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

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Box 1. Definitions of ecosystem-based management and marine spatial planning. Ecosystem-based management (EBM) and integrated marine spatial planning (MSP) have recently emerged as strategic priorities for many natural resource stewardship agencies around the world, with the overall objective of managing diverse marine uses in a comprehensive and sustainable way using a holistic and spatiallyexplicit framework (Douvere and Ehler 2009). OSPAR (Commission for the Protection of the Marine Environment of the Northeast Atlantic) defines ecosystem-based management as: “The comprehensive integrated management of human activities based on the best available scientific knowledge about the ecosystem and its dynamics, in order to identify and take action on influences which are critical to the health of marine ecosystems, thereby achieving sustainable use of goods and services and maintenance of ecosystem integrity”. NOAA defines an ecosystem approach to management (EAM) as: “A geographically specified, adaptive approach that takes account of ecosystem knowledge and uncertainties, considers multiple external influences, and strives to balance diverse societal objectives”. The UK government defines the purpose of MSP as: “The creation of a strategic marine planning system that will clarify marine objectives and priorities for the future, and direct decisionmakers and users towards more efficient, sustainable use and protection of marine resources” (Defra, 2007). 100
Box 2. Classifications as thematic maps. Classifications as thematic maps Classes of environmental data including social data within a known geographical location can be represented as a map to create a spatially explicit classification schemes or thematic map. This helps to organize, visualize and analyze diverse information in a systematic, transparent, cost-effective and operationally meaningful way to support efficient management decision making. • Classes can be a single textual descriptor or a numeric value or a range of values and can be derived from expert opinion or numerically through a multivariate group i.e. “cluster group” based on a statistical classifier or some combination • When mapped, classes are usually composed of a number of discrete and spatially homogeneous units that are assigned to grid cells or represented as polygons with discrete boundaries in a Geographical Information System (GIS) • The map accuracy, spatial and temporal resolution, geographical extent and thematic resolution (i.e. detail of the classes) are important consideration when applying classifications to support management decision making 101
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1.10 Application of estuarine and c
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SYNOPSIS Coastal and marine classif
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government and non-governmental man
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paucity of species and habitat data
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and many sub-catastrophic disturban
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conservation practitioners, industr
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levels of the hierarchy are defined
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distributions, both within and surr
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In a hierarchical framework for the
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1.10.2.3 Australian Coastal Classif
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Ecological theory predicts that the
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outbreaks in the late 1970s (Green
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intertidal zones, and shallow coast
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1.10.3.1 Identifying Priority Conse
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y the Massachusetts Oceans Act (200
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eight color coded zones to provide
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appropriate place to investigate fe
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1.10.4.3 Massachusetts Ocean Plan T
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One of the foundational concepts un
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ecosystems has shown that considera
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In May 2004, Germany was the first
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improve the design and interpretati
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NOAA’s CoastWatch Change Analysis
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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
Page 65 and 66: ecosystem service values extracted
Page 67 and 68: 1.10.12 FUTURE DIRECTIONS AND PRIOR
Page 69 and 70: 1.10.12.1 Linking Patterns and Proc
Page 71 and 72: approach. New classifications will
Page 73 and 74: Arundel, H. and Mount, R. 2007. Nat
Page 75 and 76: Connell, J. H. 1978. Diversity in t
Page 77 and 78: Duke. N.C., Meynecke, J.O., Dittman
Page 79 and 80: Green, A.L., C.E. Birkeland, R.H. R
Page 81 and 82: Hiddink, J. G., Jennings, S., Kaise
Page 83 and 84: Kostylev, V., Todd, B.J., Fader, G.
Page 85 and 86: Maxwell, D.L., Stelzenmüller, V.,
Page 87 and 88: Spatial and temporal patterns in fi
Page 89 and 90: Sharples, C. 2006. Indicative Mappi
Page 91 and 92: Wells, S., Ravilous, C., Corcoran,
Page 93 and 94: FIGURE LEGENDS Figure 1. A) Classes
Page 95 and 96: Figure 10. Ecological evaluation in
Page 97 and 98: Figure 21. Combining 'intolerance'
Page 99: selected planning units in gray ins
Page 103 and 104: Figure 1. 1
Page 117 and 118: Figure 15. Fishing effort (hrs/day)
Page 121 and 122: Figure 19. 100% Conversion. 80% 60%
Page 135: Figure 33. 33
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