1 1.10 Application of estuarine and coastal classifications in marine ...

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habitat types for national, regional and local levels; and 6) identifying and documenting the character and distribution of the most threatened habitat types in Europe. In the U.S., a variety of coastal classifications have been developed to describe local or regional ecological systems and address local objectives. In response to the need for a single classification standard that is relevant to all U.S. coastal and marine environments and that can be applied on local, regional and continental scales, NOAA and NatureServe developed the Coastal Marine Ecological Classification Standard (CMECS) (Madden et al. 2005, Madden and Grossman 2008). The classification is described as an ecosystem-oriented, science-based framework developed to allow effective identification, monitoring, protection, and restoration of unique biotic assemblages, protected species, critical habitat, and important ecosystem components. The hierarchical framework contains six nested levels; each containing clearly defined classes and units as follows: Level 1 Regime classes are differentiated by a combination of salinity, geomorphology and depth; Level 2 Formation are large physical structures formed by either water or solid substrate within systems; Level 3 Zone classes include the water column, littoral or sea bottom; Level 4 Macrohabitat classes are large physical structures that contain multiple habitats; Level 5 Habitat classes are a specific combination of physical and energy characteristics that creates a suitable place for colonization or use by biota; Level 6 Biotope classes represent the characteristic biology associated with a specific habitat. The hierarchy is conceptually divided into two parts based on the kinds of data required for applying the classification. Data for the upper levels, Regime through Zone can be captured from maps, bathymetry, remote imagery and existing historical data. In contrast, the lower levels, Macrohabitat though Biotope, exist at local spatial scales and data collection is done through finer resolution remote sensing, field observation and direct measurement. Linkages between 12
levels of the hierarchy are defined by ecosystem processes and by spatial relationships. Stated management utility includes: 1) Delineation of regions for marine protected areas and developing guidelines for their management; 2) Identification of important habitats and critical hotspots for conservation; 3) Identification of Essential Fish Habitat (EFH); and 4) Forming a scientific basis for the development, implementation and monitoring of ecosystem-based management strategies for coastal systems (Madden and Grossman 2008). For threatened and vulnerable shallow-water coastal ecosystems such as tropical coral reefs, habitat mapping is essential for the development of effective marine management plans including MPA site selection and other conservation prioritization activities. Information gained from coral reef mapping includes identifying essential fish habitat and other ecologically sensitive areas for protection, calculating volumetric or area measurements of anthropogenic impacts, identifying reef gaps for submarine cable placement, and locating areas for artificial reef enhancement. To address multiple management and research objectives, NOAA’s Benthic Habitat Classification for Puerto Rico and the U.S. Virgin Islands (Kendall 2001) was developed with a hierarchical structure that integrates four levels of classification for mapping coral reef ecosystems including: 1) Geomorphological zone (e.g., forereef, bank etc.); 2) Habitat structure (e.g., colonized hardbottom); 3) Habitat type (e.g., linear reef, seagrass) and 4) Modifiers used to show the proportion (% cover) of area coverage for macroalgae and seagrasses. A hierarchical structure means that different analyses and different levels of features can be utilized for different levels of management decision making. For example, the percentage seagrass cover was used as a variable for quantifying changes in the spatial distribution of seagrasses and the impact from hurricanes over 30 years (Kendall et al. 2004). In 2008, a new classification was developed for application to finer resolution benthic habitat maps for St John in the U.S. Virgin 13
Page 1 and 2: 1.10 Application of estuarine and c
Page 3 and 4: SYNOPSIS Coastal and marine classif
Page 5 and 6: government and non-governmental man
Page 7 and 8: paucity of species and habitat data
Page 9 and 10: and many sub-catastrophic disturban
Page 11: conservation practitioners, industr
Page 15 and 16: distributions, both within and surr
Page 17 and 18: In a hierarchical framework for the
Page 19 and 20: 1.10.2.3 Australian Coastal Classif
Page 21 and 22: Ecological theory predicts that the
Page 23 and 24: outbreaks in the late 1970s (Green
Page 25 and 26: intertidal zones, and shallow coast
Page 27 and 28: 1.10.3.1 Identifying Priority Conse
Page 29 and 30: y the Massachusetts Oceans Act (200
Page 31 and 32: eight color coded zones to provide
Page 33 and 34: appropriate place to investigate fe
Page 35 and 36: 1.10.4.3 Massachusetts Ocean Plan T
Page 37 and 38: One of the foundational concepts un
Page 39 and 40: ecosystems has shown that considera
Page 41 and 42: In May 2004, Germany was the first
Page 43 and 44: improve the design and interpretati
Page 45 and 46: NOAA’s CoastWatch Change Analysis
Page 47 and 48: ground resolution of 30 m. Each cla
Page 49 and 50: also be used to assess the role of
Page 51 and 52: States (Gundlach and Hayes 1978). T
Page 53 and 54: information at the species level. I
Page 55 and 56: 1.10.8.4 Classifying and Mapping Hu
Page 57 and 58: map of the entire Australian shorel
Page 59 and 60: within 11 regions, leading to an ov
Page 61 and 62: enhancement of certain functions in
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achieved by identifying barriers to
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ecosystem service values extracted
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1.10.12 FUTURE DIRECTIONS AND PRIOR
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1.10.12.1 Linking Patterns and Proc
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approach. New classifications will
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Arundel, H. and Mount, R. 2007. Nat
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Connell, J. H. 1978. Diversity in t
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Duke. N.C., Meynecke, J.O., Dittman
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Green, A.L., C.E. Birkeland, R.H. R
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Hiddink, J. G., Jennings, S., Kaise
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Kostylev, V., Todd, B.J., Fader, G.
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Maxwell, D.L., Stelzenmüller, V.,
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Spatial and temporal patterns in fi
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Sharples, C. 2006. Indicative Mappi
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Wells, S., Ravilous, C., Corcoran,
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FIGURE LEGENDS Figure 1. A) Classes
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Figure 10. Ecological evaluation in
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Figure 21. Combining 'intolerance'
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selected planning units in gray ins
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Box 2. Classifications as thematic
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Figure 1. 1
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Figure 3. 3
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Figure 5. 5
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Figure 7. 7
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Figure 9. 9
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Figure 11. 11
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Figure 13. 13
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Figure 15. Fishing effort (hrs/day)
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Figure 17. 17
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Figure 19. 100% Conversion. 80% 60%
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Figure 21. 21
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Figure 23. 23
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Figure 25. 25
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Figure 27. 27
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Figure 29. 29
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Figure 31. 31
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Figure 33. 33
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