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

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sources. The majority of our examples are focused on sub-national level classifications and associated management applications rather than global or national level, although we acknowledge the importance of nested classifications to facilitate consistency in regional, national and international assessments and management decision making. 1.10.1.1 Importance of Spatial, Temporal and Thematic resolution In addition to spatial extent, the three attributes of a map that impinge most on the appropriateness of a spatial classification for management application are: 1) spatial resolution; 2) temporal resolution, and 3) thematic resolution; all of which can influence the application, cost-effectiveness and feasibility of map production (Fassnacht et al. 2006, Kendall and Miller 2008). Thematic resolution is influenced by the scale at which the environment is sampled and changing the number of classes can influence the patterning, be it benthic seascape or ecosystem service values, as much as changing the spatial resolution. It is often perceived that higher thematic resolution (i.e., higher number of classes) that creates highly specialized categories can potentially offer greater predictive power, but the predictive performance of categorical data really depends on what is being predicted. Spatial resolution and thematic resolution, as well as, post-classification techniques such as smoothing can greatly impact the representation of rare and fragmented ecosystems and this has considerable implications for maps directed at site prioritization in marine conservation (Thompson and Gergel 2008). Furthermore, the static nature of most classifications is an issue when applied to dynamic marine environments. Marine environments can be modified significantly by human activities, storms and swell events, disease 8
and many sub-catastrophic disturbances at temporal scales that are markedly finer than those intervals that typically exist for the updating of maps. 1.10.1.2 Utility of Hierarchical Classification Schemes In many cases, hierarchical classification schemes have been developed to add more flexibility for the user, particularly when manipulated in a GIS, thereby facilitating the utility for both management applications and ecological applications. For example, the British Columbia Marine Ecological Classification includes Ecozone (e.g., Pacific) as the broadest level in the hierarchy, then nested at progressively finer thematic resolution are the Ecoprovince (e.g., Pacific shelf and mountains); Ecoregion (e.g., Outer Pacific Marine Shelf); Ecosection (e.g., Queen Charlotte Sound) and finally the Ecounit, based on data for wave exposure, depth, subsurface relief, currents and substrate type (Zacharias et al. 1998). This hierarchical structure is important because ecological patterns and processes are multi-scale and management actions occur across a hierarchy of spatial scales (Wiens 2000). Roff et al. (2003) provided five important considerations for the development of a generalized hierarchical habitat classification scheme: 1.) the availability of data capable of discriminating meaningful habitat classes; 2.) redundancy in discriminating variables may occur and surrogates can be identified; 3.) discriminatory function of variables may be scale dependent (i.e., salinity may work well at one level but not another), 4.) habitat types at upper levels of the hierarchy should be more distinct from one another than those at lower levels, and 5.) the importance of discriminatory variables may vary geographically (i.e., East Pacific variables may not all be applicable to the west Atlantic) (see also Roff and Taylor 2000). 9
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: paucity of species and habitat data
Page 11 and 12: conservation practitioners, industr
Page 13 and 14: levels of the hierarchy are defined
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
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within 11 regions, leading to an ov
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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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