Elsevier

Ocean & Coastal Management

Volume 136, February 2017, Pages 185-195
Ocean & Coastal Management

Spatial diversity of a coastal seascape: Characterization, analysis and application for conservation

https://doi.org/10.1016/j.ocecoaman.2016.12.002Get rights and content

Highlights

  • The shallow Yucatan coast (SYC) presents a high seascape complexity.

  • This complexity reflects the impact human activities have had in the SYC.

  • Coastal habitats occur as bands parallel to the coastline at a gradual transition.

  • Three of the seven habitats are proposed as conservation-priority areas.

  • Spatial and seascape analysis jointly help the management of marine ecosystems.

Abstract

Recent conservation approaches have focused on the landscape as either a conservation target or a mechanism by which conservation can be achieved. A seascape is a spatially heterogeneous surface that is generally represented as a mosaic of patches (homogeneous units of natural vegetation) with spatial and functional relationships that are organized as puzzle pieces, which represent one or several ecosystems. Spatial analysis using a landscape ecology approach offers a wide range of tools to study, monitor, manage, and conserve these areas. The objective of this study was to identify the benthic community and spatially characterize the submarine habitats of the shallow coast along the Yucatan, Mexico, to identify priority conservation areas. The study area was divided into 3 zones based on their environmental qualities, and a total of 290 sampling sites were defined from a stratified random sample based on the unsupervised classification of Landsat ETM+ images. For each site, a video was taken; the substrate type was identified; and the organisms present were identified to the lowest possible taxonomic level. Training groups were defined by ordination analysis for the supervised classification of spectral bands and bathymetric modeling to obtain maps of the seascape, and the composition and configuration of the seascape were analyzed using spatial diversity metrics and indices. A total of 40 benthic morphotypes, predominantly brown algae and seagrass, were identified. Seven habitat types were defined along the coast based on the arrangement and spatial organization of the benthic community: bare substrate (A), sand with seagrass (B), seagrass meadow (C), seagrass with macroalgae (D), macroalgae on sand (E), flagstone with macroalgae (F), and macroalgal forest (G). The spatial configuration of the coastal seascape reflected the geomorphological characteristics of the study area and was significantly different among the three zones. Habitats G and F were present everywhere along the coast and dominated the seascape, whereas habitat C only occurred in Zone 3. Due to their structural complexity and biological richness, habitats C, D, F, and G are potentially critical for turtle, grouper, octopus, and lobster species, so these habitats are suggested as priority conservation areas to promote the conservation of these species as well as the productivity and functionality of these ecosystems.

Introduction

Since the 1990's, conservation perspectives have focused on landscapes either as conservation goals or as the mechanisms by which conservation can be achieved (Franklin, 1993). This new approach has stimulated awareness of the importance of surface heterogeneity, spatial patterns, and large-scale disturbances (Noss, 1983, Redford et al., 2003). The idea has been transformed from “conserve species” to “conserve spaces” with the aim of maintaining biological richness by promoting the conservation of space (Noss, 1990, Roff and Evans, 2002).

The landscape concept refers to a mosaic of elements (patches, corridors and a matrix) arranged in a given proportion, number, shape, location and area that characterize a particular territory (Morera et al., 2007) and represent natural habitats, cover types or land uses. This concept arose as a result of the interactions between abiotic conditions (i.e., climate, topography, and soils), biotic conditions, anthropogenic activities and the dynamics of natural disturbances that could be observed and evaluated from any scale (Forman, 1995).

The patches in marine landscapes (seascape) contain spatial variations in substrate types, nutrients, depths, and natural disturbances (McGarigal and Cushman, 2005, Pittman et al., 2011). According to Boström et al. (2011), the seascape configuration is a mosaic of patches where submerged aquatic vegetation is distributed as islands embedded in a matrix (Patch-matrix model), as a collection of patches of different types where the interaction of the parts influences the ecological function of the entire mosaic (Patch-mosaic model) (Wiens, 1997, Collinge et al., 2003) or as a continuum of patches without distinguishable boundaries, based on a projection of the morphological characteristics of the underwater territory (Gradient model) (Cushman and McGarigal, 2003, Pittman et al., 2009).

Heterogeneity and complexity are two key concepts in the study of landscapes. Heterogeneity represents horizontal variation in the physiognomy of habitats present in a given area, and complexity describes the development of vertical strata within a particular habitat (Mac Arthur and Wilson, 1967, August, 1983). In any natural landscape, heterogeneity and structural complexity are based on factors such as geomorphology, hydrology, and climate (Lugo-Hubp et al., 1992, Solleiro-Rebolledo et al., 2011) and can be used to define the distribution of ecosystems, the regulation of matter and energy flows, and the distribution of species and environmental services (Bradley and Maher, 2001, Rodríguez-Loinaz, 2004, Vila Subirós et al., 2006).

According to Gratwicke and Speight (2005) and other authors, complexity is positively related to wildlife diversity. Structurally complex habitats provide a greater number of niches and resources that increase biodiversity (McCoy and Bell, 1991, Tews et al., 2004). Thus, biodiversity is always linked to a habitat (Walz and Syrbe, 2013), which is the space with biotic and abiotic properties where an organism, population, or community lives. Habitats are differentiated according to their biotic and structural compositions (McCoy and Bell, 1991).

In the context of the landscape, heterogeneity represents the horizontal variation in the physiognomy of the habitats present in an area (Mac Arthur and Wilson, 1967, August, 1983), and a heterogeneous region is characterized by its high richness (number of habitats) and abundance (patches per habitat) (Gratwicke and Speight, 2005). In this sense, habitat heterogeneity in this study refers to the extent (area in km2) and diversity (number) of habitat types.

On a global scale, the effects of anthropogenic activities and processes can bring about changes in habitat structures, decreases in habitat complexity and as a result, changes in the population structure and community composition (Thompson, 2005). Coastal environments do not escape the effects of anthropogenic activities. These environments are very important for secondary productivity, the transfer of matter and energy in the food web, and coastal biodiversity; however, many of the environments are located in the vicinity of densely populated regions (Weslawski et al., 2004, Lotze et al., 2006) and as a result are subject to stressors, such as eutrophication, dredging and overfishing, which generate a loss of diversity and a decrease in the quality of ecosystem services (Hughes et al., 2009, Boström et al., 2011, Watson et al., 2014).

The Aichi Biodiversity Targets for 2020 include the incorporation of at least 17% more protected terrestrial areas; 10% more inland, coastal, and marine water areas; and the restoration of at least 15% of degraded ecosystems (Convention on Biological Diversity, 2010). For 2014, approximately 10.1 million km2 (3% of the total area) of marine environments around the world were estimated to be located within protected natural areas, of which approximately 6.6% were in exclusive economic zones (Watson et al., 2014).

This situation has generated a growing need to identify the constituent factors of heterogeneity and complexity that influence species richness and abundance (Mörtberg et al., 2007, Pittman et al., 2009, Jörgensen et al., 2015). Therefore, one of the goals and objectives of environmental programs and plans is to promote the sustainable use of resources without jeopardizing biodiversity while maintaining habitat integrity (Hole et al., 2009). Key pieces include identifying the composition and distribution of communities and the characterization of the space where they are distributed (i.e., their habitats) (Steltzenmüller et al., 2013) to enable protected areas to be managed as a coherent network and not as isolated islands.

The Shallow Yucatan Coast of Mexico (SYC) is bordered entirely by environments of high ecological value (García-Frapolli et al., 2009). More than 60% of the coastal territory is included within the two Biosphere Reserves (Celestún and Ría Lagartos) and two state jurisdiction Protected Natural Areas (El Palmar and Bocas de Dzilam) (García de Fuentes et al., 2011); all four environments are recognized by the Convention on Wetlands of International Importance (RAMSAR).

Approximately 20% of the marine coast and lagoons of the State are associated with anthropogenic activities. Urban development and resource extraction exert strong pressures on biotic elements, resulting in changes in the structure and composition of the flora and fauna communities of the coastal seabeds and the functions of the ecosystems (Gobierno del Estado de Yucatán, 2007, Herrera-Silveira et al., 2010).

Considering the biological and scenic richness of sites such as the SYC, sustainable and objective management strategies that ensure the maintenance of marine diversity and ecosystem services are urgently needed. Therefore, the objectives of this work were to identify the benthic community, characterize the submerged habitats, and distinguish priority areas for conservation.

Section snippets

Study area

The SYC is delimited as a polygon that is 198 km in length with variable amplitudes up to 13 m in depth and a total surface area of 464,432.75 Ha (Fig. 1).

Three regions were distinguished based on the environmental quality of the SYC (Herrera-Silveira and Morales-Ojeda, 2009): to the west, from the town of Celestún to the village of Sisal; the central portion, from Sisal to Telchac Puerto; and to the east, from Telchac Puerto to the town of Dzilam de Bravo; these regions are designated as Zone

Biological richness and spatial characterization of the habitats

The SYC has an extent of close 465, 000 ha. The disposition and spatial arrangement of the benthic community and the associated substrate identified seven habitat types along the coastline: bare substrate (A), sand with seagrass (B), seagrass meadows (C), seagrass with macroalgae (D), macroalgae on sand (E), flagstone with macroalgae (F), and macroalgal forest (G) with B being the smaller habitat and E and G being the largest, covering more than 70% of the total vegetated area of the SYC (

Discussion

Coastal areas are dynamic regions whose spatial configuration favors diverse resources and environmental services (Cumming and Spiesman, 2006), but most of the works in these areas have focused on the study of a particular ecosystem, namely, seagrass (49%) (e.g., Boström et al., 2006, Meynecke et al., 2007), marshes (32%) (e.g., Fleeger et al., 2008), coral reefs (11%) (e.g., Andréfouët et al., 2001), mangroves (6%) (e.g., Manson et al., 2005), or oyster reefs (2%) (e.g., Peterson et al., 2003).

Conclusions

Seascapes are analogous to landscapes, but few studies have investigated the influence of spatial pattern on ecological processes. Therefore, understanding these processes at the level of the seascape is one of the pressing needs in the field of environmental management (Mumby, 2006, Grober-Dunsmore et al., 2009).

Identifying and characterizing essential spaces for the life cycle of species of commercial interest, such as octopuses, groupers, or lobsters in the SYC, is key to the success of

Author contributions

Design and direction of the study: MALC; data collection and mapping of the data analysis: EBPJ and MALC; writing of the manuscript: EBPJ and MALC. Both authors contributed equally to the development of this document.

Conflicts of interest

The authors have no conflicts of interest to declare.

Role of the funding source

Support for scientific research and environmental management of the Shallow Yucatan Coast, Mexico.

Funding

A Mixed Fund by CONACYT-State Government of Yucatan, Mexico supported this work (Project No. 108960). Infrastructure and logistical support was provided by the Laboratory of Remote Sensing and Geographic Information Systems of the Center of Research and Advanced Studies, National Polytechnic Institute, Mexico.

Acknowledgements

The authors thank the National Council for Science and Technology (CONACYT), Mexico (grant number 171610); Consuelo Díaz-Aguilar for her valuable support in the field; and Jorge Montero-Muñoz and Gilberto Acosta-González for their invaluable contributions to this document. Thanks are also due to reviewers for their useful comments and suggestions.

References (128)

  • J.W. Fleeger et al.

    Topdown and bottom-up control of infauna varies across the salt marsh landscape

    J. Exp. Mar. Biol. Ecol.

    (2008)
  • E. García-Frapolli et al.

    The complex reality of biodiversity conservation through natural protected area policy: three cases from the Yucatan Peninsula, Mexico

    Land Use Policy

    (2009)
  • J.W. Hackney et al.

    Size–frequency patterns in morphometric characteristics of the seagrass Thalassia testudinum reflect environmental variability

    Ecol. Indic.

    (2004)
  • P.T. Harris et al.

    High seas marine protected areas: benthic environmental conservation priorities from a GIS analysis of global ocean biophysical data

    Ocean Coast. Manag.

    (2009)
  • V. Hernández-García et al.

    On the reproduction of octopus vulgaris of the coast of the Canary Islands

    Fish Res.

    (2002)
  • J.A. Herrera-Silveira et al.

    Evaluation of the health status of a coastal ecosystem in southeast Mexico: assessment of water quality, phytoplankton and submerged aquatic vegetation

    Mar. Pollut. Bull.

    (2009)
  • K. Hutcheson

    A test for comparing diversities based on the Shannon formula

    J. Theor. Biol.

    (1970)
  • T.L. Jörgensen et al.

    Spatial variability in habitat structure and heterogenic coral reef fish assemblages inside a small-scale marine reserve after a coral mass mortality event

    Ocean Coast. Manag.

    (2015)
  • W. Leujak et al.

    Comparative accuracy and efficiency of six coral community survey methods

    J. Exp. Mar. Biol. Ecol.

    (2007)
  • F.J. Manson et al.

    A broad scale analysis of links between coastal fisheries production and mangrove extent: a case-study for northeastern Australia

    Fish Res.

    (2005)
  • U.M. Mörtberg et al.

    Landscape ecological assessment: a tool for integrating biodiversity issues in strategic environmental assessment and planning

    J. Environ. Manag.

    (2007)
  • P.J. Mumby

    Connectivity of reef fish between mangroves and coral reefs: algorithms for the design of marine reserves at seascape scales

    Biol. Conserv.

    (2006)
  • D. Pelletier et al.

    Comparison of visual census and high definition video transects for monitoring coral reef fish assemblages

    Fish. Res.

    (2011)
  • S.J. Pittman et al.

    Predictive mapping of fish species richness across shallow-water seascapes in the Caribbean

    Ecol. Model.

    (2007)
  • M. del C. Alejo-Plata et al.

    Reproducción, dieta y pesquería del pulpo octopus (octopus) hubbsorum (Mollusca: Cephalopoda) en la Costa de Oaxaca, México

    Rev. Biol. Trop.

    (2009)
  • R.G. Allen

    FAO. Species catologue

  • C.M. Appendini et al.

    Longshore sediment transport on the Northern coast of the Yucatan Peninsula

    J. Coast. Res.

    (2012)
  • N. Aranda-Cirerol

    Eutrofización y calidad del agua de una zona costera Tropical

    (2004)
  • R.B. Aronson et al.

    Video surveys of coral reefs: uni- and multivariate applications

  • F. Arreguín-Sánchez et al.

    Population dynamics and stock assessment for Octopus maya (Cephalopoda: Octopodidae) fishery in the Campeche Bank

    Gulf Mexico. Rev. Biol. Trop

    (2000)
  • P.V. August

    The role of habitat complexity and heterogeneity in structuring tropical mammal communities

    Ecology

    (1983)
  • G.A. Baldassarre et al.

    A review of the ecology and conservation of Caribbean flamingos in Yucatan, Mexico

    Waterbirds

    (2000)
  • J. Bello-Pineda et al.

    Incorporating GIS and MCE for suitability assessment modelling of coral reef resources

    Environ. Monit. Assess.

    (2006)
  • C. Boström et al.

    Seascape ecology of coastal biogenic habitats: advances, gaps, and challenges

    Mar. Ecol. Prog. Ser.

    (2011)
  • D.E. Bradley et al.

    Mapping ecosystem processes and function across shallow seascapes

    Contin. Shelf Res.

    (2001)
  • T. Brulé et al.

    Composición de las capturas comerciales del complejo mero-pargo en el sureste del Golfo de México e implicaciones para el manejo de su pesquería

  • R.J. Buesa et al.

    Larval Transmigration in the Caribbean Spiny Lobster (Panulirus argus) Populations

    (2007)
  • L. Capurro et al.

    Manejo sustentable del ecosistema costero de Yucatán

    Av. Perspect.

    (2002)
  • J. Carabias Lillo et al.

    Programa de Manejo Reserva de la Biósfera Ría Lagartos

    (1999)
  • L.B. Chico et al.

    Effects of algal turf and sediment on coral settlement

    Mar. Pollut. Bull.

    (2005)
  • E. Chuvieco et al.

    Fundamentals of Satellite Remote Sensing

    (2009)
  • K.R. Clarke et al.

    Primer v6: User Manual/Turorial

    (2006)
  • K.R. Clarke et al.

    Change in Marine Communities: an Approach to Statistical Analysis and Interpretation

    (2001)
  • C.B. Cogan et al.

    The role of marine habitat mapping in ecosystem-based management

    ICES J. Mar. Sci. J. Conseil

    (2009)
  • S.K. Collinge et al.

    Effects of local habitat characteristics and landscape context on grassland butterfly diversity

    Conserv. Biol.

    (2003)
  • Convention on Biological Diversity

    COP 10 Decision X/2: Strategic Plan for Biodiversity 2011–2020

    (2010)
  • A. Copeland et al.

    Marine habitat mapping in support of marine protected area management in a subarctic fjord: Gilbert Bay, Labrador, Canada

    J. Coast. Conserv.

    (2013)
  • R. Costanza et al.

    What is a healthy ecosystem?

    Aquat. Ecol.

    (1999)
  • E. Cuevas et al.

    Spatial characterization of a foraging area for immature hawksbill turtles (Eretmochelys imbricata) in Yucatan, Mexico

    Amphib. Reptil.

    (2007)
  • E. Cuevas et al.

    Influence of beach slope and width on hawksbill (Eretmochelys imbricata) and green turtle (Chelonia mydas) nesting activity in El Cuyo, Yucatan, Mexico

    Chelonian Conserv. Biol.

    (2010)
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