1 1.10 Application of estuarine and coastal classifications in marine ...
1 1.10 Application of estuarine and coastal classifications in marine ... 1 1.10 Application of estuarine and coastal classifications in marine ...
environmental conditions beyond the expected range, and “vulnerability” as the probability that a feature will be exposed to a stress to which it is sensitive. Another related term is “recoverability”, defined as the ability of a habitat, community or species to return to a state close to that which existed before the activity or event caused change. With appropriate spatial information these definitions can be represented spatially as classes within a thematic map. The identification and classification of areas based on the sensitivity of species and habitats for use in management planning requires access to extensive biophysical and socio-economic data usually for both land and sea together with interpretation of data in a comprehensive, consistent and structured way (Tyler-Walters and Jackson 1999, Hiscock and Tyler-Walters 2006). Thus, the process of classifying risk is continually evolving to incorporate best available information on the biological responses to disturbance. In Europe, work is underway to determine the most suitable indicator species to represent community level sensitivity to specific types of human activities occurring in specific marine biotopes (Tyler- Walters et al. 2009). Sensitivity analysis has been implemented with various qualitative, semiquantitative and quantitative approaches. Here we show examples of a selection of both qualitative and quantitative models that also integrate expert opinion in the development of sensitivity maps. 1.10.8.1 Environmental Sensitivity Index Mapping NOAA’s Environmental Sensitivity Index (ESI) Mapping, first developed in the 1970’s is an inter-agency map product coordinated by the Office of Response and Restoration that has become the most widely used approach to mapping environmental sensitivity in the United 50
States (Gundlach and Hayes 1978). The approach systematically compiles best-available information on: 1.) Shoreline type (substrate, grain size, tidal elevation, origin); 2.) Exposure to wave and tidal energy; 3.) Biological productivity and sensitivity; 4.) Human uses; and 5.) Ease of cleanup in the event of a chemical spill. The classified maps are provided as atlases for each state and jurisdiction in hard copy and digital form to be used by federal and state agencies as a starting point for prevention, planning and response actions and are considered to provide the essential information needed for effective site-specific planning, particularly in the event of a chemical spill (NOAA 1996 – ESI guidelines). Electronic versions of the ESI maps and associated descriptive information are utilized by the U.S. Coast Guard as a first phase in assessing the course of action relative to priority areas when an oil spill occurs. Some of the first ESI maps were produced for The State of Alabama in 1996 and then updated in 2007 (Figure 20). The maps incorporated dynamic characteristics of the coastal system in the prediction of the behavior and persistence of oil since the intensity of energy expended upon a shoreline by wave action, tidal currents, and river currents directly affect the persistence of stranded oil in addition to substrate type and grain size. The potential for biological injury and ease of cleanup of spilled oil are also important factors in the ESI ranking. In general, areas exposed to high levels of physical energy, such as wave action and tidal currents, and low biological activity rank low on the scale, whereas sheltered areas with associated high biological activity have the highest ranking. The “shoreline,” representing the boundary between land and water, is color-coded with the ESI classification. The distribution of biological resources is shown using many different conventions (Figure 20). The major convention is an icon associated with a point, line, or polygon that shows the species’ areal distribution. The icon’s reference number corresponds to a 51
- 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
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- Page 9 and 10: and many sub-catastrophic disturban
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- 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: also be used to assess the role of
- 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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- 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
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- Page 87 and 88: Spatial and temporal patterns in fi
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- Page 93 and 94: FIGURE LEGENDS Figure 1. A) Classes
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- Page 97 and 98: Figure 21. Combining 'intolerance'
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environmental conditions beyond the expected range, <strong>and</strong> “vulnerability” as the probability that a<br />
feature will be exposed to a stress to which it is sensitive. Another related term is<br />
“recoverability”, def<strong>in</strong>ed as the ability <strong>of</strong> a habitat, community or species to return to a state<br />
close to that which existed before the activity or event caused change.<br />
With appropriate spatial <strong>in</strong>formation these def<strong>in</strong>itions can be represented spatially as<br />
classes with<strong>in</strong> a thematic map. The identification <strong>and</strong> classification <strong>of</strong> areas based on the<br />
sensitivity <strong>of</strong> species <strong>and</strong> habitats for use <strong>in</strong> management plann<strong>in</strong>g requires access to extensive<br />
biophysical <strong>and</strong> socio-economic data usually for both l<strong>and</strong> <strong>and</strong> sea together with <strong>in</strong>terpretation <strong>of</strong><br />
data <strong>in</strong> a comprehensive, consistent <strong>and</strong> structured way (Tyler-Walters <strong>and</strong> Jackson 1999,<br />
Hiscock <strong>and</strong> Tyler-Walters 2006). Thus, the process <strong>of</strong> classify<strong>in</strong>g risk is cont<strong>in</strong>ually evolv<strong>in</strong>g to<br />
<strong>in</strong>corporate best available <strong>in</strong>formation on the biological responses to disturbance. In Europe,<br />
work is underway to determ<strong>in</strong>e the most suitable <strong>in</strong>dicator species to represent community level<br />
sensitivity to specific types <strong>of</strong> human activities occurr<strong>in</strong>g <strong>in</strong> specific mar<strong>in</strong>e biotopes (Tyler-<br />
Walters et al. 2009). Sensitivity analysis has been implemented with various qualitative, semiquantitative<br />
<strong>and</strong> quantitative approaches. Here we show examples <strong>of</strong> a selection <strong>of</strong> both<br />
qualitative <strong>and</strong> quantitative models that also <strong>in</strong>tegrate expert op<strong>in</strong>ion <strong>in</strong> the development <strong>of</strong><br />
sensitivity maps.<br />
<strong>1.10</strong>.8.1 Environmental Sensitivity Index Mapp<strong>in</strong>g<br />
NOAA’s Environmental Sensitivity Index (ESI) Mapp<strong>in</strong>g, first developed <strong>in</strong> the 1970’s is<br />
an <strong>in</strong>ter-agency map product coord<strong>in</strong>ated by the Office <strong>of</strong> Response <strong>and</strong> Restoration that has<br />
become the most widely used approach to mapp<strong>in</strong>g environmental sensitivity <strong>in</strong> the United<br />
50
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