Appendix E Prioritization of Management Options |
- Nearshore Management Strategies
- Influence of Disturbance on Management Actions
- Background to Prioritization Process
- Relevance to Bainbridge Island Nearshore
- The Prioritization Method for Bainbridge Island Nearshore
- References
The objective of the prioritization process is to develop a science-based protocol for determining priorities and strategies for improving nearshore ecosystem functions on Bainbridge Island. The process links output from the Nearshore Characterization and Assessment with the prioritization process. The process draws from the fields of restoration ecology, landscape ecology, and conservation biology. The input to the approach is based on expert opinion founded in the best available science (BAS) for the region. A companion report developed for Bainbridge Island (Williams et al., 2003) provides a discussion of the BAS for Bainbridge Island nearshore.
Nearshore Management Strategies
Five fundamental strategies for improving ecosystem functions of nearshore systems (listed in no particular order) are included in the process and form the basis for management decisions:
- Creation – Creation involves bringing into being a new ecosystem that previously did not exist on the site (NRC 1992). In contrast to restoration, creation involves the conversion of one habitat type or ecosystem into another.
- Enhancement – Enhancement means any improvement of a structural or functional attribute (NRC 1992). As noted by Lewis (1990), enhancement and restoration are often confused. Enhancement is the intentional alteration of an existing habitat to provide conditions that previously did not exist and which by consensus increase one or more attributes. Shreffler and Thom (1993) found that, for estuarine systems, enhancement often meant enhancement of selected attributes of the ecosystem, such as improving the quality or size of a tidal marsh or eelgrass meadow.
- Restoration – As defined in the scientific literature, restoration means the return of an ecosystem to a close approximation of its previously existing condition (e.g., Lewis 1990, NRC 1992). We use the term restoration to refer to any form of human intervention with the intent of improving upon the existing condition of the ecosystem or habitat. Restoration involves doing something to increase the rate of recovery over the rate of natural recovery occurring without human intervention.
- Conservation – Conservation, as defined by Meffe et al. (1994), refers to the maintenance of biodiversity. Conservation Biology is a synthetic field that applies the principles of ecology, biogeography, population genetics, economics, sociology, anthropology, philosophy and other theoretically based disciplines to the maintenance of biological diversity. Conservation can allow development to occur as long as biodiversity and the structure and processes to maintain it are not affected.
- Preservation – Preservation refers to the formal exclusion of activities that may negatively affect the structure and/or functioning of habitats or ecosystems. It can also refer to preservation of a species or group of species through management actions, such as elimination of harm to a species directly or indirectly through damage of its habitat. Marine protected areas (MPAs) can fit within this strategy. Marine protected areas are receiving growing attention as a viable way to preserve fish populations threatened by over-fishing and habitat loss (e.g., Roberts et al. 2001). They are typically established in habitats known to be important for function, such as reproduction or rearing.
Influence of Disturbance on Management Actions
The prioritization process considers the level of disturbance affecting the nearshore systems of Bainbridge Island. The success of any strategy varies depending on the level of disturbance of the site and the landscape within which the site resides (NRC 1992). Using the findings of the National Research Council (NRC) and a review of the literature on estuarine habitat restoration, Shreffler and Thom (1993) concluded that the strategies of restoration, enhancement, and creation should be applied depending on the degree of disturbance of the site and the landscape (Figure E-1). It is assumed that the historical conditions represent the optimal habitat conditions for a particular site. In general, restoration to historical conditions is best accomplished where the sites and the landscape are not heavily altered (Shreffler and Thom 1993; NRC 1992). Creation of new habitat (i.e., habitat not historically present) at a site is done when the site and the landscape are heavily damaged. Because the nearshore and adjacent uplands of the Island have typically not been heavily urbanized, the goal of restoring the nearshore habitats to historical conditions is viable over much of the Island. However, in some areas of the Island, other alternative actions are more appropriate (see below). For example, sites with a high degree of disturbance on the landscape (management area) and site (reach) scales (Figure E-1), in general, have a low probability for restoration, and creation of a new habitat or ecosystem or perhaps enhancement of selected attributes would be the only viable strategies to apply in these situations. In contrast, where the site and landscape are essentially intact, restoration to historical (i.e., humans present, but insignificant disturbance) or predisturbance (i.e., before man) conditions would be viable options and the probability of success would be high.
Figure E-1. The restoration strategies for nearshore systems relative to disturbance levels on the site and in the landscape (from Shreffler and Thom 1993).
(The relative chance of success increases with the size of the dot.)
Conservation strategy is related to another strategy common in the literature: sustainable development. Development here means the qualitative change in a systems complexity and configuration as opposed to (sustainable) growth which refers to a quantitative increase the size of the system (Meffe et al. 1994). Basically, this means that society conducts itself in a manner that preserves ecosystems for the future by encouraging actions that conserve what exists and that restore what has been damaged or lost (Meffe et al. 1994). Hence, the fields of conservation biology and restoration ecology merge under sustainable development, and, furthermore, are interdependent upon one another.
Some of the practical steps in sustainable development include the following:
- Avoid and minimize damages from any development project through thorough review and refinement of the project–base this on sound understanding of the individual and cumulative effects of the project on the ecosystem. By knowing the sources of stress, one can better provide advice on how to avoid these stresses through engineering and project modifications.
- Devote a strong effort in the planning phase for the restoration project to maximize the assurance of success.
- Execute the restoration project effectively and comprehensively.
- Monitor and adjust the project as needed to better meet the goals.
Finally, effectively achieving the goal may require that several strategies be employed at a site and in the landscape. It is possible that preservation of landscape features, enhancement of selected nearshore attributes, and conservation in the nearshore may be highly effective in restoring the controlling factors that affect historical structure, functions, and processes to the system.
Background to Prioritization Process
There is no universally accepted method for prioritizing nearshore sites for restoration or for determining what strategies are best applied to each site. At a national level, the U.S. Army Corps of Engineers (2000) has the most developed planning process for projects under their civil works mission (i.e., navigation, flood control), and they are adapting this process to ecosystem restoration projects (Thom et al., in press). Once the site is selected, the Corps process evaluates alternative plans relative to environmental planning objectives and cost. Through what is termed incremental analysis, they arrive at a point where there is a rapidly diminishing return on investment in the project. The process therefore highlights the action that provides the most benefit per unit of investment. The Corps utilizes environmental indices (e.g., habitat suitability indices; hydrogeomorphic indices; Shafer and Yozzo 1998; Thom et al., in press) as metrics to evaluate environmental outcomes from alternative restoration plans.
In the northwest, several approaches have been applied to prioritizing restoration projects. The approaches have several aspects in common: a goal statement, a site assessment to ascertain changes in conditions from the historical condition, a set of selection criteria, and a qualitative or semi-quantitative scoring protocol. The overall driver for these programs is to determine where and what needs to be done to result in improved conditions relative to the goal. Improvement in the landscape (management area) (e.g., limiting factor analysis), or simply the opportunity for restoration (e.g., sites made easily available, Bloch et al., 2002) at least partially drives the process of site prioritization. In highly urbanized and developed areas such as ports, site selection and prioritization is strongly driven by the cost for the site and its restoration relative the chance for restoration to be successful (Shreffler and Thom 1993). The chief drawback with all approaches has been the need to rely heavily on subjective (i.e., expert opinion) information in the face of a lack of critical data on key relationships. For example, it would be ideal to develop a metric that indicates the increase in fitness of juvenile salmon relative to various manipulations of the nearshore ecosystem. Because this is not possible with our present understanding, surrogates are utilized, such as area of selected habitats, juvenile salmon prey densities produced by habitats, area covered by exotic plants, and area of intact riparian zone.
Multi-criteria methods use data on the physical and chemical requirements (i.e., the controlling factors as used in this study) of a selected nearshore habitat (e.g., eelgrass), along with data on past restoration experience for that habitat to parameterize a model or index that evaluates the restoration potential for sites in a region (e.g., Store and Kangas 2001; Short 2003). Recent work with multi-criteria methods link results directly to a Geographic Information System (GIS), where the results of the analysis can be displayed on maps of the region (Store and Kangas 2001). The advantage of these habitat suitability models (HSM) is that quantitative data on habitat requirements are used along with information on existing conditions at sites. If data on habitat requirements are available and used, this type of analysis is generally more objective than other methods relying on expert opinion. However, expert opinion can also be incorporated when quantitative data are not available, which increases susceptibility to bias and decreases repeatability.
For analysis of sites, the method not only requires information on the needs of a particular habitat type, but also on the historic and present conditions of sites in the region. For example, a site with appropriate conditions prior to development may not presently be suitable for a particular habitat. Therefore, careful examination of the potential site needs to incorporate past (historical undisturbed) and present conditions, and the degree of change that needs to take place to reestablish the habitat. This method deals only with habitats where there is a large amount of information on their requirements as well as on their restoration potential. A separate model would be required for each habitat within a system.
The Index of Biological Integrity (IBI) is a multi-metric index of habitat quality and condition that composite several environmental or biotic variables to evaluate aquatic resources and to assess the effects of anthropogenic degradation (Karr 1993; Hughes et al. 2002). A biotic index is calculated based on a set of measurable biotic variables that are known to be indicative of habitat quality. For example, the following set of variables was used by Hughes et al. (2000) for evaluating estuarine quality on the east coast:
- Fish abundance or biomass
- Total fish species per trawl
- Species dominance
- Number of resident species
- Number of estuarine nursery species
- Number of in-estuary spawning species entering the estuary as adults to spawn
- Proportion of benthic-associated, or demersal, species
- Proportion of diseased fish.
The eight variables are compared with critical values indicating low habitat quality, and assigned a score. Often an independent set of data on water quality or other environmental variables are collected, computed as an index similar to the IBI, and compared with the IBI scores. If the IBI is a valid indicator of habitat conditions, the IBI score will correlate with the index based on environmental variables. Through analysis, the environmental factors most responsible for site-to-site variation in the IBI can be identified, and these can guide actions at the site that would lead to an improved IBI. For the IBI analysis to be most informative and defensible, critical values for the biotic and environmental variables need to be known.
In developing ecological assessment criteria for restoring anadromous salmon habitat, Simenstad and Cordell (2000) advocated the use of measures directly relatable to the ecological and physiological responses of juvenile salmonids to restored habitats. They proposed the use of three categories: capacity, opportunity, and realized functions (Table E-1). Capacity metrics include habitat attributes that promote juvenile salmon production through promotion of foraging, growth, and growth efficiency, and/or decreased mortality. The capacity category is an extension of the ecological concept of carrying capacity. Examples of capacity metrics include the productivity and density of prey, physical and chemical conditions that promote high assimilation efficiencies, and structural conditions that provide protection from predation. Opportunity metrics appraise the ability of salmon to access and benefit from the habitat’s capacity (Simenstad and Cordell 2000). Opportunity incorporates the principles of landscape ecology (Forman and Godron 1986). Examples of metrics include tidal elevation of feeding habitats, extent of morphometric features such as habitat edge length, as well as refugia (such as low-tide, deep-water refuges) from predation. Finally, realized function metrics include any direct measures of physiological or behavioral responses that can be attributable to fish occupation of the habitat and that promote fitness and survival (Simenstad and Cordell 2000). Survival is the ultimate metric, but related metrics include habitat-specific residence time, foraging success, and growth.
Table E-1. Capacity, Opportunity, and Realized Functions as Measures of Ecological and Physiological Responses of Juvenile Salmonids to Restored Habitats (Simenstad and Cordell 2000)
Category |
Potential Armoring Impact |
Potential Impact to Salmon |
Capacity |
Altered habitat type |
Change in prey species |
Opportunity |
Altered access |
Change in ability to find prey |
Realized Function |
Altered residence time |
Change in growth rate and survival |
Relevance to Bainbridge Island Nearshore
On Bainbridge Island, a numerical multi-criteria assessment of habitat suitability could be developed for eelgrass and tidal marshes. Quantitative information on physical and chemical requirements for these habitats would drive assessments of the appropriateness of sites for restoring these habitats. Other potential habitats include tidal flats and cobble and rocky shores, although these have not been evaluated rigorously. To accomplish this evaluation, the classification system developed by Dethier (1990) would be an important source for the physical “setting” for the various nearshore habitats found on Bainbridge Island. Dethier’s classification is descriptive, however, and linking physical conditions to habitat types is qualitative. The IBI multi-metric analysis, as described for other estuarine systems, may be appropriate for evaluating the functionality of restoration projects carried out on the Island. An IBI approach could also be employed to compare conditions before and after site restoration.
The process developed here relies as much as possible on solid ecological principles, coupled with the best available scientific understanding of the nearshore ecosystems of Puget Sound (Williams et al., 2003), and the best information available on the biophyscial conditions of the nearshore on Bainbridge Island (this report). Specifically, the process developed here relies on restoration of controlling factors as the key to successful and long-term sustainability. We have not done an analysis of historical conditions on the Island. Historical information on reaches on the Island should be examined to fully evaluate the appropriate strategy and potential for a strategy to work for those reaches. In the present analysis, we assumed that the “historical” conditions are present within other similar geomorphic settings in Puget Sound or relatively undisturbed sites on Bainbridge Island.
The Prioritization Method for Bainbridge Island Nearshore
The prioritization for Bainbridge Island nearshore involves an initial assessment of which strategies would have the highest priority of working within each reach, followed by a site (reach) specific assessment to refine the strategy and priority. This approach uses landscape ecology and conservation biology principles, and national recommendations on the most applicable restoration strategies as the fundamental underpinnings for prioritization (see above and NRC 1992; Shreffler and Thom 1993). These principles are well established in the ecological literature, and are highly useful in providing comprehensive, larger-scale guidance.
Analysis of the Most Applicable Management Strategies
A national assessment showed that the degree of impact on the landscape and site scales affected the probability of restoration success, and that the most appropriate restoration strategies varied according to disturbance on these two scales (Figure E-1). Restoration of natural aquatic systems can be uncertain (NRC 1992; Thom 2000). Prioritization of sites and management action strategies for these sites are presented here using information designed to reduce this uncertainty as much as possible. For Bainbridge Island, reach is equated to site-scale, and management area is equated to landscape scale. Actual sites on Bainbridge Island may be smaller than a reach, and should be evaluated at the actual scale when developing strategies for that site. Because the shoreline management area is based on drift cells, a major contributor to habitat-forming processes in reaches, shoreline management areas encompass appropriate landscape-scale processes. Because some sites may be located at the convergence or divergence between two drift cells, these sites should be evaluated relative to their unique position.
The matrix in Figure E-2 identifies the strategies most appropriate under the different states of combined reach and management area impact. Figure E-2 integrates the restoration strategies in Figure E-1 and the two additional strategies of conservation and preservation discussed above. The strategies most likely to work are indicated, as well as where each strategy might also be applied with a somewhat lower probability of working.
As seen in the matrix (Figure E-2), multiple strategies are potentially viable under any one of the states. This matrix provides general guidance as a first approximation of specific management actions that could be evaluated within a reach or management area. In developing the matrix in Figure E-2, the following logic was used:
- The lower the disturbance on both scales, the greater reliance on preservation, conservation, and restoration
- The greater the disturbance on both scales, the greater reliance on enhancement
- Under the greatest levels of disturbance, greater is the reliance on creation.
Low Reach Impact |
Restore |
Preserve |
Preserve |
|
Restore |
Conserve |
Conserve |
High Reach Impact |
Restore |
Restore |
Restore |
|
High Management Area Impact |
|
Low Management Area Impact |
Figure E-2. Matrix of management action strategies most appropriate for a reach based on the degree of disturbance of the management area and the reach (not listed in any particular order).
Figure E-3. Shoreline Management Area average normalized controlling factor disturbance score versus reach normalized controlling factor disturbance score.
To develop this prioritization specifically for the Bainbridge Island nearshore, the average controlling factor score (based on normalized reach scores) for each shoreline management area is plotted against the normalized controlling factor score for reaches (Figure E-3). Each point in Figure E-3 represents a reach. The rationale for using average controlling factor scores within each management area is that the average score indicates the relative degree of disturbances of the management area, which corresponds to the degree of disturbance of the landscape in Figure E-1. The degree of disturbance on the site scale is represented by the reach scale controlling factor score.
Figure E-3 corresponds to the matrix of management action strategies in Figure E-2 above, and can be used to prioritize appropriate management action strategies for those reaches. For example, for reaches with low controlling-factor disturbance scores on both axes, the most appropriate management action strategies would be to conserve, preserve, and restore (to pre-disturbance or pre-historical conditions). Whereas, reaches where controlling-factor disturbance scores are high on both axes, management action strategies of enhancement of selected habitat attributes or creation of new ecosystems are most appropriate. Areas where shoreline management area controlling factor scores are low (good), but reach scores are high (poor), the reach is in relatively good condition; however, any strategy for restoration needs to be considered relative to the ability of processes afforded by a relatively disturbed landscape to maintain the restored reach in the long term. Because the points are continuously distributed (at least on the reach scale) and there is a high degree of variability, the management action strategy most appropriate for a particular reach needs further reach-specific analysis. This degree of variation in the application of strategies is reflected in the general zones illustrated in Figure E-4. The scores and categories for each reach and management area are provided in Table E-2.
Figure E-4. Generalized zones of application of management strategies relative to management area and reach disturbance.
Table E-2. Controlling factors scores for reaches and management areas, along with their relative qualitative ranking.
MA |
Reach |
Normalized |
Qualitative |
Average |
Qualitative |
Ecological Function Score |
1 |
3217 |
-0.689 |
Mod/High |
-0.470 |
Mod |
32 |
1 |
3218 |
-0.622 |
Mod/High |
-0.470 |
Mod |
32 |
1 |
3219 |
-0.578 |
Mod |
-0.470 |
Mod |
30 |
1 |
3220 |
-0.556 |
Mod |
-0.470 |
Mod |
30 |
1 |
3221 |
-0.600 |
Mod |
-0.470 |
Mod |
26 |
1 |
3222 |
-0.378 |
Low/Mod |
-0.470 |
Mod |
30 |
1 |
3223 |
-0.333 |
Low/Mod |
-0.470 |
Mod |
26 |
1 |
3487 |
-0.622 |
Mod/High |
-0.470 |
Mod |
22 |
1 |
3488 |
0.000 |
No |
-0.470 |
Mod |
28 |
1 |
3489 |
-0.222 |
Low/Mod |
-0.470 |
Mod |
28 |
1 |
3490 |
-0.511 |
Mod |
-0.470 |
Mod |
28 |
1 |
3491 |
-0.533 |
Mod |
-0.470 |
Mod |
27 |
2 |
3193 |
-0.622 |
Mod/High |
-0.471 |
Mod |
22 |
2 |
3194 |
-0.025 |
Low |
-0.471 |
Mod |
32 |
2 |
3195 |
-0.371 |
Low/Mod |
-0.471 |
Mod |
27 |
2 |
3196 |
-0.486 |
Mod |
-0.471 |
Mod |
30 |
2 |
3197 |
-0.600 |
Mod |
-0.471 |
Mod |
21 |
2 |
3198 |
-0.375 |
Low/Mod |
-0.471 |
Mod |
22 |
2 |
3199 |
-0.625 |
Mod/High |
-0.471 |
Mod |
19 |
2 |
3200 |
-0.600 |
Mod |
-0.471 |
Mod |
18 |
2 |
3201 |
-0.425 |
Mod |
-0.471 |
Mod |
19 |
2 |
3202 |
-0.325 |
Low/Mod |
-0.471 |
Mod |
16 |
2 |
3203 |
-0.300 |
Low/Mod |
-0.471 |
Mod |
16 |
2 |
3204 |
-0.475 |
Mod |
-0.471 |
Mod |
18 |
2 |
3205 |
-0.650 |
Mod/High |
-0.471 |
Mod |
16 |
2 |
3206 |
-0.650 |
Mod/High |
-0.471 |
Mod |
16 |
2 |
3207 |
-0.500 |
Mod |
-0.471 |
Mod |
20 |
2 |
3208 |
-0.250 |
Low/Mod |
-0.471 |
Mod |
20 |
2 |
3209 |
-0.425 |
Mod |
-0.471 |
Mod |
18 |
2 |
3210 |
-0.700 |
Mod/High |
-0.471 |
Mod |
18 |
2 |
3211 |
-0.375 |
Low/Mod |
-0.471 |
Mod |
20 |
2 |
3212 |
-0.525 |
Mod |
-0.471 |
Mod |
30 |
2 |
3213 |
-0.356 |
Low/Mod |
-0.471 |
Mod |
36 |
2 |
3214 |
-0.350 |
Low/Mod |
-0.471 |
Mod |
32 |
2 |
3215 |
-0.622 |
Mod/High |
-0.471 |
Mod |
34 |
2 |
3216 |
-0.667 |
Mod/High |
-0.471 |
Mod |
32 |
3 |
3176 |
-0.467 |
Mod |
-0.421 |
Mod |
20 |
3 |
3177 |
-0.800 |
Mod/High |
-0.421 |
Mod |
18 |
3 |
3178 |
-0.756 |
Mod/High |
-0.421 |
Mod |
20 |
3 |
3179 |
-0.178 |
Low |
-0.421 |
Mod |
25 |
3 |
3180 |
-0.400 |
Low/Mod |
-0.421 |
Mod |
22 |
3 |
3181 |
-0.578 |
Mod |
-0.421 |
Mod |
23 |
3 |
3182 |
-0.325 |
Low/Mod |
-0.421 |
Mod |
22 |
3 |
3183 |
-0.533 |
Mod |
-0.421 |
Mod |
21 |
3 |
3184 |
-0.511 |
Mod |
-0.421 |
Mod |
24 |
3 |
3185 |
-0.178 |
Low |
-0.421 |
Mod |
25 |
3 |
3186 |
-0.125 |
Low |
-0.421 |
Mod |
24 |
3 |
3187 |
-0.225 |
Low/Mod |
-0.421 |
Mod |
20 |
3 |
3188 |
-0.600 |
Mod |
-0.421 |
Mod |
26 |
3 |
3189 |
-0.325 |
Low/Mod |
-0.421 |
Mod |
24 |
3 |
3190 |
-0.600 |
Mod |
-0.421 |
Mod |
22 |
3 |
3191 |
-0.467 |
Mod |
-0.421 |
Mod |
24 |
3 |
3192 |
-0.289 |
Low/Mod |
-0.421 |
Mod |
26 |
3 |
6002 |
-0.225 |
Low/Mod |
-0.421 |
Mod |
26 |
4 |
3156 |
-0.622 |
Mod/High |
-0.334 |
Low/Mod |
18 |
4 |
3157 |
-0.422 |
Mod |
-0.334 |
Low/Mod |
18 |
4 |
3158 |
-0.311 |
Low/Mod |
-0.334 |
Low/Mod |
26 |
4 |
3159 |
-0.133 |
Low |
-0.334 |
Low/Mod |
24 |
4 |
3160 |
-0.600 |
Mod |
-0.334 |
Low/Mod |
26 |
4 |
3161 |
-0.325 |
Low/Mod |
-0.334 |
Low/Mod |
20 |
4 |
3162 |
-0.244 |
Low/Mod |
-0.334 |
Low/Mod |
24 |
4 |
3163 |
-0.578 |
Mod |
-0.334 |
Low/Mod |
22 |
4 |
3164 |
-0.356 |
Low/Mod |
-0.334 |
Low/Mod |
26 |
4 |
3165 |
-0.067 |
Low |
-0.334 |
Low/Mod |
22 |
4 |
3166 |
-0.467 |
Mod |
-0.334 |
Low/Mod |
22 |
4 |
3167 |
-0.644 |
Mod/High |
-0.334 |
Low/Mod |
14 |
4 |
3168 |
-0.425 |
Mod |
-0.334 |
Low/Mod |
13 |
4 |
3169 |
-0.125 |
Low |
-0.334 |
Low/Mod |
16 |
4 |
3170 |
-0.050 |
Low |
-0.334 |
Low/Mod |
19 |
4 |
3171 |
0.000 |
No |
-0.334 |
Low/Mod |
24 |
4 |
3172 |
-0.222 |
Low/Mod |
-0.334 |
Low/Mod |
17 |
4 |
3173 |
-0.175 |
Low |
-0.334 |
Low/Mod |
16 |
4 |
3174 |
-0.500 |
Mod |
-0.334 |
Low/Mod |
17 |
4 |
3175 |
-0.422 |
Mod |
-0.334 |
Low/Mod |
18 |
5 |
3121 |
-0.267 |
Low/Mod |
-0.559 |
Mod |
19 |
5 |
3122 |
-0.475 |
Mod |
-0.559 |
Mod |
20 |
5 |
3123 |
-0.575 |
Mod |
-0.559 |
Mod |
18 |
5 |
3124 |
-0.578 |
Mod |
-0.559 |
Mod |
24 |
5 |
3125 |
-0.700 |
Mod/High |
-0.559 |
Mod |
20 |
5 |
3126 |
-0.700 |
Mod/High |
-0.559 |
Mod |
14 |
5 |
3127 |
-0.575 |
Mod |
-0.559 |
Mod |
12 |
5 |
3128 |
-0.425 |
Mod |
-0.559 |
Mod |
12 |
5 |
3129 |
-0.325 |
Low/Mod |
-0.559 |
Mod |
16 |
5 |
3130 |
-0.625 |
Mod/High |
-0.559 |
Mod |
14 |
5 |
3131 |
-0.844 |
High |
-0.559 |
Mod |
14 |
5 |
3132 |
-0.644 |
Mod/High |
-0.559 |
Mod |
22 |
5 |
3133 |
-0.550 |
Mod |
-0.559 |
Mod |
18 |
5 |
3134 |
-0.686 |
Mod/High |
-0.559 |
Mod |
18 |
5 |
3135 |
-0.400 |
Low/Mod |
-0.559 |
Mod |
19 |
5 |
3136 |
-0.325 |
Low/Mod |
-0.559 |
Mod |
16 |
5 |
3137 |
-0.500 |
Mod |
-0.559 |
Mod |
19 |
5 |
3138 |
-0.375 |
Low/Mod |
-0.559 |
Mod |
18 |
5 |
3139 |
-0.250 |
Low/Mod |
-0.559 |
Mod |
20 |
5 |
3140 |
-0.300 |
Low/Mod |
-0.559 |
Mod |
19 |
5 |
3141 |
-0.725 |
Mod/High |
-0.559 |
Mod |
22 |
5 |
3142 |
-0.571 |
Mod |
-0.559 |
Mod |
19 |
5 |
3143 |
-0.867 |
High |
-0.559 |
Mod |
14 |
5 |
3144 |
-0.822 |
High |
-0.559 |
Mod |
13 |
5 |
3145 |
-0.675 |
Mod/High |
-0.559 |
Mod |
16 |
5 |
3146 |
-0.733 |
Mod/High |
-0.559 |
Mod |
17 |
5 |
3147 |
-0.650 |
Mod/High |
-0.559 |
Mod |
18 |
5 |
3148 |
-0.600 |
Mod |
-0.559 |
Mod |
13 |
5 |
3149 |
-0.622 |
Mod/High |
-0.559 |
Mod |
18 |
5 |
3150 |
-0.475 |
Mod |
-0.559 |
Mod |
21 |
5 |
3151 |
-0.622 |
Mod/High |
-0.559 |
Mod |
20 |
5 |
3152 |
-0.400 |
Low/Mod |
-0.559 |
Mod |
16 |
5 |
3153 |
-0.400 |
Low/Mod |
-0.559 |
Mod |
20 |
5 |
3154 |
-0.644 |
Mod/High |
-0.559 |
Mod |
20 |
5 |
3155 |
-0.644 |
Mod/High |
-0.559 |
Mod |
20 |
6 |
3105 |
-0.150 |
Low |
-0.295 |
Low/Mod |
14 |
6 |
3106 |
-0.400 |
Low/Mod |
-0.295 |
Low/Mod |
10 |
6 |
3107 |
-0.222 |
Low/Mod |
-0.295 |
Low/Mod |
18 |
6 |
3108 |
-0.333 |
Low/Mod |
-0.295 |
Low/Mod |
16 |
6 |
3109 |
-0.422 |
Mod |
-0.295 |
Low/Mod |
14 |
6 |
3110 |
-0.675 |
Mod/High |
-0.295 |
Low/Mod |
16 |
6 |
3111 |
-0.325 |
Low/Mod |
-0.295 |
Low/Mod |
14 |
6 |
3112 |
0.000 |
No |
-0.295 |
Low/Mod |
19 |
6 |
3113 |
0.000 |
No |
-0.295 |
Low/Mod |
22 |
6 |
3114 |
-0.089 |
Low |
-0.295 |
Low/Mod |
27 |
6 |
3115 |
-0.300 |
Low/Mod |
-0.295 |
Low/Mod |
20 |
6 |
3116 |
-0.375 |
Low/Mod |
-0.295 |
Low/Mod |
17 |
6 |
3117 |
-0.475 |
Mod |
-0.295 |
Low/Mod |
17 |
6 |
3118 |
-0.425 |
Mod |
-0.295 |
Low/Mod |
16 |
6 |
3119 |
-0.475 |
Mod |
-0.295 |
Low/Mod |
17 |
6 |
3120 |
-0.050 |
Low |
-0.295 |
Low/Mod |
24 |
7 |
3080 |
-0.600 |
Mod |
-0.468 |
Mod |
15 |
7 |
3081 |
-0.475 |
Mod |
-0.468 |
Mod |
16 |
7 |
3082 |
-0.350 |
Low/Mod |
-0.468 |
Mod |
15 |
7 |
3083 |
-0.650 |
Mod/High |
-0.468 |
Mod |
21 |
7 |
3084 |
-0.600 |
Mod |
-0.468 |
Mod |
17 |
7 |
3085 |
-0.525 |
Mod |
-0.468 |
Mod |
18 |
7 |
3086 |
-0.450 |
Mod |
-0.468 |
Mod |
15 |
7 |
3087 |
-0.300 |
Low/Mod |
-0.468 |
Mod |
14 |
7 |
3088 |
-0.700 |
Mod/High |
-0.468 |
Mod |
12 |
7 |
3089 |
-0.675 |
Mod/High |
-0.468 |
Mod |
14 |
7 |
3090 |
-0.375 |
Low/Mod |
-0.468 |
Mod |
16 |
7 |
3091 |
-0.050 |
Low |
-0.468 |
Mod |
18 |
7 |
3092 |
-0.050 |
Low |
-0.468 |
Mod |
16 |
7 |
3093 |
-0.700 |
Mod/High |
-0.468 |
Mod |
18 |
7 |
3094 |
-0.650 |
Mod/High |
-0.468 |
Mod |
14 |
7 |
3095 |
-0.425 |
Mod |
-0.468 |
Mod |
14 |
7 |
3096 |
-0.625 |
Mod/High |
-0.468 |
Mod |
14 |
7 |
3097 |
-0.600 |
Mod |
-0.468 |
Mod |
20 |
7 |
3098 |
-0.511 |
Mod |
-0.468 |
Mod |
18 |
7 |
3099 |
-0.450 |
Mod |
-0.468 |
Mod |
16 |
7 |
3100 |
-0.550 |
Mod |
-0.468 |
Mod |
14 |
7 |
3101 |
-0.375 |
Low/Mod |
-0.468 |
Mod |
16 |
7 |
3102 |
-0.350 |
Low/Mod |
-0.468 |
Mod |
14 |
7 |
3103 |
-0.400 |
Low/Mod |
-0.468 |
Mod |
14 |
7 |
3104 |
-0.200 |
Low |
-0.468 |
Mod |
14 |
7 |
3540 |
-0.778 |
Mod/High |
-0.468 |
Mod |
14 |
7 |
6000 |
-0.325 |
Low/Mod |
-0.468 |
Mod |
21 |
7 |
6001 |
-0.375 |
Low/Mod |
-0.468 |
Mod |
22 |
8 |
3502 |
-0.667 |
Mod/High |
-0.466 |
Mod |
24 |
8 |