South Fork Skagit Restoration Monitoring to Develop and Test Restoration Design Tools
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South Fork Skagit Restoration Monitoring to Develop and Test Restoration Design Tools Nearshore Database Project Number: 07-1107 Proponent Contact Info: Steve Hinton Skagit River System Cooperative Director of Restoration [email protected] (360) 466-7243 Site Access Contact Info: W. Gregory Hood Skagit River System Cooperative Senior Restoration Ecologist [email protected] (360) 466-7282 Site Location: South Fork Skagit River Delta, including Deepwater Slough restoration site Milltown Island restoration site Wiley Slough restoration site Fisher Slough restoration site Reference tidal marshes All sites are located on the Skagit River, downstream from Conway, WA. Latitude 48.315˚ Longitude -122.365˚ Start Date: January 2008 End Date: December 2009 Key Personnel: W. Gregory Hood, Phd, Senior Restoration Ecologist Project manager and Scientist Will plan and implement the monitoring program, direct fieldwork, analyze data, and report and disseminate results. Problem Statement Restoration monitoring is sometimes perceived as not having delivered value to management agencies. Consequently, agencies are reluctant to fund monitoring, preferring instead to fund only restoration. The criticism of monitoring is valid and the causes of its failure are multiple, among them: [a] funding for monitoring is often inconsistent or unreliable (which leads to inconsistent and unreliable monitoring, and a catch-22 situation); [b] monitoring is often mere comparison of reference and restoration sites rather than hypothesis testing, [c] monitoring often requires long-term observation (patience) incompatible with short-term performance requirements of many agencies; and [d] monitoring often does not deliver useful information on which agencies can act. In support of Chinook salmon recovery, we propose to deliver value through a monitoring project that develops and tests restoration design and planning tools that could be used throughout Puget Sound. The tools we will develop and test are [1] a predictive model of tidal marsh vegetation that uses marsh elevation (tidal flooding frequency and duration), soil salinity, and sediment grain size to generate probabilistic predictions of vegetation occurrence; and [2] a predictive model of dendritic tidal channel geometry. We will also acquire data necessary to develop [3] a conceptual model of distributary channel dynamics. In addition to quantitatively predicting the tidal marsh vegetation that would develop following dike breaching or removal, the vegetation model would also allow modelling of climate change scenarios (sea-level rise and changes in salinity and sediment dynamics) to predict restoration sustainability (Hood 2005). The predictive dendritic channel geometry model can be used to predict the amount of juvenile Chinook salmon habitat and abundance resulting from marsh restoration. The distributary dynamics model will be applicable to distributary restoration, e.g., across Fir Island. Existing Information/Previous Work [1] Vegetation model. The first step in developing a predictive model for tidal marsh vegetation has already been accomplished. Survey-grade GPS (2-cm horizontal and vertical accuracy) sampling of the South Fork Skagit tidal marshes has generated a data set of over 600 data points that pair observed elevation and vegetation (Fig. 1). Figure 1. Box-plot of the elevation distributions of common marsh vegetation in the South Fork Skagit tidal marshes (blue), compared to vegetation in the Deepwater Slough restoration site (red) prior to dike removal (the site had poorly drained, fallow fields prior to dike removal). Sample sizes are in parentheses. Shaded and unshaded portions of the boxes represent the 2nd and 3rd quartiles around the median, vertical lines represent two standard deviations from the mean, and stars are outliers. 1 These data can be reorganized to generate probability functions for species occurrence at a given elevation range (Fig. 2), which can then be used to recode lidar data to generate probabilistic vegetation predictions (Fig. 3). This preliminary model has been tested by Figure 2 (left) Vegetation species occurrence probabilities relative to marsh elevation. Figure 3 (right) Probabilities of encountering Carex lyngbyei (sedge) [top], Typha angustifolia (cattail) [middle], and Myrica gale (sweetgale) [bottom] on the Fisher Slough project site following proposed tidal restoration. Warm colors are high probabilities, cool colors are low probabilities. White areas are either off-site or have probability of zero. monitoring vegetation changes in the Deepwater Slough restoration site (restored in summer of 2000) and performing an adaptive management experiment (2003-2007). The results to date are encouraging and suggest this modelling approach has a strong likelihood of successfully predicting marsh vegetation following tidal regime restoration. [2] Dendritic tidal channel model. Planform dendritic tidal channel geometry has been modelled for the Skagit marshes by scaling tidal channel metrics with marsh area. Details are described in Hood (2007), and the results indicate significant utility in planning optimal marsh restoration designs. For example, to maximize tidal channel surface area and length it is better to restore one large continuous parcel than several 2 smaller separate parcels. The results were also used to infer anthropogenic impacts (river distributary obstruction) to a significant portion of the Skagit marshes. [3] Distributary channel conceptual model. Analysis of the recent development of a river distributary in the North Fork Skagit tidal marshes indicates that relative distributary gradient is a reasonable predictor of distributary size (Hood 2004; Hood, unpublished data). Similar analysis of simple parts of the South Fork distributary system shows promise as well, but the current approach does not yet account for complex anastomosing patterns that are also present in the South Fork delta. Data Gaps [1] Vegetation model. The current vegetation model describes only oligohaline tidal marshes, and thus is constrained to a narrow range of conditions. To make the model more general requires inclusion of additional environmental influences on tidal marsh vegetation distribution, particularly soil salinity and grain size. This will allow prediction for a larger variety of marshes and for likely climate change influences. [2] Dendritic tidal channel model. The current model is based only on planform geometry quantifiable from high-resolution orthophotos. A more complete and generalizable model will require vertical information as well, i.e., surveys of channel cross-sections to acquire depth and cross-sectional area. Vertical information will also allow better linkage of channel geometry to fish use by estimating channel capacity (accessibility to fish during the tidal cycle). [3] Distributary conceptual model. This model also lacks vertical information, i.e., channel cross-section data. Proposed Work Data Acquisition for Model Parameterization [1] Vegetation model. We will collect paired elevation-vegetation data in Skagit Delta tidal marshes with a variety of soil salinities, similar to that already collected in the oligohaline portion of the South Fork Skagit delta [0-8 ppt]. Collection sites will include [a] Skagit bay-fringe marshes (10-18 ppt) between the North and South Fork tidal marshes (where historical distributaries are now blocked by dikes); [b] marshes in the southern-most portion of the South Fork delta [8-12 ppt]; and marshes fringing [c] Port Susan Bay [10-18 ppt]; [d] the Swinomish Channel (20-25 ppt); [e] Padilla Bay (25-30 ppt); and [f] Samish Bay [20-25 ppt]. Elevations will be measured relative to survey benchmarks and known tidal datums with either survey-grade GPS or laser levels. We anticipate acquiring 1500 to 2000 data points. We will measure grain size in marshes associated with various geomorphic characteristics (proximity to river distributaries, areas of dynamic historical change, and wave fetch). GIS analysis of current and historical air photos will be used to determine sampling locations. Vegetation and elevation will be simultaneously sampled with sediment grain size. Preliminary field observations indicate that sediment types (sandy vs silty vs clay/mud) can occur in distinct patches and zones in the Skagit system with distinct effects on tidal marsh vegetation. [2] Dendritic tidal channel model. Channel cross-sections will be surveyed with either survey-grade GPS or laser levels relative to known bench marks and tidal datums. Cross-sections will be surveyed at channel outlets, at ¼ of the channel length inland from 3 the outlet, and at the channel midpoint. Cross-sections will include elevation of each bank for a distance of at least 20 m to characterize channel berms and marsh elevation. We anticipate surveying at least 100 tidal channels (300 cross-sections) spanning a large range of sizes and broadly distributed in the Skagit marshes. All data will be spatially identifiable and entered into a GIS. [3] Distributary conceptual model. Channel cross-sections will be surveyed for all South Fork Skagit River distributaries above and below distributary junctions and divergences. To support data collection and model testing for all three models we propose acquisition of new high-resolution (15-cm pixel) infra-red orthophotos of the South Fork Skagit marshes in either 2008 or 2009, depending on when the Wiley Slough and Fisher Slough restoration projects are implemented (implementation for Wiley Slough is expected