RIPPLE Case Study Rock Creek Oregon Coho Enhancement

Transcription

1 Juvenile coho salmon in East Fork Rock Creek RIPPLE Case Study Rock Creek Oregon Coho Enhancement Prepared by Stillwater Sciences 850 G Street Suite K Arcata, CA, Contacts: Frank Ligon ext. 213 frank@stillwatersci.com Jody B. Lando jblando@stillwatersci.com

2 OVERVIEW RIPPLE is a digital terrain based model that predicts the distribution of fish habitat conditions throughout a watershed and simulates salmon population dynamics. It is a powerful tool for evaluating the effectiveness of restoration and recovery planning strategies. Developed in collaboration between Stillwater Sciences and UC Berkeley, RIPPLE characterizes the geomorphic and ecological processes that create and maintain freshwater salmon habitat. It is publicly available from the National Center for Earth Systems Dynamics CED website The open source nature of RIPPLE allows the scientific community the opportunity to evaluate its assumptions and improve its value. One of the guiding principles of RIPPLE is the assumption that physical processes and the resulting environment specifically topography, geology, climate, drainage area, channel gradient, channel longitudinal profile are essentially time invariant compared with ecosystems and the animal and plant populations supported by these ecosystems. This assumption enables us to construct a model that establishes a physical template composed of such information as topographic data, channel networks, and geology. RIPPLE thus uses geomorphic characteristics and physical habitat characteristics, combined with density and suitability criteria by species and life stage, to predict reach specific historical, current, and potential future salmon habitat. RIPPLE then employs a multi stage, stock production model to predict long term average abundance for each life stage. The model can also produce a single number, such as ʺlong term average escapementʺ for the purposes of scenario comparisons or hypothesis testing. Operationally, these elements are evaluated through three sub models that are run sequentially: (1) a physical model ( GEO ), executed through ESRI s ArcGIS Desktop, (2) a habitat carrying capacity model ( HAB ), and (3) a population dynamics model ( POP ). RIPPLE is a flexible, scientifically rigorous tool designed for salmon conservation and management. It can be used with limited data and still produce credible preliminary results to guide further hypothesis testing; it can be customized with watershed specific data to generate progressively more refined results; and it can be used to assess the value of collecting additional field data. INTRODUCTION This document provides a concrete example of how RIPPLE has been used, displaying one of the analyses conducted during the North Umpqua Hydroelectric Project relicensing and license implementation. An important application involved evaluating the potential to restore coho populations in Rock Creek, a major tributary to the North Umpqua River. RIPPLE is ideal for this application, because it can be run to predict population size for historical, current, or future conditions. In the Rock Creek application, RIPPLE was first run for current conditions, and then for potential future restored conditions. We note that this report is a case study, rather than a comprehensive user manual or model documentation. Questions arising from this example should be addressed to the points of contact on the cover page. 2

3 Figure 1 shows intrinsic potential (IP) for coho salmon in the North Umpqua River Basin generated by the Coastal Landscape Analysis and Modeling Study (CLAMS). IP is based on mean annual discharge, channel gradient, and valley width (see Burnett et. al 2007), and is a screening tool for rapidly evaluating channel segments or whole watersheds for the quality of their historic coho salmon habitat. Rock Creek contains relatively long stream sections with high IP, illustrating why this stream was recognized as a natural candidate for coho restoration. Figure 1. Intrinsic potential for coho salmon in the North Umpqua Basin. 3

4 CHANNEL NETWORK Creating a GIS layer of the channel network, broken into channel reaches that are each attributed with their local slope and contributing drainage area, is the starting point for using RIPPLE. Creating this layer must be done within ESRI s ArcMAP and precedes application of the model components. Below is the channel network for Rock Creek showing slope and drainage area (Figures 2 and 3). Notice the extensive low gradient (<2 %) habitat in Rock Creek, which is important for coho salmon. Figure 2. Slope in the Rock Creek basin. 4

5 Figure 3. Drainage area in the Rock Creek basin. GEO GEO, the first of RIPPLE S three sub models, generates the physical template of the watershed, including such attributes as bankfull width and depth and median grain size of the stream bed. Its main page is shown in Figure 4. 5

6 Figure 4. GEO main page, showing options to input the ArcGIS generated river network ( Load ); to view and, if desired, modify the GEO parameters that determine the predicted sizes of channel features from the GIS input; and to run the GEO sub model. To run GEO, field data on the hydraulic geometry of river channels from the region of interest were required. Figure 5 shows an example of such hydraulic geometry data collected by Stillwater Sciences in the Western Cascades geomorphic landscape unit in the North Umpqua watershed. Figure 6 shows the GEO data input page with the measured parameters. Hydraulic geometry for other selected geomorphic regions that Stillwater Sciences has previously applied to RIPPLE can be selected from the pull down menu at the top of the GEO input page. Alternatively, the user can input entirely new values. 6

7 Figure 5. Field measured relationships between bankfull channel depth, bankfull channel width, and drainage area in the Western Cascades region of the North Umpqua Basin (Stillwater Sciences 1997 unpubl. data). Figure 6. GEO input page, showing the equations used to describe channel ( bankfull ) parameters and wetted flow dimensions, based on data collected in the Western Cascades region of the North Umpqua Basin. 7

8 The GEO model output permits examination of various geomorphic parameters at the scale of the individual reach segments defined during the initial GIS set up of the channel network. For example, predicted median grain size (one of the outputs of GEO) is shown for Rock Creek in Figure 7. Figure 7. GEO model output showing predicted median grain size. 8

9 HAB The GEO output, specifically the predictions of channel dimensions and grain size at different discharges, is used in the HAB sub model to estimate life stage specific carrying capacities. Figure 8 shows the HAB main page (left) and the HAB parameters page (right). Figure 8. HAB main page (left) and RIPPLE HAB Parameters screen (right) provides access to input screens for habitat composition; usability and density; and width, depth, and grain size thresholds (shown circled). The first step in applying HAB is to determine the stream channel slope breaks that separate reaches with different morphology and, consequently, differing habitat quality and quantity. This is accessed from the HAB Parameters screen, using the Habitat Composition button. Figure 9 demonstrates the importance of slope in determining channel type, showing a 0 1% channel and a 1 2% channel in Rock Creek, and the distinct habitat types that are created. The appropriate slope breaks to use can vary depending on the geomorphic landscape unit (e.g., Western Cascades versus High Cascades). 9

10 Figure 9. Examples of 0 1% (top) and 1 2% (bottom) channel slope in Rock Creek. 10

11 The fish bearing streams within the channel network are categorized into one of four habitat types whose relative proportions are presumed to stratify on the basis of slope classes (Montgomery and Buffington, 1997). For each slope category used by salmon, the proportions of different habitat types (pools, riffles, runs, and cascades) must be assigned. For an accurate characterization of current conditions, channel surveys are required for representative portions of the channel network. Oregon Department of Fish and Wildlife (ODFW) has completed such a habitat survey data for Rock Creek, which is what we used for current conditions (Figure 10). Coho do not use channels steeper than 4% during any life stage, and so entries for this class are unnecessary. Figure 10. Habitat composition input screen showing habitat type frequency values used for current conditions in Rock Creek. Once the relationships between slope and the relative proportion of habitat types have been established, each combination of slope and habitat type category (e.g., 1 2 percent/riffle) must be assigned a density and usability for each coho salmon life stage. Density is the maximum number of individuals per square meter for a given life stage in the area of the habitat unit that is actually used by that life stage (e.g., spawner). Usability is the percent of the total habitat unit that is, on average, usable for a given life stage. If biological surveys report fish numbers for the entire habitat unit, rather than just the portion being used, then the whole habitat unit is treated as usable. Density values for juvenile coho in the summer (summer 0) and winter (winter 0) were derived from snorkel surveys and electrofishing conducted in East Fork Rock Creek in (Stillwater Sciences 2006) (Figure 11). A useable fraction of 1 was applied because fish surveys were conducted at the habitat unit scale. Based on previous surveys, it was assumed that coho salmon do not rear in the 4 8% and 8 20% slope classes. 11

12 Figure 11. Summer and winter density values for juvenile coho salmon were determined using direct observation snorkel surveys (left) and electrofishing surveys (right). Figure 12 shows the Habitat Usability input screen, accessed from the Habitat Parameter page, for winter juvenile coho salmon densities and habitat usability based on data collected in East Fork Rock Creek. Note that fish density data for 0 1% channels were unavailable, and so densities from 1 2% channels were applied to these lower gradient channels. Multiple runs of the model, with different values inserted in the 0 1% range, could show whether or not this assumption was critical to final results and thus whether more complete field data were appropriate. Figure 12. Habitat input screen, showing the parameters for habitat density and usable fraction ( usability f ) for age 0+ coho salmon winter rearing. 12

13 The HAB Parameters screen also allows the user to set life stage specific thresholds (e.g., substrate size, channel width, and channel depth) to exclude reaches with unusable habitat (see Figure 8). HAB will then calculate reach specific carrying capacities for all reaches not excluded by life stagespecific thresholds. After all parameters have been established, the model can produce output such as that displayed in Figure 13, which shows reach specific carrying capacity for summer rearing juvenile coho salmon in numbers of fish per meter of stream length. Figure 13. Reach specific carrying capacity for summer rearing juvenile coho salmon expressed as numbers/linear meter (only the portion of the network that contains coho salmon is shown). These results incorporate not only the presumed distribution of habitat units but also systematic changes in channel geometry. For example, carrying capacities typically increase downstream, because GEO calculates the total area of habitat units as a function of drainage area. Pools in downstream reaches are wider, for example, and therefore can accommodate more fish. RIPPLE can also incorporate other factors that limit salmon utilization of habitat units. As one such example, elevated summer water temperatures due to reduced shading by riparian forests can preclude coho rearing (Welsh et al. 2001). BasinTemp, a model that that predicts maximum weekly average water temperatures (MWAT) for stream channel networks (Allen 2008), was applied to Rock 13

14 Creek under current riparian forest conditions. Reaches with MWAT 17 C were considered unsuitable for coho salmon summer rearing (Figure 14). Therefore, in these warm reaches, summer juvenile carrying capacity was changed to zero (operationally, this is accomplished by assigning those reaches a summer baseflow width of zero in the GEO output). Figure 14. Suitable water temperatures for juvenile coho salmon summer rearing under current conditions. Suitable reaches for coho salmon are shown in blue and unsuitable reaches are shown in red. 14

15 POP The POP sub model used the reach specific carrying capacities generated by HAB to predict the population size of the watershed. The model simulates mature adults migrating to stream reaches with available spawning habitat. Once the spawning carrying capacity of a reach is filled, then subsequent spawners can look for available habitat in other reaches. Likewise, when fry emerge and fill a reach s carrying capacity for summer juveniles, excess fry will look for available habitat in other reaches. Similarly, juveniles in excess of a reach s winter carrying capacity will search for unsaturated habitat in other reaches. Figure 15 shows the POP main screen and input screen. The POP input screen has parameters for proportion of females, fecundity, and life stage specific density independent survivals. It opens with default values, but the user can modify any of the population parameters. For example, embryo survival ( embryo background ) was estimated to be 0.50 (50%) based on measurements of spawning gravel permeability in Rock Creek (Figure 16). Figure 15. POP main screen (left) and POP parameter input screen (right); the latter is accessed via the View/Modify button on the main screen. 15

16 Survival to to emergence (%) (%) Reach Figure 16. Estimated embryo survival by reach in Rock Creek based on measured permeabilities of spawning gravels. Permeabilities were converted to % survival values based on the work of McCuddin (1977) and Tagart (1976). 16

17 The density independent mortalities and carrying capacities from HAB are used to produce life statespecific stock production curves. The form of the stock production curve is user selected via a pulldown menu in the POP parameter input screen (Figure 17). Figure 17. Pull down menu (circled) that allows user selection of the desired stock production model in the RIPPLE POP interface. The life stage specific stock production curves are used to estimate the equilibrium population size of each life stage (Figure 18). V* Permeability LWD Fry Adults Parr Fry Smolts Parr Fry Smolts Spawners Year Smolts Parr Figure 18. Conceptual diagram of how individual life stage stock production curves are linked to provide a population dynamics model. Adult spawners become fry, fry become parr, parr become smolts, and smolts return to begin a new year of spawners. Over a series of years, tracking the number of smolts will indicate if the model is predicting a stable, increasing, or declining population. 17

18 Figure 19 provides an example of POP output maps showing the distribution and abundance of summer and smolt ready juveniles. Figure 19. RIPPLE output maps showing predicted distribution and number of summer juveniles (top) and smolt ready juveniles (bottom). 18

19 Currently, much of the channel network of Rock Creek does not have suitable habitat for summer juveniles (top map of Figure 19, reaches in red) due to high water temperatures, but it does support smolt ready juveniles (bottom map). This occurs because juveniles in cool summertime reaches subsequently exceeded the winter carrying capacity of those reaches, and so they migrated downstream to find rearing habitat that became available during the winter. Figure 20 shows the POP main screen after running the submodel, illustrating predicted long term equilibrium population sizes of the different life stages. In this example, the model predicted a spawning escapement of 467, which falls within the range of wild adult coho salmon estimated by recent ODFW spawning surveys in Rock Creek. Figure 20. POP main page after running the submodel, showing predicted equilibrium population sizes for each life stage for current conditions. 19

20 RESTORATION SCENARIOS Elevated summer temperatures due to riparian forest management have long been identified as a problem in Rock Creek (Stillwater Sciences 1998), and have the potential to greatly reduce coho salmon summer rearing habitat (Figure 14). To evaluate the impact of cooler water temperatures on the coho population, Stillwater Sciences developed a number of different restoration scenarios involving riparian forest recovery. Contrary to expectations, however, RIPPLE did not predict any increase in the number of smolts or returning spawners under greater riparian shading when compared to current conditions. This initially surprising result is due to the fact that winter (not summer) carrying capacity is limiting, and this parameter remains unchanged under both current and riparian restoration scenarios. Under current conditions, the predicted loss of mainstem rearing in the summer due to temperature limitations is not enough to lower total summer carrying capacity (about 16,000) sufficiently to make it more limiting than winter carrying capacity (about 9,500). This analysis illustrates the importance of including the movement of individuals from reach to reach in RIPPLE. Because migration can occur, juveniles from reaches suitable for summer rearing (blue in Figure 14) are able to move downstream to occupy available winter habitat in reaches that were too hot for juvenile coho salmon in the summer (red in Figure 14). If the model had not allowed juvenile fish to migrate, it would have effectively reduced available winter habitat as well as summer habitat, significantly lowering the estimate of the current population size and erroneously showing population scale benefits of stream cooling. These results indicate that efforts to improve coho populations in Rock Creek will be most effective if directed at improving winter survival rather than lowering summer water temperatures. As a result, Stillwater Sciences is conducting a multi year field study to determine the most cost effective way to increase winter survival in Rock Creek through wood and boulder additions. Figure 21 presents the results of one of the three year pre project monitoring, which shows a marked decline in coho numbers between summer and fall surveys and those carried out after the onset of winter storms in Additional years of sampling show the same pattern (Stillwater Sciences 2006). 20

21 ,874 3 Abundance Stage Height (ft) Jun-03 9-Jul-03 9-Aug-03 9-Sep Oct Nov Dec Jan Feb Mar-04 0 Figure 21. Abundance estimates resulting from direct observation snorkel and electrofishing surveys conducted in East Fork Rock Creek in summer, fall, winter, and spring, overlaid on stage height. Red segments of the stage height line reflect survey periods. After three years of pre project monitoring and simulated conditions from RIPPLE model output, 126 pieces of large wood were experimentally added to increase the number of pools, the complexity of existing pools, and the access to side channels. Figure 22 illustrates one of the enhancement sites. 21

22 Figure 22 Large wood placements enhance coho habitat capacity in Rock Creek Design plans for the placement of wood pieces were facilitated with the use of Low Elevation Aerial Photography (LEAP) (Figures 23 25). LEAP is a cost-effective tool for obtaining high resolution, digital aerial photographs, ideal for mapping small reaches or areas with abundant canopy cover. Figure 23. Conceptual representation of additional large woody debris (LWD) (red) to create new pools in riffle habitat. The digital base map was obtained using LEAP. 22

23 Figure 24. Conceptual representation of additional LWD (red) to increase complexity of existing pools in East Fork Rock Creek. The digital base map was obtained using LEAP. Figure 25. Conceptual representation of additional LWD (red) to promote side channel development and access in East Fork Rock Creek. Note: the log jam to the far right was intended to create local aggradation to re water the side channel at baseflow. 23

24 In total, Stillwater Sciences identified appropriately 11 miles of stream as good candidates for wood additions (Figure 26). Figure 26. Suitable wood enhancement reaches in the Rock Creek basin highlighted in red. 24

25 The addition of LWD is modeled in RIPPLE by increasing both the proportion of pools and winter density of juveniles. We estimated the change in proportion of pools by measuring the change in pool frequency in our study reach; it could also be estimated by reference to the published literature on reference conditions in forested stream, or from the plans of proposed LWD additions. The change in winter density of juveniles was estimated by measured winter densities in high quality pools of the type intended to be created with the LWD additions. With these changes, RIPPLE can predict the distribution and number of smolt ready juveniles after enhancements (Figure 27). The model predicts that improving winter survival would nearly double the numbers of spawners, from approximately 450 to 875 (Figure 28). ODFW is currently conducting large scale wood additions in Rock Creek (ODFW Roseburg, Oregon, pers. comm.). Figure 27. RIPPLE output map showing distribution and number of smolt ready juveniles following proposed LWD enhancements. 25

26 Figure 28. POP main page showing predicted equilibrium population sizes for each life stage after the addition of LWD. The model further predicts that after implementation of all the LWD enhancements, the limiting condition will be summer rearing habitat, because summer carrying capacity is predicted to increased modestly to approximately 17,700 while winter carrying capacity is predicted to increase dramatically to approximately 19,400. Therefore, even though decreasing summer water temperatures would not improve coho salmon production by itself, temperature reduction in conjunction with large improvements in winter survival would be beneficial. In summary, the use of RIPPLE in this instance served to illuminate previous misconceptions about temperature effects and population dynamics on Rock Creek. The model inputs, functional relationships and results provide a quantitative and transparent prediction of habitat restoration effectiveness. 26

27 LITERATURE CITED Allen, D. M Development and application of a process based basin scale stream temperature model. Doctoral dissertation. University of California, Berkeley. Montgomery, D. R., and J. M. Buffington, Channel reach morphology in mountain drainage basins, Geol. Soc. Am. Bull., 109, , Burnett, K. M., G. H. Reeves, D. J. Miller, S. Clarke, K. Vance Borland, and K. Christiansen Distribution of salmon habitat potential relative to landscape characteristics and implications for conservation. Ecological Applications 17: McCuddin, M. E Survival of salmon and trout embryos and fry in gravel sand mixtures. Masterʹs thesis. University of Idaho, Moscow. Montgomery, D. R., and J. M. Buffington Channel reach morphology in mountain drainage basins. Geological Society of America Bulletin 109: Stillwater Sciences The North Umpqua cooperative watershed analysis synthesis report. Prepared by Stillwater Sciences, Berkeley, California for PacifiCorp, Portland, Oregon. Stillwater Sciences Summary of the first three years of effectiveness monitoring for the East Fork Rock Creek habitat enhancement study. Prepared by Stillwater Sciences, Arcata, California for PacifiCorp, Portland, Oregon. Tagart, J. V The survival from egg deposition to emergence of coho salmon in the Clearwater River, Jefferson County, Washington. Masterʹs thesis. University of Washington, Seattle. Welsh, H. H., Jr., G. R. Hodgson, B. C. Harvey, and M. E. Roche Distribution of juvenile coho salmon in relation to water temperatures in tributaries of the Mattole River, California. North American Journal of Fisheries Management 21: