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

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Islands with a minimum mapping unit (MMU) of 1000 m 2 . The fundamental difference in the St. John scheme is the deviation from coral-centric classification rules to a biological dominance scheme in which benthic habitats were classified based on the dominant biological cover type present on each mapped feature. The importance of describing the percent cover of live coral, however, was maintained by the introduction of a new map attribute Percent Coral Cover. This attribute describes the percent live coral cover for every feature at the scale of diver observation in the water, with no regard to dominant biological cover (Zitello et al. 2009). Maps of habitat structure, a relatively coarse habitat classification using dominant cover types, was found to be most appropriate for predicting differences in fish assemblage composition (i.e., mangrove, seagrasses/algae, colonized hardbottom and unvegetated sediments) in SW Puerto Rico (Pittman et al. 2010) and to classify optimal seascapes for fish (Pittman et al. 2007b). When combined with information on topographic complexity of the seafloor the benthic habitat maps at the habitat type level were able to accurately predict the spatial patterns of fish species richness in the U.S. Virgin Islands and SW Puerto Rico (Pittman et al. 2007a). Furthermore, in the same region, combining geomorphological zones and habitat structure proved useful for explaining the across-shelf size dependent distributions for fish (Christensen et al. 2003). 1.10.2 SPATIAL CHARACTERIZATION USING MARINE AND COASTAL CLASSIFICATIONS Classification schemes and associated maps are indispensible to environmental managers in providing the baseline information on the distribution of natural features, including species 14
distributions, both within and surrounding their jurisdictions. Spatial characterizations can be species-centered, biological community centered, can represent bioregions and can be derived from geophysical or chemical variables and more recently have extended to characterize human use patterns and threats to ecosystems. The most common data types used for baseline characterizations in the marine environment are benthic habitat maps and landcover maps in terrestrial environments. Thematic habitat maps are typically developed from interpretation of remotely sensed data (space-, air- or ship-based) guided by georeferenced in situ samples to define classes or through spatial interpolation of georeferenced in situ samples. In many instances the ecological relevance of mapped classes is unclear and much work is required to determine the relationship between the spatial distributions of habitat classes and the distribution of other ecological attributes including species and biological communities. In the Bahamas, Mumby et al. (2008) found that approximately 25-30% of benthic invertebrate species and fish were associated with a single habitat class, yet they determined that all classes (n=11) were needed if the management objective was to represent all species in the seascape. In the same region, Harborne et al. (2008) found that although each habitat class supported a distinct assemblage of fish, the efficacy of mapped habitats as surrogates for fish communities was limited by intra-habitat variability that increased with geographical scale. The relevance of mapped classes to biological communities, however, can be dependent on the mapping tools applied and the variables measured. In southern England, Eastwood et al. (2006) determined that benthic classifications of soft sediments derived from side-scan sonar were not effective at classifying biological assemblages. Similarly, Stevens and Connolly (2004) found that abiotic surrogates classified from underwater video transects in Moreton Bay, Australia, were not good surrogates for patterns of marine biodiversity. In northern Australia, however, 15
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 and 12: conservation practitioners, industr
Page 13: levels of the hierarchy are defined
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
Page 63 and 64: 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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