetlands. A complete classification of ecosystem units allows for additional study of how the physical and chemical processes may influence the structure of the biological communities.
The classification of mangrove communities is critical to understanding the role of tidal wetlands throughout the Bahamas in carbon sequestration. In many coastal environments, mangroves aid in the production of soil by trapping debris around the prop roots and pneumatophores, which accumulate and eventually form mangrove peats. The dead leaves and wood of dying mangroves contribute organic content to the mangrove peat, as they get broken down by crabs that live within the mangrove soils [34]. Thus, mangrove ecosystems are major sinks for carbon in coastal environments with a net primary production estimated to be around 218 Tg C y−1 [35].
Mangrove creeks provide a habitat for a wide range of life forms, other than the forests which surround the creeks. The bottom of the creeks is typically covered by patches of submerged aquatic vegetation (SAV) which include seagrasses, such as Thalassia testudium, or stands of macroalgae species like Halimeda sp. or Penicillus sp. Mangrove ecosystems increase the availability of nutrients to nearby SAV communities. The relatively calm conditions within the mangrove creeks, combined with the structural complexity provided by the mangrove plant species and the forage provided by the SAV that is typically associated with mangrove creeks make mangrove creeks important habitats for benthic epifauna as well as nurseries for other types of fauna (i.e., fish, turtles, and birds).
CMECS provides the framework to create novel biotopes in previously unclassified areas, should the need arise. The application of CMECS to Great Exuma illustrates the concentration of coral reef and beach communities concentrated along the ocean side of the island, the area with the most intense coastal development [36]. The loss or degradation of natural communities has already been documented [37], and can be tracked through CMECS datasets.

5. Conclusions

The CMECS framework has been applied to the island of Great Exuma, The Bahamas, to create a spatial database that classifies the coastal environs of the area to describe the unique distribution of biological communities within the island’s coastal zones. For small island developing states, the utilization of CMECS in both large-scale land-based source- of-pollution monitoring and estimating carbon sequestration is a powerful tool for marine and coastal resource management.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/land14101939/s1. Supplemental S1: Table of CMECS Classification for Shorelines and Nearshore Benthic Communities in the Three Regimes for Great Exuma, The Bahamas. Supplemental S2: the Table of survey sites and ecological characterizations for the CMECS classification.

Author Contributions

Conceptualization, K.S.S.; methodology, K.S.S. and J.P.; formal analysis, K.S.S. and J.P.; resources, K.S.S.; data curation, J.P.; all writing K.S.S. and J.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received funding from the Earthwatch Institute for the Coastal Ecology of The Bahamas expeditions from 2002 to 2011. Additional funding was provided by the University of Miami, College of Arts and Science for the Coastal Ecology Field Courses from 2012 to 2016, and from the Waitt Foundation under a Rapid Ocean Response grant for the study of the coastal impacts of Hurricane Irma from 2017 to 2019. Research permits were obtained from the Government of the Commonwealth of the Bahamas, Department of Marine Resources.

Data Availability Statement

The data presented in this study are available on request from the corresponding author, this data include GIS shape files, field notes, and photos.

Acknowledgments

Funding for the “Coastal Ecology of The Bahamas” project came from the Earthwatch Institute (2002–2011), and the University of Miami, College of Arts and Science (2012–2014). Field assistance from Yishen Li, Louis Grace, Alexio Brown, Ashleigh Braynen, and Janeae Wallace is gratefully acknowledged. Local assistance was provided from the Exuma Foundation.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
CMECSCoastal and Marine Ecological Classification Standard
NSNearshore
Tg CTera-grams of Carbon

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Figure 1. Regimes around Great Exuma and Little Exuma are based on depth and salinity. There is a small estuarine regime characterized by variable salinities and tidal influence, and much larger marine regimes, one on the open ocean side adjacent to Exuma Sound, and the other on the bank side adjacent to the Great Bahama Bank. The Marine Bank Side Regime is the largest in the area. Hatch marks on the island indicate the location of large freshwater lens formations on the islands.
Figure 1. Regimes around Great Exuma and Little Exuma are based on depth and salinity. There is a small estuarine regime characterized by variable salinities and tidal influence, and much larger marine regimes, one on the open ocean side adjacent to Exuma Sound, and the other on the bank side adjacent to the Great Bahama Bank. The Marine Bank Side Regime is the largest in the area. Hatch marks on the island indicate the location of large freshwater lens formations on the islands.
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Figure 2. Complete biotope map for Great Exuma and Little Exuma Islands. The nearshore benthic and shoreline colors are shown to illustrate the ecological complexity of natural communities around the islands. Supplemental S1 provides a full description of the biotopes by regime.
Figure 2. Complete biotope map for Great Exuma and Little Exuma Islands. The nearshore benthic and shoreline colors are shown to illustrate the ecological complexity of natural communities around the islands. Supplemental S1 provides a full description of the biotopes by regime.
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Figure 3. Percent area of biotopes by regime; colors follow same convention as biotope map shown in Figure 2. Shoreline biotopes (S) are represented in the left column; benthic biotopes (B) are in the right column. Each color is a unique biotope; legend in Figure 1 provides a list. The ocean regime of the island has the greatest diversity of biotopes.
Figure 3. Percent area of biotopes by regime; colors follow same convention as biotope map shown in Figure 2. Shoreline biotopes (S) are represented in the left column; benthic biotopes (B) are in the right column. Each color is a unique biotope; legend in Figure 1 provides a list. The ocean regime of the island has the greatest diversity of biotopes.
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Figure 4. CMECS classification for shoreline and tidal communities for Great Exuma Island. The Estuarine regime is characterized by a large area of complex tidal wetlands with variable salinity from shallow freshwater lens and rain inundation. The ocean side marine regime has the largest area of beach shoreline biotopes.
Figure 4. CMECS classification for shoreline and tidal communities for Great Exuma Island. The Estuarine regime is characterized by a large area of complex tidal wetlands with variable salinity from shallow freshwater lens and rain inundation. The ocean side marine regime has the largest area of beach shoreline biotopes.
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Figure 5. CMECS classification for benthic nearshore (NS) communities for Great Exuma Island. The largest area of nearshore communities is found on the bank side of the marine regime, extending out into the Great Bahama Bank. Communities are dominated by sandy bottom communities with less than 10% algal cover. The ocean side of the island includes the majority of coral reef communities including patch reefs and hard bottom; this NS regime includes Elizabeth Harbour and many coves and embayments. The Estuarine regime has a small benthic component as much of this area is dominated by tidal wetlands.
Figure 5. CMECS classification for benthic nearshore (NS) communities for Great Exuma Island. The largest area of nearshore communities is found on the bank side of the marine regime, extending out into the Great Bahama Bank. Communities are dominated by sandy bottom communities with less than 10% algal cover. The ocean side of the island includes the majority of coral reef communities including patch reefs and hard bottom; this NS regime includes Elizabeth Harbour and many coves and embayments. The Estuarine regime has a small benthic component as much of this area is dominated by tidal wetlands.
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Table 1. Summary of shoreline biotopes in each of the three regimes for Great Exuma, The Bahamas. The shoreline biotopes are grouped by beach, rocky shore, and mangrove communities.
Table 1. Summary of shoreline biotopes in each of the three regimes for Great Exuma, The Bahamas. The shoreline biotopes are grouped by beach, rocky shore, and mangrove communities.
Estuarine Regime
Beach
Biotopes		Rocky Shore
Biotopes		Mangrove
Biotopes		Total
Total Area (km2)28.90313.306132.466474.66
Number of Polygons429225258
Mean Area (km2)7.210.8027.2525.09
Nearshore Marine—Ocean Side
BeachRocky ShoreMangroveTotal
Total Area (km2)566.751155.623840.125562.50
Number of Polygons73242361676
Mean Area (km2)7.764.7710.638.22
Nearshore Marine—Bank Side
BeachRocky ShoreMangroveTotal
Total Area (km2)68.05677.973366.094112.13
Number of Polygons19114217350
Mean Area (km2)3.585.9415.5111.74
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Sealey, K.S.; Patus, J. Application of Standard Ecological Community Classification (CMECS) to Coastal Zone Management and Conservation on Small Islands. Land 2025, 14, 1939. https://doi.org/10.3390/land14101939

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Sealey KS, Patus J. Application of Standard Ecological Community Classification (CMECS) to Coastal Zone Management and Conservation on Small Islands. Land. 2025; 14(10):1939. https://doi.org/10.3390/land14101939

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Sealey, Kathleen Sullivan, and Jacob Patus. 2025. "Application of Standard Ecological Community Classification (CMECS) to Coastal Zone Management and Conservation on Small Islands" Land 14, no. 10: 1939. https://doi.org/10.3390/land14101939

APA Style

Sealey, K. S., & Patus, J. (2025). Application of Standard Ecological Community Classification (CMECS) to Coastal Zone Management and Conservation on Small Islands. Land, 14(10), 1939. https://doi.org/10.3390/land14101939

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