Draft Technical Memorandum

Transcription

1 5309 Shilshole Avenue NW Suite 200 Seattle, WA phone fax Draft Technical Memorandum date February 21, 2013 to from subject Renee LaCroix, City of Bellingham Pete Lawson, Margaret Clancy, Vikki Jackson (NES), Brock Rylander, Aaron Raymond, and Jenna Friebel Draft Existing Conditions Analysis for the City of Bellingham Habitat Restoration Master Plan OVERVIEW AND PURPOSE Environmental Science Associates (ESA) is assisting the City of Bellingham (City) prepare a citywide Habitat Restoration Master Plan (Plan). The Plan is intended to provide a prioritization framework for the preservation, restoration, and recovery of the City s terrestrial, aquatic (both marine and riverine), and riparian habitats, in order to maintain a healthy environment within the City limits and City urban growth areas (UGAs) (with the exception of the Lake Whatcom watershed) (Figure 1). The Plan will help achieve the City's Legacies and Strategic Commitments including the following goals: Protection and improvement of the health of lakes, streams and bays; Protection and restoration of ecological functions and habitat; Reduction of contributions to climate change; and Conservation of natural and consumable resources. Key steps in the development of the Plan that will help address the City s goals, as outlined above include: 1) review key ecological datasets for the study area that may inform the analysis, 2) develop a function-based conceptual model and conceptual model that can be used to assess existing conditions and prioritize restoration actions, 3) apply the model to analyze existing conditions (level of existing function) within the study area, 4) develop a comprehensive suite of restoration actions, and 5) assess and prioritize effects of the restoration actions on improving or maintaining desired levels of ecological function. Project steps one and two have been completed and are summarized in the previous project deliverable, the Draft Conceptual Model for the City of Bellingham Habitat Restoration Master Plan ( date). That memorandum summarized and documented the conceptual model which will be used to classify existing ecological conditions within the study area and to prioritize restoration actions to improve ecological functions within various ecosystem components, including freshwater, marine, and terrestrial habitats.

2 This memorandum briefly summarizes historical conditions of the various habitat groups, and then documents the process of refining the specific components of the conceptual model based on data availability and quality and the incorporation of this information into GIS (geographic information system) to complete the analysis. During the iterative process of 1) data selection, 2) incorporation into GIS, and 3) review of output data, we determined that several specific components of the conceptual model required alteration or adjustment. The majority of the adjusted components were attribute measures, although in some cases the ecological functions and functional attributes of a habitat group were also adjusted accordingly. In addition to more detailed information on the analysis methods for each habitat group, the preliminary results of the functional analysis are also presented. Based on our initial review of the output data, it appears as if the assessment results generally achieved the goal of accurately assessing the relative state of key ecological functions within habitat groups in the project area, although review of the analysis results by the City and the technical advisory group (TAG) will be a key step in indentifying necessary modifications to specific analysis metrics, particularly the composition and weighting of individual attribute measures. The memo also identifies data gaps and recommends specific City of Bellingham datasets which could be collected in the future in order to more accurately define ecological functions. Acquisition of recommended data would aid in any future ecologically-based restoration prioritization plans in the City. Lastly, a review of next steps summarizes the remaining project work elements. HISTORICAL PERSPECTIVE ON HABITAT GROUPS AND FUNCTIONS As described in the Draft Conceptual Model for the City of Bellingham Habitat Restoration Master Plan memorandum, a key element of the Plan is the comparison of baseline ecological conditions between various habitat analysis units within the City (e.g., sub-watersheds or forest habitat blocks). The analysis of baseline conditions, which is the primary focus of this memorandum, is based on existing conditions versus historic (pre- European settlement) conditions. Historical conditions and the ecological stressors that have altered ecological functions inform our present evaluation of existing conditions. Therefore, the following sections briefly summarize general historical conditions and current and historical ecological stressors and limiting factors for each of the five habitat groups included in the analysis. Riverine Habitats Although none of the streams in the study area are large river systems, these smaller, independent drainages historically provided high-quality habitat for a variety of salmonid species, including coho, cutthroat, steelhead, chum, and to a lesser degree, Chinook salmon (Smith, 2003). Although salmonids still utilize many of Bellingham s streams, a reduction in habitat quality has substantially reduced instream and riparian habitat quality, resulting in a concurrent reduction in the number of spawning fish in these systems (Smith, 2003). Much of the reduction in habitat quality and quantity is a byproduct of land conversion in these lowland streams and tributaries. Once forested floodplains were converted to agricultural or urban use, which has resulted in channelization and confinement from dikes, levees, and armored banks, water withdrawals, riparian wetland fill, and altered land cover. Low stream flows are also believed to be a problem in many of these streams, such as Squalicum, Whatcom, Padden, and Chuckanut Creeks, which all have closures for further water allocations and numerous existing water rights. 2

3 Limiting factors within streams in the City of Bellingham have been identified as fish passage barriers, lack of connected floodplain, fine sediments, lack of quality pools and large woody debris (LWD), degraded riparian conditions (both species composition and buffer distance), and poor water quality. Many of these limiting factors are related and due to increased development pressure and conversion of forest lands to urban land cover. For example, stream bank modification, the loss of riparian vegetation, urban storm water, and agricultural impacts are some of the likely causes of these water quality problems (Scott and McDowell, 1994). Freshwater Wetland Habitats Prior to settlement in the 1850 s, a mosaic of freshwater wetlands along streams, lakes, and low lying depressional areas characterized wetlands in the study area. The General Land Office (GLO) mapped the lowlands along the Nooksack River and its tributaries between the 1850 s and 1880 s. GLO Plat Maps for the Nooksack River show a network of freshwater wetlands extending upstream of the Nooksack estuary (GLO, 1859, 1872, 1873, 1874, 1884). Historically, wetlands extended across the Nooksack s low-gradient floodplain and meandering river valley (Collins and Sheikh, 2003). Plat maps for other portions of the study area were not readily available at the time of this assessment. Relatively little data exists regarding the historical extent of freshwater wetland habitat along smaller streams and depressions in the study area. City maps and drawings from the late 19th century depict development occurring along the Bellingham Bay coastline, extending eastward in a scattered pattern towards Lake Padden and Lake Whatcom in the 1890 s (COB, 1889; 1890; 1892). Urban growth led to the development and fill of tidelands and adjacent deltas. Settlers also diked and drained fertile floodplain and wetland soils, converting them to prime agricultural lands. Approximately 65% of the Nooksack floodplain has been converted to agriculture since the 1930s (Collins and Sheikh, 2003; Brown et al., 2005). Limiting factors within wetlands in the study area include the loss and fragmentation of wetland habitat, lack of habitat features (e.g., large woody debris and standing snags), increased invasive species presence, lack of native plant structure and diversity, impaired water quality, and changes to natural wetland hydrology (e.g., increased runoff rates, low base flows, etc) (COB, 2012). Limiting factors are primarily related to anthropogenic disturbances, such as increased urban and rural development, and the loss of wetland habitat. Upland Habitats (Forest and Meadow) Prior to the mid 1800s the City of Bellingham, like most of this region, was covered in dense mature lowland coniferous forest. A striking feature of these forests was the dominance of conifers, with deciduous trees being limited to areas of disturbance (e.g. river floodplains, landslides, fires).the GAP Analysis of Washington State indicates the vegetation zones in the vicinity of Bellingham as the Puget Sound Douglas fir Zone and the Mountain Hemlock Zone (Cassidy, K.M. et al 1997). The Douglas fir zone is the predominant vegetation zone and dominated by Douglas fir. The Western Hemlock zone occurs in low to mid elevations and is mapped at the southern edge of the city within Chuckanut Mountain and east. Western hemlock is the dominant species of this zone. Dense coniferous forests began to decline with European settlement of the area. European colonization of the region began to alter the native forests starting aggressively in the mid 1800s and by the 1920s most of the city forests had been cut and no contiguous stands of old growth remained in the City (Eissinger 1995). Forests returned to many area of the city after the early 1920s and large contiguous stands of second growth forest are present throughout the City although development in the mid-1990s and early 2000s resulted in large tracts of second growth forest being converted to residential and commercial uses. Deciduous forest cover is more frequent than in the historical context due to more frequent disturbance. The largest tracts of contiguous forest remain in City Parks and along the southeast and southern edges of the city fringing Galbraith and Chuckanut Mountains. 3

4 Not all areas were forested prior to European settlement native prairie habitat has been documented in the area of Fort Bellingham and King Mountain (Tim Wahl, person communication). Open thin soiled meadows, referred to as balds were frequent on the west face of Chuckanut Mountain and along the sandstone dominated shorelines. These natural meadow habitats were likely anthropogenically maintained by native peoples. Native people kept these meadows open by removing invading trees and shrubs, often through fire. Meadows were important to the cultivation native foods such as bulb plants. A number of plant species are restricted to these habitats and several butterfly and moth species are associated with these limited habitat types. Most of the natural prairie habitat in the Bellingham area has been converted to agriculture or developed. Remaining balds are present in Chuckanut Bay and on Chuckanut Mountain, but are at risk due to invasion of trees and non-native Scot s broom within the meadows. Other meadow habitat has been created via farming practices. Agricultural has converted many areas from forest to meadow. These meadow habitats differ from the native meadows as they are dominated by nonnative plants introduced for agriculture. The opening of forest to meadow habitat have benefited many species that require open habitats particularly waterfowl, raptors, coyotes and a number of small mammal species that provide food for the predators. In the past farms were frequent in the City, but are disappearing rapidly with development infill. Nearshore and Estuarine Habitats Since the late 1800s, the local community has utilized the abundant natural resources within and adjacent to Bellingham Bay. The Bay once provided both richer and more diverse habitat for fish, wildlife, and other aquatic organisms. Native eelgrass, salt marsh, and other key aquatic habitats existed over much more of the Bay than present day (Nahkeeta Northwest, 2003). Historically, extensive estuarine wetlands and tide flats existed at the mouths of Squalicum, Whatcom, and Padden Creeks and the Nooksack Delta (NES, 2004; CGS, 2013). Urbanization, including industrial land uses and activities, has had an adverse impact on much of the original high quality habitat, in and around downtown Bellingham, particularly in the northeast quadrant of Bellingham Bay. These activities included filling of the historic shoreline, construction on or adjacent to the shoreline, and water and sediment contamination in the Bay and associated estuaries. EXISTING CONDITIONS ANALYSIS APPROACH OVERVIEW As summarized in the Draft Conceptual Model for the City of Bellingham Habitat Restoration Master Plan memorandum (date), the quantitative analysis of ecological functions is based on a hierarchical conceptual model that relates functions, functional attributes, and attribute measures to relate the useful ecological concept of ecosystem function to discreet measureable features. This analysis framework will be applied separately to habitat groups, which share a discreet set of functions and similar physical, chemical, and biological components. Five habitat groups were selected after a screening process to determine suitability for use incorporation into the Plan. Taken together, the sums of habitat groups generally represent the broad range of ecological assemblages present within the Plan area. Ecological function will be evaluated at the individual habitat group level for the following selected habitat groups. 1) riverine (including riparian areas), 2) wetlands, 3) forests, 4) meadow/ shrub, and 4

5 5) nearshore/estuarine. The majority of the information that follows is related to the first four habitat groups above, for which the conceptual model was developed. As indicated in the previous memorandum, significant model development for the nearshore/estuarine habitat group has already occurred in support of a completed restoration prioritization plan for nearshore and estuarine areas within WRIA 1 (MacLennan et al., 2013). Therefore, the concepts and data incorporated into the WRIA 1 plan will be adopted for analysis of the nearshore/estuarine habitat group in the Bellingham Plan, applying the existing data/analysis methods to the scale of the project area, in order to prioritize restoration actions with greater spatial resolution. SUMMARY OF ANALYSIS APPROACH BY HABITAT GROUP This section presents details on the analysis approach discussion of the analysis approach for all five habitat units. Information presented includes both changes in some analysis metrics based on data availability and further detail on the calculation of attribute measures. Riverine Habitat Group For the Riverine Habitat Group, data analysis was conducted at the level of the sub-watershed (see Conceptual Model memo for delineation details). A total of 24 sub-watersheds were analyzed for conditions of existing riverine functions (Table 1 and Figure 2). This does not include four sub-watersheds (Central Bellingham, North Lower Squalicum, South Bellingham, and Squalicum Harbor) that have no streams within the sub-watershed, three sub-watersheds (Chuckanut Bay, Upper Spring Creek, and Upper Baker Street) that contain only a very small portion of the sub-watershed within the study area), and two other watersheds (Upper Sqalicum and Upper Toad Creek) that lie entirely outside of the study area. However, information for many of these watersheds was utilized to conduct analysis of the other 24 sub-watersheds where appropriate (e.g., contributing basin information). The right side of Table 2 (see Table section at end of memorandum) presents the revised conceptual model and shows the relationships between all riverine functions, attributes, and attribute measures as used in the analysis. All riverine functions proposed in the previous memorandum were analyzed, however several attribute measures have been altered due to either 1) a lack of comprehensive (project area wide) GIS data to evaluate the measure, requiring the removal of the measure from the analysis, or 2) addition of new measures to describe that better define the existing condition of the attribute and function. Both the removed and added measures are indicated in Table 2 by cell shading (grey and green shading, respectively). 5

6 Table 1. Riverine Habitat Group s Analyzed for Existing Conditions of Ecological Function Alderwood Creek Baker Creek Tributary Bear Creek Cemetery Creek Chuckanut Creek Connelly Creek Fever Creek Fort Bellingham Hannah Creek Lake Padden Lincoln Creek Little Squalicum Creek Lost Creek Lower Baker Creek Lower Padden Creek Lower Spring Creek Lower Squalicum Lower Toad Creek Lower Whatcom Creek Silver Creek Tributary #1 Silver Creek Tributary #2 Subwatershed Area (acres) Total Stream Length (Miles) , , , , , , , , , , Spokane Creek Upper Padden Creek Upper Whatcom Creek The left side of Table 2 provides detail on the selected attribute measure, including definition, data sets utilized in the analysis, the metrics (units) of the measures, and the weighting applied to combining multiple measure scores into a single attribute score (this applied only in some cases) and combining multiple attribute scores into a single function score (applied in all cases). The weighting factors for measures and attributes were developed using the following criteria: Where 1) all data was considered of equal quality and geographic coverage, and 2) ecological principles indicate that the multiple measures or attributes generally contribute equally to the respective attribute or function, the data was equally weighted. Where the conditions above did not apply a lower weighting factor was applied to those measures where data quality was sub-standard compared to other data sources and/or where a measure was determined to contribute (or drive ) a function to a lesser degree than other associated functions. 6

7 The data from individual riverine functions required normalization on a zero to one scale, and in some cases transposition, in order to have all metrics scaled where zero indicates the lowest comparative score and one the highest. The GIS analysis results were exported to Microsoft Excel, which was then used to calculate all measure, attribute, and function scores. Table 3 (see Table section at end of memorandum) summarizes the raw outputs from this effort and the attached electronic Excel file contains the complete Excel spreadsheet, including all intermediate calculations and data transformation analysis steps. Wetland Habitat Group For the Wetland Habitat Group, data analysis was also conducted at the level of the sub-watershed (see Conceptual Model memo for delineation details). A total of 28 sub-watersheds were analyzed for conditions of existing wetland functions (Table 4 and Figure 3). This does not include three sub-watersheds (Chuckanut Bay, Upper Spring Creek, and Upper Baker Street) that contain only a very small portion of the sub-watershed within the study area and few to no mapped wetlands), and two other watersheds (Upper Squalicum and Upper Toad Creek) that lie entirely outside of the study area. The right side of Table 5 (see Table section at end of memorandum) presents the revised conceptual model and shows the relationships between all wetland functions, attributes, and attribute measures as used in the analysis. With the exception of thermoregulation, all other wetland functions proposed in the previous memorandum were analyzed. However, a number of attribute measures have been altered due to either 1) a lack of comprehensive (project area wide) GIS data to evaluate the measure, requiring the removal of the measure from the analysis, or 2) addition of new measures to describe that better define the existing condition of the attribute and function. Both the removed and added measures are indicated in Table 5 by cell shading (grey and green shading, respectively). The left side of Table 5 provides detail on the selected attribute measure, including definition, data sets utilized in the analysis, the metrics (units) of the measures, and the weighting applied to combining multiple measure scores into a single attribute score (this applied only in some cases) and combining multiple attribute scores into a single function score (applied in all cases). The weighting factors for measures and attributes were developed using the same criteria discussed under the Riverine Habitat Group The data from individual wetland functions required normalization on a zero to one scale, and in some cases transposition, in order to have all metrics scaled where zero indicates the lowest comparative score and one the highest. The GIS analysis results were exported to Microsoft Excel, which was then used to calculate all measure, attribute, and function scores. Table 6 summarizes the raw outputs from this effort and the attached electronic Excel file contains the complete Excel spreadsheet, including all intermediate calculations and data transformation analysis steps. 7

8 Table 4. Wetland Habitat Group s Analyzed for Existing Conditions of Ecological Function Subbasin Area (Acres) Wetland Area (Acres) Alderwood Creek Baker Creek Tributary Bear Creek 2, Cemetery Creek 1, Central Bellingham Chuckanut Creek 4, Connelly Creek Fever Creek 1, Fort Bellingham Hannah Creek Lake Padden 1, Lincoln Creek Little Squalicum Creek Lost Creek Lower Baker Creek Lower Padden Creek 1, Lower Spring Creek 1, Lower Squalicum 2, Lower Toad Creek Lower Whatcom Creek 1, North Lower Squalicum Silver Creek Tributary # Silver Creek Tributary #2 1, South Bellingham Spokane Creek Squalicum Harbor Upper Padden Creek Upper Whatcom Creek Forest Habitat Group For the Forest Habitat Group, data analysis was also conducted at the level of the forest block, as delineated by Nahkeeta Northwest (2003) (see Conceptual Model memo for delineation details). The forest habitat blocks were included in the analysis is there is at least one contiguous habitat patch, consisting of more than 5 acres of forest habitat. A total of 85 forested habitat blocks were analyzed for conditions of existing forest functions (Table 7 and Figure 4). Any forested habitat block that was at least partially within the study area was included in the analysis. Other habitat patches which are outside, but adjacent to the study area were used for analysis of certain metrics (e.g. connectivity), but were not analyzed for ecological function within the block. 8

9 Table 7. Forest Habitat Group s Analyzed for Existing Conditions of Ecological Function Forest Block ID Number Forest Block Area (Acres) Forest Block - Forested Patches (Acres) Percent of Block Consisting of Forest Patches ,624 4, A B A ,765 3, A

10 Forest Block ID Number Forest Block Area (Acres) Forest Block - Forested Patches (Acres) Percent of Block Consisting of Forest Patches 081A A , , ,753 1, ,119 2,

11 Forest Block ID Number Forest Block Area (Acres) Forest Block - Forested Patches (Acres) Percent of Block Consisting of Forest Patches Totals 26,025 17, The right side of Table 8 (see Table section at end of memorandum) presents the revised conceptual model and shows the relationships between all forest functions, attributes, and attribute measures as used in the analysis. Subsequent to the formulation of Forest Habitat Group functions, attributes, and measures as presented in the previous memorandum, the analysis framework has been substantially altered. The number of terrestrial habitat functions has been reduced since the early submitted drafts. The initial identified functions and supporting attributes were extensive, but upon closer investigation were found to be complicated and duplicative and did not allow a clear analysis of the primary terrestrial habitat functions. Terrestrial habitat functions initially included biodiversity, habitat creation and maintenance, support of trophic structure, nutrient cycling and soil development, thermoregulation and control of water quality and quantity. In further analysis it became apparent these functions were all common to mature forest systems and that identification of later seral systems would target forest habitats functioning at their highest level for this analysis. Meadow habitats were historically a limited habitat type in the study area. The habitat increased in area with the expansion of agriculture in the region and allowed the expansion of some species associated with this habitat. Since the majority of this habitat type is artificial, but important we have included it in the analysis. The analysis is restricted to presence of the habitat type, its connection to other similar habitats and association with other important habitat types. Specific data on plant and animal species utilizing the habitats is lacking. It also became apparent that there is a significant lack of data on terrestrial habitats in the study area. Specific data on plant and animal distributions across the entire study area was found in only two data sources: the Nahkeeta Northwest assessments performed in 1995 and 2003 and Washington Department of Fish and Wildlife Priority Habitat and Species data sets. The Nahkeeta NW data was well compiled, but may no longer reflect existing conditions. Data on species of concern (PHS and state and listed plant and animal species) is spotty and captures very few species. Information on habitat structure is also lacking. Other reviewed data originates from regional analysis on species distribution and lacks the specificity require for this analysis. Therefore, based on a lack of data and desire to eliminate weighting a measure too much (essentially double or triple counting) we simplified the functions into two functions, with appropriate attributes that have little overlap. Each function in the forest and meadow/shrub habitats is composed a number of attributes. This provides more 11

12 information to analyze and rank to assess existing conditions and to be used during the formulation of restoration actions. The left side of Table 8 provides detail on the selected attribute measure, including definition, data sets utilized in the analysis, the metrics (units) of the measures, and the weighting applied to combining multiple measure scores into a single attribute score (this applied only in some cases) and combining multiple attribute scores into a single function score (applied in all cases). The weighting factors for measures and attributes were developed using the same criteria discussed under the Riverine Habitat Group The data from individual wetland functions required normalization on a zero to one scale, and in some cases transposition, in order to have all metrics scaled where zero indicates the lowest comparative score and one the highest. The GIS analysis results were exported to Microsoft Excel, which was then used to calculate all measure, attribute, and function scores. Table 9 (see Table section at end of document) summarizes the raw outputs from this effort and the attached electronic Excel file contains the complete Excel spreadsheet, including all intermediate calculations and data transformation analysis steps. Meadow/Shrub Habitat Group For the Meadow/Shrub Habitat Group, data analysis was also conducted at the level of the meadow/shrub block, as delineated by NNW (2003) (see Conceptual Model memo for delineation details). The meadow/shrub habitat blocks were included in the analysis is there is at least one contiguous habitat patch, consisting of more than 5 acres of meadow/shrub habitat. A total of 46 habitat blocks were analyzed for conditions of existing meadow/shrub functions (Table 10 and Figure 5). Any meadow/shrub habitat block that was at least partially within the study area was included in the analysis. Other habitat patches which are outside, but adjacent to the study area were used for analysis of certain metrics (e.g. connectivity), but were not analyzed for ecological function within the block. Table 10. Meadow/Shrub Group s Analyzed for Existing Conditions of Ecological Function Meadow Block ID Number Meadow/ Shrub Block Area (Acres) Meadow/ Shrub Patch Area (Acres) Percent of Block Consisting of Meadow/ Shrub Patches

13 A The right side of Table 11 (see Table section at end of memorandum) presents the revised conceptual model and shows the relationships between all meadow/shrub functions, attributes, and attribute measures as used in the analysis. The general conceptual model used is nearly identical to those in the Forest Habitat Group, as upland habitat functions are similar in both types of vegetated habitat, therefore similar measures are appropriate. 13

14 Also, as discussed for the Forest Habitat Group and for similar reasons, the measures as presented in the previous memorandum, the analysis framework has been substantially altered. The left side of Table 11 provides detail on the selected attribute measure, including definition, data sets utilized in the analysis, the metrics (units) of the measures, and the weighting applied to combining multiple measure scores into a single attribute score (this applied only in some cases) and combining multiple attribute scores into a single function score (applied in all cases). The weighting factors for measures and attributes were developed using the same criteria discussed under the Riverine Habitat Group The data from individual wetland functions required normalization on a zero to one scale, and in some cases transposition, in order to have all metrics scaled where zero indicates the lowest comparative score and one the highest. The GIS analysis results were exported to Microsoft Excel, which was then used to calculate all measure, attribute, and function scores. Table 12 (see Table section at end of document) summarizes the raw outputs from this effort and the attached electronic Excel file contains the complete Excel spreadsheet, including all intermediate calculations and data transformation analysis steps. Nearshore and Estuarine Habitat Group In January, 2013, Coastal Geologic Services (CGS) completed the WRIA 1 Nearshore & Estuarine Assessment and Restoration Prioritization (MacLennan et al., 2013). For the assessment of existing conditions, we used the geodatabase results from their work along with ancillary information to document the existing conditions specific to the City of Bellingham s nearshore environment. First, the dominant shoreforms in the project area were identified, based on the Puget Sound Nearshore Ecosystem Restoration Project (PSNERP) shoreform mapping (Shipman, 2008). The breakdown of shoreform units at the scale of the project area is presented in Table 13 and Figure 6. Table 13: Shoreform Composition of Bellingham Shoreform Count Total Length (Miles) Average Length (Miles) % Length of Bellingham Shoreline Artificial Barrier Estuary Barrier Lagoon Bluff-backed Beach Pocket Beach Plunging Rocky Rocky Platform As with the WRIA 1 analysis, the next step was an analysis, limited to the project area extent, of 1) submerged aquatic vegetation (SAV) occurrences for eelgrass and bull kelp, 2)forage fish spawning areas and distribution, and 3) salt marshes and freshwater inputs, all categorized by the geomorphic shoreform. Results of these analyses are presented in Tables 14 through

15 Shoreform Table 14. Eelgrass and Bull Kelp Occurrence by Geomorphic Shoreform Count Shoreforms with SAV Length of Bull Kelp (ft) Percent of Bull Kelp Length of Eelgrass (ft) Percent of Eelgrass Artificial , Barrier Estuary , Barrier Lagoon Bluff-backed Beach Pocket Beach Plunging Rocky Rocky Platform , Table 15. Distribution of surf smelt and sand lance spawning in Bellingham by Geomorphic Shoreform Shoreform Count Number with Smelt Spawning Length with Smelt Spawning (ft) Percent of Bellingham with Smelt Spawning Number with Sand Lance Spawning Length with Sand Lance Spawning (ft) Percent of Bellingham with Sand Lance Spawning Artificial , , Barrier Estuary Barrier Lagoon Bluff-backed Beach 2 1 5, Pocket Beach Plunging Rocky Rocky Platform Table 16. Salt Marshes and Freshwater Inputs by Geomorphic Shoreform Shoreform Count Number with Salt Marsh Percent with Salt Marsh Length with Salt Marsh (ft) Number with Freshwater Inputs Percent with Freshwater inputs Artificial , Barrier Estuary , Barrier Lagoon , Bluff-backed Beach Pocket Beach Plunging Rocky Rocky Platform

16 Nearshore process degradation and the occurrence of various stressors were mapped and analyzed as part of multiple PSNERP efforts, primarily the Change Analysis (Simenstad et al. 2011) and the Strategic Needs Assessment Report (SNAR, Schlenger et al. 2011). Data from these regional efforts were mapped and analyzed to form an appropriate measure of nearshore stressors, which will ultimately compared to strategies and priorities. The results were summarized and interpreted for the project area to highlight what actions to apply where across the nearshore landscape. The results of the project area stressor analysis indicate that armoring is shoreline armoring is by far the predominant in the study area, mostly occurring in artificial and rocky platform shoreform types (Table 17). Railroad fill and right-of-way also contributes as a significant stressor. Table 17. Length of Nearshore Stressors in Project Area by Geomorphic Shoreform Shoreform Fill (ft) Armoring (ft) Railroads (ft) Roads (ft) Marinas (ft) Breakwaters and Jetties (ft) Artificial 0 28, Barrier Estuary Barrier Lagoon Bluff-backed Beach 0 2, Pocket Beach Plunging Rocky Rocky Platform 0 9,399 9, TOTALS 0 40,572 9, In order to prioritize potential restoration actions, the data presented in this section will ultimately be combined with the Ecological Value Criteria (EVC) score for various nearshore and estuarine processes. The EVC scores represent the existing condition of the processes and are somewhat analogous to the function scores for the other four habitat groups addressed in the Plan. The EVC scores in the project area are presented and discussed in the next section of the memorandum. EXISTING CONDITIONS ANALYSIS RESULTS This section summarizes the preliminary results of combining the numerous attribute measures to assess the functions within each of the four applicable habitat groups. The results of the separate nearshore analysis are also presented. For each analysis unit (e.g., sub-watershed or habitat block) in each habitat group, a total function score was calculated. Within a habitat group, each function scores were rank ordered, then the analysis unit assigned a relative ranking. Various ranking strategies for classifying relative ecological function were explored by the technical team. Ideally, the selected strategy would result in four to five data groups, with the upper and lower data group consisting primarily of the tails of the data distribution, including any data outliers. These extreme low and high values are important to classify because they likely will be the primary focus of preservation and restoration actions. The strategies assessed for grouping function scores included assigning groups based on the standard deviation of the analysis unit scores. Several methods were assessed, including using one-half, one, or two standard deviations 16

17 to create the classification system. The use of standard deviations for classification of functional categories proved problematic for several reasons. In many cases, the classification was too broad, with too few categories due to the large spread of data. The standard deviation approaches often combined data points in the upper and lower ranges of the distribution with the group around the mean, while also placing the middle data group significantly outside of the median function score. Another approach included dividing the data into quartiles or quintiles (four or five groups with even numbers of data points). This approach had the advantage of centering the middle group(s) of data directly around the median value, while the upper and lower categories effectively defined the highest and lowest values in the dataset. It was determined that the use of quintiles (five groups) would be more effective for future determination of restoration actions, as this classification allows greater flexibility in analyzing existing conditions. However, for some of the habitat groups analyzed, the numbers of analysis units were not directly divisible by five. Therefore, the categories were slightly altered so all data points (analysis units) would be considered and classified. In order to rank order the data, the highest and lowest groups were assigned slightly fewer values than the middle 3 groups. In some cases the middle group also had slightly more data points than all groups. This approach results in similar sized groups, while ensuring that the upper and lower groups are not overly represented. It should be reiterated that the overall analysis approach only compares conditions of functions within the study area, and does not assess these functions in relation to the range of natural conditions over a larger area (e.g., WRIA 1 or the Puget Sound). In order to emphasize this important point, the sum of the categories is termed Relative Functional Condition Score. In addition, terminologies for the five data categories that compose the scores are as follows, in order from lowest ecological function to highest. Lowest The analysis units classified into the group had the very lowest function scores. This group included the lower outliers and would be a primary focus for investigating restoration actions to increase function. Lower The analysis units classified into the group had function scores higher than the lowest group, but lower than the median group. This group could be a focus for investigating restoration actions to increase function, especially if other associated functions in the habitat group are low functioning. Median By definition of the quintile grouping method, the analysis units classified into the group had scores at, and adjacent to. The median scores for the group. Units in this group generally represent the median condition for the function in question within the study area. Analysis units in this group will likely not be the primary focus of restoration or preservation efforts targeted at the function being analyzed. Higher The analysis units classified into the group had function scores lower than the highest group, but higher than the median group. This group could be a focus for investigating preservation actions to maintain function, especially if other associated functions in the habitat group are high functioning. Highest The analysis units classified into the group had the very highest function scores. This group included the upper outliers and would be a primary focus for investigating preservation actions to maintain function. Riverine Habitat Group Results A total of 24 analysis units (data points) were examined for each of the six riverine functions analyzed. The ranking of the analysis units into Relative Functional Condition Score categories included four analysis units in each of the highest and lowest categories, five analysis units each in the intermediate categories, and six analysis units in the median category. Results of the functional analysis show general patterns of high/low function across 17

18 all of the functions, although many of the sub-watersheds show substantial variation across all of the functions (Table 18). Table 18. Relative Functional Condition Score for All Analyzed Functions in the Riverine Habitat Group by Sub-Watershed RIVERINE HABITAT GROUP FUNCTION Flow Variation Function Surface Storage Function Biodiversity Maintenance Habitat Creation and Maintenance Chemical Regulation Thermoregulation Alderwood Creek Lower Median Lower Lowest Lower Median Baker Creek Tributary Median Median Lowest Lower Lowest Median Bear Creek Lower Highest Median Lower Median Higher Cemetery Creek Higher Lower Higher Highest Median Lower Chuckanut Creek Highest Lower Higher Highest Highest Highest Connelly Creek Lower Median Lower Higher Lower Lowest Fever Creek Lowest Median Lower Lower Lowest Lower Fort Bellingham Median Highest Highest Lower Median Lowest Hannah Creek Higher Lowest Median Median Median Higher Lake Padden Highest Highest Lowest Higher Higher Higher Lincoln Creek Lowest Higher Lower Median Lower Lower Little Squalicum Creek Lowest Median Lowest Lowest Higher Higher Lost Creek Higher Highest Higher Lowest Higher Lower Lower Baker Creek Median Lower Median Median Lowest Median Lower Padden Creek Median Lower Lower Median Lower Median Lower Spring Creek Lower Lower Highest Median Lower Higher Lower Squalicum Median Higher Higher Higher Median Lowest Lower Toad Creek Higher Lowest Median Higher Higher Median Lower Whatcom Creek Lowest Lowest Highest Median Lowest Lowest Silver Creek Tributary #1 Median Higher Higher Lower Higher Median Silver Creek Tributary #2 Lower Median Lowest Lowest Median Lower Spokane Creek Highest Higher Median Higher Highest Highest Upper Padden Creek Higher Lowest Median Highest Highest Highest Upper Whatcom Creek Highest Higher Highest Highest Highest Highest Wetland Habitat Group Results A total of 28 analysis units (data points) were examined for each of the seven wetland functions analyzed. The ranking of the analysis units into Relative Functional Condition Score categories included four analysis units in each of the highest and lowest categories and five analysis units each in the intermediate categories and the median category. Results of the functional analysis show general patterns of high/low function across all of the functions, although many of the sub-watersheds show substantial variation across all of the functions (Table 19). 18

19 Table 19. Relative Functional Condition Score for All Analyzed Functions in the Wetland Habitat Group by Sub-Watershed Sub watershed Surface Water Storage Nitrogen Removal WETLAND HABITAT GROUP FUNCTION Pathogen Removal Organic Matter Export/ Contribution Sediment/ Phosphorus Removal Wildlife Habitat Carbon Sequestration Alderwood Creek Lowest Lower Lower Lowest Lower Lower Lower Baker Creek Tributary Higher Highest Highest Median Higher Higher Higher Bear Creek Higher Highest Higher Higher Highest Highest Median Cemetery Creek Highest Higher Median Highest Median Higher Higher Central Bellingham Lowest Lowest Highest Lowest Lowest Lowest Lowest Chuckanut Creek Highest Higher Highest Higher Higher Highest Highest Connelly Creek Median Lower Lower Median Lowest Median Lower Fever Creek Median Lower Lowest Median Median Median Higher Fort Bellingham Median Higher Higher Lowest Higher Lower Lower Hannah Creek Highest Median Median Higher Median Median Highest Lake Padden Higher Higher Median Higher Median Higher Higher Lincoln Creek Lower Median Lower Lower Lower Lower Median Little Squalicum Creek Lower Lowest Lowest Lower Lower Lowest Lowest Lost Creek Median Highest Higher Median Higher Median Median Lower Baker Creek Higher Median Higher Higher Highest Higher Median Lower Padden Creek Lower Lower Lower Lower Lowest Median Median Lower Spring Creek Lower Median Median Lower Higher Median Lower Lower Squalicum Higher Highest Higher Higher Highest Highest Median Lower Toad Creek Lower Lower Higher Median Median Lowest Lower Lower Whatcom Creek Lowest Lowest Lowest Lowest Lowest Lower Lowest North Lower Squalicum Lower Lowest Lowest Lower Lower Lowest Highest Silver Creek Tributary #1 Median Highest Highest Highest Higher Higher Lower Silver Creek Tributary #2 Higher Median Highest Highest Highest Lower Higher South Bellingham Lowest Lower Lower Lowest Lower Highest Lowest Spokane Creek Highest Higher Median Highest Highest Highest Highest Squalicum Harbor Lowest Lowest Lowest Lower Lowest Lowest Lowest Upper Padden Creek Median Median Lower Median Lower Lower Higher Upper Whatcom Creek Highest Higher Median Highest Median Higher Highest 19

20 Forest Habitat Group A total of 85 analysis units (forest blocks) were examined for each of the two forest functions analyzed. The ranking of the analysis units into Relative Functional Condition Score categories included four analysis units in each of the highest and lowest categories and five analysis units each in the intermediate categories and the median category. Results of the functional analysis show general patterns of high/low function between both functions, although several of the habitat blocks show substantial variation across both of the functions (Table 20). Table 20. Relative Functional Condition Score for All Analyzed Functions in the Forest Habitat Group by Forested Habitat Block Forest Block ID Number FOREST HABITAT GROUP FUNCTION Habitat Maintenance Function Biodiversity Function Score Score 002 Highest Highest 003 Higher Higher 004 Highest Highest 005 Median Median 006 Highest Highest 007 Highest Highest 009 Highest Highest 011 Highest Highest 011A Higher Higher 011B Higher Higher 012 Median Lower 013 Median Median 016 Lower Median 024 Median Median 032 Median Lower 032A Lowest Lowest 034 Lowest Median 035 Lowest Higher 037 Lower Lower 040 Higher Median 041 Lower Lower 042 Highest Highest 043 Median Median 052 Highest Highest 052A Median Median 056 Lowest Lower 060 Highest Higher 068 Median Median 20

21 069 Lower Lower 072 Highest Median 073 Higher Median 074 Median Median 075 Higher Higher 076 Median Median 078 Lowest Lowest 081A Lower Lowest 089 Median Higher 089A Median Lower 090 Lowest Lowest 099 Lowest Lowest 100 Lower Lowest 101 Lower Lowest 108 Lowest Median 111 Lowest Lowest 112 Lower Median 113 Lower Lower 114 Median Median 116 Median Median 119 Median Median 120 Lower Lower 121 Median Higher 122 Higher Highest 123 Lower Lower 124 Lower Lower 125 Lower Lowest 126 Higher Higher 127 Higher Higher 128 Higher Median 129 Median Higher 130 Median Lowest 131 Lowest Lower 133 Lower Lower 134 Highest Highest 135 Lowest Lower 137 Median Highest 138 Higher Higher 140 Higher Median 141 Median Highest 142 Highest Highest 21

22 143 Higher Highest 146 Median Higher 147 Higher Higher 148 Highest Higher 149 Higher Median 150 Lower Lower 151 Higher Median 153 Lowest Lowest 155 Median Median 157 Lower Median 158 Median Median 165 Highest Lower 171 Lowest Lowest 178 Median Lowest 179 Median Higher 192 Lowest Lowest Meadow/Shrub Habitat Group A total of 46 analysis units (shrub/meadow blocks) were examined for each of the two forest functions analyzed. The ranking of the analysis units into Relative Functional Condition Score categories included four analysis units in each of the highest and lowest categories and five analysis units each in the intermediate categories and the median category. Results of the functional analysis show general patterns of high/low function between both functions, although many of the habitat blocks show substantial variation across both of the functions (Table 21). Table 21. Relative Functional Condition Score for All Analyzed Functions in the Meadow/Shrub Habitat Group by Meadow/Shrub Habitat Block Block ID Number Meadow/Shrub Habitat Group Function Biodiversity Function Score Habitat Maintenance Function Score 002 Higher Higher 003 Median Lowest 004 Highest Highest 006 Highest Median 011 Median Lower 022 Lowest Median 039 Lower Median 040 Higher Higher 041 Lowest Lowest 052 Highest Highest 060 Highest Higher 22

23 068 Higher Median 072 Higher Higher 073 Median Highest 076 Lowest Lower 101 Median Median 108 Median Lowest 108A Lowest Lower 111 Lower Median 113 Higher Median 114 Median Median 118 Median Median 120 Median Lowest 122 Highest Higher 123 Lower Higher 124 Lower Higher 125 Lowest Lowest 126 Median Median 127 Median Highest 128 Higher Highest 130 Median Lower 132 Lowest Lowest 133 Median Lower 134 Highest Highest 137 Higher Median 138 Median Highest 140 Median Higher 142 Highest Higher 149 Higher Median 150 Lowest Lower 151 Higher Lower 153 Lower Lowest 155 Lower Lower 157 Lower Lower 158 Lower Median 178 Lower Median 23

24 Nearshore and Estuarine Habitat Group Results In order to characterize existing conditions of ecological processes within the Nearshore and Estuarine Habitat Group, the EVC of each analysis unit was analyzed. The analysis units are defined as drift cells (or alternatively as process units). The EVC values from the WRIA 1 assessment (MacLennan et al., 2013) were exported to the current projects geo-database and the linear drift cell dataset was clipped to the project area (City/UGA limits). The EVC scores were then length-weighted by determining the percent of the total drift-cell length that was composed of each shoreform. That percentage was multiplied by the EVC score for the shoreform. Each lengthweighted EVC score was then summed for all shoreforms within each drift cell, and the EVC was scored for the project area (Table 22), both with and without shellfish considered. Table 22. Length-weighted EVC Scores for Drift Cells Within the Project Area Drift Cell Artificial Barrier Estuary Barrier Lagoon Bluffedbacked Beach Pocket Beach Plunging Rocky Rocky Platform Total Score Total Score (No Shellfish) ART ART PB PL RP RP RP RP RP WH NAD WH WH-5-22/ WH-H WH NAD WH-H WH-H-1/ WH-H WH-H WH-H WH-H- 3/WH-H WH-H

25 In addition, degradation of the nearshore processes was scored on a scale of high, medium, and low (Table 23). Although these results are color coded into categories of high, medium, and low to approximate the data presentation format of habitat functions of the other habitat group, note that data presented measures the amount of degradation (low function). Although the WRIA 1 report (MacLennan et al., 2013) determined that sediment supply and tidal flow were driving overall degradation within drift cells, the degradation for all processes is presented here. Table 23. Nearshore Process Degradation (Level of degradation - H=high, M=medium, L=low, NA=not applicable) Drift Cell (Process Unit) Sediment Supply Sediment Transport Accretion of Sediment Tidal Flow Distributary Channel Formation Tidal Channel Formation Freshwater Input Detritus Import and Export Exchange of Aquatic Organisms Physical Disturbance Solar Incidence SPU 7157 M H H H NA None M H H H M SPU 7159 H H H H NA None M H H H M SPU 7161 H H H H NA None M M M M L SPU 7158 H H H H NA None M H H H M SPU 7160 H H H H NA None M H H H M 25

26 DATA GAPS During the establishment of the conceptual model and development of specific attribute measures, a number of data gap were identified, that if filled, would allow a more robust and sensitive analysis. Table 23 lists the key data gaps for each Habitat Group, as well as the relevance of the information to both the current analysis for purposes of producing the Plan, as well as other potential benefits to the City that procurement of this data may provide. 26

27 Table 23. Key Data Gaps Identified for Each Habitat Group Habitat Group Priority (H = Highest, M=Moderate, L= Lowest) Data Gap Description Additional Information and Relevance to BHRMP Relevance to Other COB Departments and Uses Riverine H Mapping of floodplain and CMZs within the City of Bellingham/UGA Detailed information on presence of stream floodplain and CMZs would assist in refining measures for multiple functions in the analysis for riverine and wetland habitat groups, resulting in more accurate and precise measures for flood storage, off-channel habitat, and riparian wetlands. This information would potentially provide City key data for planning, implementation, and regulation of 1) flood control and floodplain development, 2) shoreline and critical areas, 3) non-bhrmp mitigation and restoration, and 4) hydraulic and hydrologic modeling and monitoring efforts, 5) comprehensive planning efforts. Riverine H Mapping of stream bank condition, including mapping of armoring/confinement (mapping of levees, dikes, walls, rip-rapped channel segments) and reaches of bank instability (mapping of bank sloughing, slumping, fracturing, slides and similar features). Detailed information on streambank conditions would assist in refining measures for multiple functions in the analysis for riverine habitat groups, resulting in more accurate and precise measures for flood storage, off-channel habitat, and other riparian functions. Could be done in conjunction with streambank mapping exercise to develop polygon (versus existing line) COB GIS stream layer. This information would potentially provide City key data for planning, implementation, and regulation of 1) flood control and floodplain development, 2) project implementation and success monitoring, 3) mitigation and restoration, and 4) stormwater, hydraulic, and hydrologic modeling and monitoring efforts. Riverine M Results from B-IBI, or other similar macroinvertebrate index, for streams within the City/UGA. Results from an annual or biennial B-IBI sampling would provide a key metric for riverine biodiversity and could assist in developing additional measures for other functions such as water quality (using pollution tolerant taxa data), trophic structure (data on shredders and grazers). A B-IBI sampling program would ideally include all watersheds within Bellingham, and sampling locations in upper and lower basin positions and key tributaries. This information would potentially provide City key data for planning, implementation, and regulation of 1) project implementation and success monitoring 2) water quality programs including TMDL and 303(d) listed reaches, 3) non- BHRMP mitigation and restoration efforts

28 Habitat Group Priority (H = Highest, M=Moderate, L= Lowest) Data Gap Description Additional Information and Relevance to BHRMP Relevance to Other COB Departments and Uses Riverine M Comprehensive stream surveys to determine channel morphology, substrate, confinement, and other key habitat features. Detailed information on instream habitat would assist in refining riverine function measures, resulting in more accurate and precise measures for instream habitat, as well as sediment functions. Could be done in conjunction with streambank mapping exercise as described above to add detailed habitat information to COB GIS stream layer. This information would potentially provide City key data for planning, implementation, and regulation of 1) project implementation and success monitoring, and 2) non- BHRMP mitigation and restoration efforts Wetland Wetland H M Wetland inventory verifications and updates, including site specific wetland boundary information, wetland classifications and ratings from delineations submitted to the City. Aquatic/wetland dependent fish, wildlife, and rare/significant native plant species inventory for wetlands within the City/UGA. In some cases, data in this analysis is ten to twenty years old or more (e.g., wetland inventories from 1992 and 2003) and may have relied on aerial photography with limited groundtruthing. Accurate wetland mapping would assist the City in refining several measures in this analysis. Additional species inventory would strengthen wetland biodiversity measures in this analysis. This information would be useful to the City in planning, implementation, and regulation with respect to Critical Areas, Shoreline Management, and Comprehensive Planning. This information would provide the city with specific locations of high wetland biodiversity to be used in planning, implementation and regulation of COB Critical Areas Ordinance, Shoreline Management programs and comprehensive planning efforts Wetland M Wetland hydrology characteristics (e.g., Cowardin water regimes, source of hydrology inputs/outputs, area of contributing basin, connectivity, depth and duration of ponding, and live storage) Detailed information on wetland hydrology characteristics would refine hydrology and water quality functions of wetlands. The City s sitespecific GIS information included some hydrology information, but did not include enough coverage of the analysis area. Additional information from critical areas studies could be incorporated into City databases or the City could partner with local naturalist groups to set up citizen science programs to collect data. This information would be useful to the City in planning, implementation, and regulation with respect to Critical Areas, Shoreline Management, Comprehensive Planning, wetland mitigation and restoration monitoring. Wetland M Inventory and mapping of invasive plant cover Accurate mapping of invasive plant populations is important in wetland habitat management. Whatcom County noxious weed board provides assistance, but they are behind in mapping and do not keep records on all invasive plants. This information would provide the city with specific locations of invasive species populations to be used in planning, implementation and regulation of COB Critical 28

29 Habitat Group Priority (H = Highest, M=Moderate, L= Lowest) Data Gap Description Additional Information and Relevance to BHRMP Relevance to Other COB Departments and Uses Wetland Meadow/ Shrub M M Inventory and mapping of organic soils and soil carbon content. Terrestrial species inventory of wildlife within City/UGA Could partner with local naturalist groups to set up citizen science programs to collect data. Information on the extent of organic soils and soil carbon storage is important for calculating carbon sequestration in wetlands and responding to climate change. Could partner with local naturalist groups to set up citizen science programs to collect data. Results from an inventory of terrestrial wildlife species would provide a strong metric for terrestrial (forest and meadow/shrub) biodiversity. Inventory could be limited to indicator species within a taxa or guild to reduce cost but still retain analysis value. Could partner with local naturalist groups to set up citizen science programs to collect data. Areas Ordinance, Shoreline Management programs, comprehensive planning efforts, and wetland restoration/mitigation monitoring. This information would be useful to the City in planning, implementation, and regulation with respect to Critical Areas, Shoreline Management, Comprehensive Planning, wetland mitigation and restoration monitoring. This information would provide the city with specific locations of high biodiversity to be used in planning, implementation and regulation of COB Critical Areas Ordinance, Shoreline Management programs and comprehensive planning efforts Meadow/ Shrub Meadow/ Shrub Meadow/ Shrub H M M Update data in Nahkeeta NW 2003 City of Bellingham Wildlife Habitat Assessment Inventory and mapping of invasive plant cover Inventory and mapping of invasive wildlife The data in this analysis is over ten years old. Development during that time has altered habitat block conditions and project conclusions. Accurate mapping of invasive plant populations is important in terrestrial habitat management. Whatcom County noxious weed board provides assistance, but they are behind in mapping and do not keep records on all invasive plants. Could partner with local naturalist groups to set up citizen science programs to collect data. No data was located on invasive wildlife distribution and/or status. This data can be important in managing sensitive plant and animal species populations. Could partner with This information would provide the city with specific locations of high biodiversity to be used in planning, implementation and regulation of COB Critical Areas Ordinance, Shoreline Management programs and comprehensive planning efforts This information would provide the city with specific locations of high biodiversity to be used in planning, implementation and regulation of COB Critical Areas Ordinance, Shoreline Management programs and comprehensive planning efforts This information would provide the city with specific locations of high biodiversity to be used in planning, implementation and 29

30 Habitat Group Priority (H = Highest, M=Moderate, L= Lowest) Data Gap Description Additional Information and Relevance to BHRMP Relevance to Other COB Departments and Uses Meadow/ Shrub Meadow/ Shrub Meadow/ Shrub Meadow/ Shrub M L H M Inventory and mapping of sensitive and locally important native plant populations Assessment and mapping of forest habitat structure Identification of significant habitat corridors Terrestrial species inventory of wildlife within City/UGA local naturalist groups to set up citizen science programs to collect data. Results from an inventory of terrestrial wildlife species would provide a strong metric for terrestrial (forest and meadow/shrub) biodiversity. Inventory could be limited to indicator species within a taxa or guild to reduce cost but still retain analysis value. This data is partially presented in the 1995 and 2003 Nahkeeta NW datasets, but is out of date and limited in the original scope. Could partner with local naturalist groups to set up citizen science programs to collect data. This data is partially presented in the 1995 and 2003 Nahkeeta NW datasets, but is out of date since significant development has occurred since the analysis was performed. Results from an inventory of terrestrial wildlife species would provide a strong metric for terrestrial (forest and meadow/shrub) biodiversity. Inventory could be limited to indicator species within a taxa or guild to reduce cost but still retain analysis value. Could partner with local naturalist groups to set up citizen science programs to collect data. regulation of COB Critical Areas Ordinance, Shoreline Management programs and comprehensive planning efforts This information would provide the city with specific locations of high biodiversity to be used in planning, implementation and regulation of COB Critical Areas Ordinance, Shoreline Management programs and comprehensive planning efforts This information would provide the city with specific locations of high biodiversity to be used in planning, implementation and regulation of COB Critical Areas Ordinance, Shoreline Management programs and comprehensive planning efforts This information would provide the city with specific locations of high biodiversity to be used in planning, implementation and regulation of COB Critical Areas Ordinance, Shoreline Management programs and comprehensive planning efforts This information would provide the city with specific locations of high biodiversity to be used in planning, implementation and regulation of COB Critical Areas Ordinance, Shoreline Management programs and comprehensive planning efforts 30

31 NEXT STEPS This memorandum and the data and preliminary results presented within, including functional rating of analysis units within all habitat groups, will undergo technical review by the City and Bellingham and the Plan TAG. The analysis parameters and this memorandum will be revised if necessary, based on both reviewer comments and a final assessment of available analysis area data. The final existing condition analysis will be used as a tool to assess potential restoration actions in the study area and to prioritize these actions. Specific tasks associated with this next project milestone include: Coordinate with City and TAG to review the existing conditions analysis. Incorporate recommended additional data (if available) into GIS database and analysis. Develop and characterize list of project actions for subsequent analysis. For each Habitat Group, develop a matrix assessing the relative effect of each restoration action on each function. For each Habitat Group, expand matrix to include outcomes for restoration actions, based on existing condition score and potential uplift. Initial prioritization of restoration actions (solely based on a science-based approach and without consideration of various constraints).

32 REFERENCES Anchor QEA and Northwest Geologic Services. September City of Bellingham Habitat Restoration Plan: Limiting Factors Analysis. Brown, M., M. Maudlin, and J. Hansen. Nooksack River Estuary Habitat Assessment. Report for Salmon Recovery Funding Board, Office of Interagency Committee, IAC # N. April 30, Lummi Nation Natural Resources Department. Bellingham, WA. Cassidy, K.M., M.R. Smith, C.E. Grue, K.M. Dvornich, J.E. Cassady, K.R. McAllister, and R.E. Johnson Gap Analysis of Washington State: an evaluation of the protection of biodiversity. Volume 5 in Washington State Gap Analysis- Final Report (K.M. Cassidy, C.E. Grue, M.R. Smith, and K.M. Dvornich, eds). Washington Cooperative Fish and Wildlife Research Unit, University of Washington, Seattle, 192 pp. City of Bellingham Sehome and Vicinity Plat Map. Accessed at: Date Accessed: February 18, City of Bellingham Bellingham Bay Cities Plat Map. Accessed at: Date Accessed: February 18, City of Bellingham Fairhaven and Vicinity Map. Accessed at: Date Accessed: February 18, Coastal Geologic Services. January 17, WRIA 1 Nearshore and Estuarine Assessment and Restoration Prioritization. Collins, B., D.R. Montgomery, and A.J. Sheik Reconstructing the Historical Riverine Landscape of the PugetLowland. In: D. R. Montgomery, S. M. Bolton, D. B. Booth, and L. Wall, eds.restoration of Puget Sound Rivers, University of Washington Press, Seattle, WA. pp Eissinger, Ann Wildlife and Habitat Assessment, an inventory of existing conditions and background information and wildlife habitat plan. City of Bellingham Department of Planning and Development General Land Office (GLO). 1859, 1872, 1873, 1874, Historic Plat Survey Maps. Accessed at: Date Accessed: February 18, MacLennan, A., P. Schlenger, S.Williams, J. Johannessen, and H. Wilkinson WRIA 1 Nearshore & Estuarine Assessment and Restoration Prioritization - Draft Report. Prepared for the City of Bellingham. January 17, Nahkeeta Northwest City of Bellingham Wildlife Habitat Assessment. Prepared for City of Bellingham Department of Public Works Environmental Division. March Bellingham, Washington. Northwest Ecological Services City of Bellingham Shoreline Characterization and Inventory Report. 32

33 Schlenger, P., A. MacLennan, E. Iverson, K. Fresh, C. Tanner, B. Lyons, S. Todd, R. Carman, D. Myers, S. Campbell, and A. Wick Strategic Needs Assessment: Analysis of Nearshore Ecosystem Process Degradation in Puget Sound. Prepared for the Puget Sound Nearshore Ecosystem Restoration Project. Technical Report Available at pugetsoundnearshore.org. Scott, G.R. and J.D. McDowell Whatcom County comprehensive plan: environmental impact statement, existing conditions report. Whatcom County Planning and Development Services Dept. Bellingham, Washington. 136 pp. Shipman, H., A Geomorphic Classification of Puget Sound Nearshore Landforms. Puget Sound Nearshore Partnership Report No Published by the US Army Corps of Engineers, Seattle, Washington. Simenstad, C., Ramirez, M., Burke, J., Logsdon, M., Shipman, H., Tanner, C., Davis, C., Fung, J., Block, P., Fresh, K., Campbell, S., Myers, D., Iverson, E., Bailey, A., Schlenger, P., Kiblinger, C., Myre, P., Gerstel, W., and MacLennan, A., Historic Change and Impairment of Puget Sound Shorelines: Puget Sound Nearshore Ecosystem Project Change Analysis. Puget Sound nearshore Report No XX. Published by Washington Department of Fish and Wildlife, Olympia, Washington, and U.S. Army Corps of Engineers, Seattle, Washington. Smith, C.J Salmon and steelhead habitat limiting factor in WRIA 1, the Nooksack Basin. Washington State Conservation Commission. July, Olympia, Washington. Wahl, Tim. City of Bellingham Parks Department. Personal communication

34 FIGURES 34

35 Whatcom County 5 Project Area Birch Bay Lake Whatcom San Juan County Skagit County 5 S:\GIS\Projects\12xxxx\D120902_BellinghamHabitatRestoration\Mxd\Habitat Groups\Vicinity.mxd (MJL, 2/20/2013) Legend Project Area Streams Water Bodies Other Water Bodies SOURCE City of Bellingham, 2012, ESA, 2012, ESRI, Bellingham Habitat Restoration Master Plan Figure 1 Bellingham Habitat Restoration Master Plan Study Area Bellingham, Washington Miles

36 SILVER CREEK SILVER CREEK TRIBUTARY #2 UPPER SPRING CREEK SILVER CREEK TRIBUTARY #1 SILVER CREEK UPPER BAKER CREEK UPPER SQUALICUM LOST CREEK FORT BELLINGHAM ALDERWOOD CREEK BEAR CREEK NORTH LOWER SQUALICUM LOWER SPRING CREEK BAKER CREEK TRIBUTARY LOWER BAKER CREEK SQUALICUM CREEK LOWER TOAD CREEK UPPER TOAD CREEK BELLINGHAM BAY NORTH BELLINGHAM BAY LITTLE SQUALICUM CREEK LITTLE SQUALICUM CREEK SQUALICUM HARBOR CENTRAL BELLINGHAM LOWER SQUALICUM LOWER WHATCOM CREEK LINCOLN CREEK FEVER CREEK UPPER WHATCOM CREEK WHATCOM CREEK CEMETERY CREEK HANNAH CREEK LAKE WHATCOM LOWER PADDEN CREEK CONNELLY CREEK PADDEN CREEK UPPER PADDEN CREEK LAKE PADDEN SOUTH BELLINGHAM SPOKANE CREEK CHUCKANUT CREEK CHUCKANUT CREEK S:\GIS\Projects\12xxxx\D120902_BellinghamHabitatRestoration\Mxd\Habitat Groups\Riverine.mxd (MJL, 2/20/2013) Legend Project Area Analysis Area Watersheds s Streams Water Bodies Other Water Bodies Basin Type 1 2a 2b 3 CHUCKANUT BAY CHUCKANUT BAY s Excluded from Analysis Note: No natural stream features in Type 1 sub-watersheds SOURCE City of Bellingham, 2012, ESA, 2012, ESRI, Bellingham Habitat Restoration Master Plan Figure 2 Riverine Habitat Group Analysis Units Bellingham, Washington Miles

37 SILVER CREEK SILVER CREEK TRIBUTARY #2 UPPER SPRING CREEK SILVER CREEK TRIBUTARY #1 SILVER CREEK UPPER BAKER CREEK UPPER SQUALICUM LOST CREEK FORT BELLINGHAM ALDERWOOD CREEK BEAR CREEK NORTH LOWER SQUALICUM LOWER SPRING CREEK BAKER CREEK TRIBUTARY LOWER BAKER CREEK SQUALICUM CREEK LOWER TOAD CREEK UPPER TOAD CREEK BELLINGHAM BAY NORTH BELLINGHAM BAY LITTLE SQUALICUM CREEK LITTLE SQUALICUM CREEK SQUALICUM HARBOR CENTRAL BELLINGHAM LOWER SQUALICUM LOWER WHATCOM CREEK LINCOLN CREEK FEVER CREEK UPPER WHATCOM CREEK WHATCOM CREEK CEMETERY CREEK HANNAH CREEK LAKE WHATCOM LOWER PADDEN CREEK CONNELLY CREEK PADDEN CREEK UPPER PADDEN CREEK LAKE PADDEN SOUTH BELLINGHAM SPOKANE CREEK CHUCKANUT CREEK CHUCKANUT CREEK S:\GIS\Projects\12xxxx\D120902_BellinghamHabitatRestoration\Mxd\Habitat Groups\Wetlands.mxd (MJL, 2/20/2013) Legend Project Area Analysis Area Watersheds s Streams Wetlands Water Bodies Other Water Bodies CHUCKANUT BAY CHUCKANUT BAY SOURCE City of Bellingham, 2012, ESA, 2012, ESRI, Bellingham Habitat Restoration Master Plan Figure 3 Wetland Habitat Group Analysis Units Bellingham, Washington Miles

38 S:\GIS\Projects\12xxxx\D120902_BellinghamHabitatRestoration\Mxd\Habitat Groups\Forest.mxd (MJL, 2/20/2013) Legend Project Area Forest Patches > 5 Acres Habitat Blocks Streams Water Bodies Other Water Bodies SOURCE City of Bellingham, 2012; ESRI, 2010; Nahkeeta, Note: Analysis area includes those habitat blocks that contain forest patches greater than 5 acres and are either fully within or intersect the project area boundary. Bellingham Habitat Restoration Master Plan Figure 4 Forest Habitat Group Analysis Units Bellingham, Washington Miles

39 S:\GIS\Projects\12xxxx\D120902_BellinghamHabitatRestoration\Mxd\Habitat Groups\Meadow.mxd (MJL, 2/20/2013) Legend Project Area Shrub/Meadow Patches > 5 Acres Habitat Blocks Streams Water Bodies Other Water Bodies SOURCE City of Bellingham, 2012; ESRI, 2010; Nahkeeta, Note: Analysis area includes those habitat blocks that contain shrub/meadow patches greater than 5 acres and are either fully within or intersect the project area boundary. Bellingham Habitat Restoration Master Plan Figure 5 Shrub/Meadow Habitat Group Analysis Units Bellingham, Washington Miles

40 WH-5-22 WH-5-22-NAD WH-5-22/WH-H-4 WH-H-4 WH-H-3/WH-H-4 WH-H-3 WH-H-2 WH-H-1 WH-H-1/WH-H-2 Document Path: S:\GIS\Projects\12xxxx\D120902_BellinghamHabitatRestoration\Mxd\Nearshore\Shoreform_Types.mxd (MJL, 2/21/2013) Shoreform Type Artificial Barrier Estuary Barrier Lagoon Bluff-backed Beach Pocket Beach Plunging Rocky Rocky Platform Study Area Water Bodies Other Water Bodies Streams Labels indicate drift cell name based on CGS drift cell mapping (2005) RP-89 ART-91 RP-96 RP-92 PL-95 PB-93 RP-94 WH-4-22-NAD RP-100 SOURCE: PSNERP, 2011; CGS, 2012; Bellingham, 2012; ESA, 2012; DNR, Bellingham Habitat Restoration Master Plan Figure 6 Shoreform Types Miles