Food web interactions in Kachess and Keechelus

Food web interactions in Kachess and Keechelus Reservoirs, Washington: implications for threatened adfluvial bull trout and management of water storage

Final Report

Adam G. Hansena,b, Matt Polacekc, Kristin A. Connellya, Jennifer R. Gardnera, and David A. Beauchampa,d aWashington

Cooperative Fish and Wildlife Research Unit, School of Aquatic and Fishery Sciences, University of Washington, Box: 355020 Seattle, WA 98195-5020 bColorado

Parks and Wildlife, 317 West Prospect Road, Fort Collins, Colorado 80526

cWashington

State Department of Fish and Wildlife, Large Lakes Research Team, 317 ½ North Pearl Street, Suite 7, Ellensburg, Washington 98926

dU.S.

Geological Survey

January 2017

Prepared for: Washington State Department of Ecology: Contract No. C1600072 IAA No. C1600072 and UW contract No. A108563.

Food web structure of Kachess and Keechelus Reservoirs

2017

EXECUTIVE SUMMARY  Projects that increase the active water storage capacity of Kachess and Keechelus Reservoirs, two of five primary reservoirs in the Yakima River Basin, are being proposed to help mediate the impacts of drought for irrigators in the basin. These include the Keechelus-to-Kachess Conveyance and the Kachess Drought Relief Pumping Plant (KDRPP).

 Both Kachess and Keechelus contain threatened populations of adfluvial bull trout. Here, we evaluate the contemporary food web structure of each reservoir, quantify key predator-prey interactions, and examine how the timing and magnitude of thermal stratification and reservoir elevation affect trophic interactions to provide a baseline for evaluating the potential impacts of these proposed water projects on bull trout.

 Based on stable isotope analysis, Keechelus is supported more by pelagic production than Kachess. This is likely a result of the earlier and more extensive draw-down during the growing season. Consequently, more burden is placed on pelagic production in Keechelus. This suggests that more frequent and extensive draw-down of Kachess under the KDRPP could also erode littoral production, placing more burden on the pelagic energy pathways important for bull trout and their prey.

 Adult bull trout are top predators and highly piscivorous. Kokanee and other coldwater pelagically oriented fish (e.g., pygmy whitefish, redside shiners) are key prey, which rely on Daphnia when available.

 Adult burbot and northern pikeminnow are piscivorous and could impact populations of prey fishes that are important forage for bull trout, or consume juvenile bull trout, particularly if alternative benthic prey resources shared less by bull trout become scarce. Under contemporary conditions, northern pikeminnow rely mostly on benthically oriented fish and invertebrates, whereas burbot appear to eat a mix of benthic and pelagic prey. Both piscivores also consume significantly greater biomass of kokanee and other salmonids than bull trout, so hydrologic changes that shift their diets toward higher reliance on pelagic prey would likely increase their predation on kokanee and other pelagic prey fishes.

 The abundance of bull trout in Kachess and Keechelus is low. Stable isotope samples from juvenile and sub-adult bull trout, and data on the spatial distribution of bull trout, size- and age-structure, and size/age at immigration into each reservoir (all currently lacking) would inform the potential impact of cannibalism, and the vulnerability of juvenile bull trout to predation by burbot or northern pikeminnow.

 Thermal stratification begins in late June, peaks in July, and persists through October. Epilimnetic temperatures during peak thermal stratification approach 22°C, too warm for adult bull trout. Based on hydroacoustics, all age-classes of kokanee generally

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avoid the epilimnion during peak thermal stratification, remaining within or below the thermocline at all times of day.

 The density of Daphnia peaks in June (Kachess) or July (Keechelus). Daphnia are concentrated in the epilimnion during the growing season in Keechelus, but are not accessible to kokanee during peak thermal stratification. More Daphnia are available during spring (April-June) in Kachess than Keechelus. Unlike Keechelus, the density of Daphnia in Kachess within the metalimnion and hypolimnion is relatively high compared to the epilimnion. Overall, Daphnia densities are relatively low in both reservoirs compared to nearby Cle Elum Reservoir.

 Based on bioenergetics modeling simulations, kokanee in Kachess and Keechelus experience low consumption and growth. This is caused by a combination of cold thermal experience (exclusion from the epilimnion during peak thermal stratification and behavioral thermoregulation/predator avoidance), and low Daphnia densities (limiting the prey encounter and feeding rate of kokanee). Increasing the number of kokanee fry stocked into Kachess and Keechelus during spring/early summer beyond current levels could lead to a significant feeding and growth bottleneck during midsummer. The consumption demand for zooplankton was many-fold higher for ages 12 and 2-3 kokanee than the demand by age-0 kokanee.

 The potential competition between kokanee and the other major planktivores is likely minimized due to thermal segregation during the growing season. Additional consumption demand for Daphnia by redside shiners during the summer likely has minimal impact on the food available to kokanee, because redside shiners feed in the warmer epi-pelagic zone while it is inaccessible to kokanee during peak stratification.

 Feeding rates of bull trout estimated from the bioenergetics model suggested that bull trout are not limited by foraging opportunities in Kachess under contemporary conditions, and our hydroacoustics-based estimate of the pelagic forage base in Kachess during August could support a higher population size of adult bull trout, or any expected increase in consumption during periods of drought or increased reservoir draw-down from the current population of bull trout.

 Annual stockings of kokanee are an important source of prey for all piscivores in Kachess and should continue. Northern pikeminnow and burbot collectively could eat 11-fold more kokanee biomass than bull trout each year due to their much higher abundance. These two piscivores are also supported by considerable fractions of alternative benthic-littoral and nearshore epi-pelagic fishes and benthic invertebrates. Consequently, water operations that limit the productivity of these alternative prey species would likely increase consumption demand on and potential competition for pelagic prey fish resources shared by adult bull trout, and reduce the suite of potential feeding opportunities available for smaller, younger age-classes of bull trout entering the reservoir.

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 Simulating the effect of draw-down by the KDRPP on pelagic prey fish density empirically measured from hydroacoustics in Kachess indicates that greater drawdown should not concentrate predators with prey to a point that would lead to unsustainable predator-prey interactions.

 At the current proposed elevation of the pump intake for the KDRPP (2,112 ft), water managers will not be able to utilize the full 200,000 ac-ft of what is currently dead storage without pumping water directly from the thermocline and epilimnion. This has important implications for reservoir productivity, thermal structure, and food web interactions.

 Our food web analysis of Kachess spanned three years, which included a drought year and two average water years. From a feeding and growth perspective, data and modeling simulations suggested that the reservoir has the capacity to support a larger population of bull trout under current management, yet the abundance of bull trout remains low. A number of uncertainties related to the severity of potential competition among bull trout, burbot, and northern pikeminnow in the reservoir, the growth and survival of juvenile bull trout in the reservoir, suitability of spawning and juvenile rearing habitat, access to spawning tributaries, or combination of these factors still remain. Because of these additional uncertainties and potential limiting factors, the importance of reservoir productivity and maintaining a diverse suite of feeding opportunities for bull trout in Kachess should not be overlooked when developing water management regimes involving the KDRPP.

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PROJECT BACKGROUND Scope and purpose The U.S. Bureau of Reclamation (USBOR) and the Washington State Department of Ecology (WSDOE), through the Office of Columbia River, worked with the Yakima River Basin Water Enhancement Workgroup to develop an integrated water resource management plan designed to balance irrigation, recreation, and conservation needs in the Yakima River Basin, Washington (USBOR and WSDOE 2012). To meet these objectives, the integrated plan proposed numerous alterations to the structure and operation of existing reservoirs and dams within the basin. Two individual projects identified in the integrated plan are currently undergoing project-level environmental review. These include: (1) the Kachess Drought Relief Pumping Plant (KDRPP), and (2) the Keechelus-to-Kachess Conveyance (KKC). How these proposed water management alterations might impact food web structure and populations of sensitive species (i.e., bull trout Salvelinus confluentus) within these reservoirs remains a key uncertainty for the environmental review process. However, before potential impacts can be identified and assessed, a contemporary understanding of the food web structure of these reservoirs is needed. Information on the physical and biological characteristics of Kachess and Keechelus Reservoirs is most limited. The purpose of this study was to synthesize existing information with new data to fill key knowledge gaps regarding the physical environment, food web structure, and predator–prey interactions in Kachess and Keechelus Reservoirs as they relate to supporting the production of bull trout. This information will (1) help identify important trophic pathways (i.e., pelagic vs. benthic production) supporting adult bull trout in these reservoirs, (2) provide key baseline data needed to consider the suitability of these reservoirs as potential rearing habitats and migratory corridors for reintroduced anadromous salmonids, and (3) aid in the projectlevel environmental review for KDRPP and KKC.

SITE DESCRIPTIONS Kachess and Keechelus Reservoirs Kachess and Keechelus were natural lakes in the upper Yakima River Basin until earth-fill dams were constructed at the outlet of each lake in 1912 and 1917, respectively. Both reservoirs are oligotrophic with high transparency (Mongillo and Faulconer 1982; Hiebert 1999). Kachess is larger than Keechelus Reservoir in both surface area and storage capacity at full pool (Table 1). Neither dam allows passage by anadromous salmonids. Consequently, sockeye salmon Oncorhynchus nerka, which require natural lakes as juveniles for rearing, were extirpated from each system. Other anadromous salmonids (spring Chinook salmon O. tshawytscha, coho salmon O. kisutch, and steelhead O. mykiss) were restricted to habitat below the storage reservoirs. Each 5



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reservoir contains kokanee salmon, resident rainbow trout, and remnant populations of adfluvial bull trout that spawn primarily in Box Canyon Creek and the Kachess River in Kachess Reservoir, and Gold Creek in Keechelus Reservoir (James 2002). Fish passage would open approximately 2.4 miles of tributary stream habitat for anadromous salmonids in Kachess, and 13.8 miles in Keechelus Reservoir. However, low base flows in tributary streams, combined with reservoir draw-downs, can create additional passage issues for spawning fish in both reservoirs during some years (WSDOE 2009). In terms of organisms of direct relevance to bull trout and kokanee, the reservoir food webs are composed of benthic and pelagic fishes, crustacean macrozooplankton, and benthic invertebrates. The fish communities in Kachess and Keechelus Reservoirs include bull trout Salvelinus confluentus, kokanee O. nerka, rainbow trout O. mykiss, cutthroat trout O. clarki, pygmy whitefish Prosopium coulterii, mountain whitefish Prosopium williamsoni, burbot Lota lota, northern pikeminnow Ptychocheilus oregonensis, redside shiner Richardsonius balteatus, speckled dace Rhinichthys osculus, sculpin Cottus sp., largescale suckers Catostomus macrocheilus, The primary crustacean zooplankton include Daphnia, Bosmina, Holopedium, and calanoid copepods. The benthic invertebrate forage base is composed of signal crayfish Pacifastacus leniusculus, aquatic insects, and an assortment of other benthic invertebrates. Table 1. Morphometric characteristics of Kachess and Keechelus Reservoirs.

Parameter

Kachess

Surface area (ha) Flushing rate (days) Max. depth (ft) Mean depth (ft) Surface elevation at full pool (ft) Elevation of outlet (ft) Total capacity (ac-ft) Drainage area (ha) Average annual runoff (ac-ft)

a

1,837 227b 430c 2,262a 2,192a 239,000a 16,472c 213,398c

Keechelus 1,039a 68b 310c 96c 2,517a 2,425a 157,800a 14,167c 244,764c

aUSBOR

(http://www.usbr.gov/projects/dams.jsp; accessed Jan. 7, 2015). report provided by USBOR. Average for 1998-2001 (wet and dry years). cPeriod of record from 1920-1999 (WSDOE 2009). bUnpublished

Bull trout in Kachess and Keechelus Reservoirs Adfluvial bull trout in Kachess and Keechelus Reservoirs are listed as threatened under the United States Endangered Species Act (ESA; USFWS 1998). The Yakima River Basin represents one of 34 Core Areas within the larger Middle Columbia River Recovery Unit. This unit is a part of the range-wide Columbia River Distinct Population Segment associated with the ESA listing (Reiss et al. 2012). Data suggest that the population size of adult bull trout is low in each reservoir. The geometric mean number of redds observed between 2001 and 2011 was 10 in Box Canyon Creek (Kachess), 8 in the Kachess River (Kachess), and 15 in Gold Creek (Keechelus) (Reiss et al. 2012). Similar redd counts were observed between 1994 and 2000 (James 2002). In 2000, 6



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systematic snorkeling surveys between July and October indicated that adult bull trout begin migrating into Box Canyon and Gold Creeks in early August. Adults moving into the Kachess River were delayed until early October. The total number of adult bull trout observed during each survey only ranged between 10 and 25 individuals (James 2002). Conversely, adfluvial populations in Rimrock and Bumping Reservoirs (Naches arm of Yakima River Basin) are considered relatively healthy and stable (Reiss et al. 2012). Mark-recapture estimates of abundance indicate that Indian Creek and the South Fork of the Tieton River (Rimrock) each contain 1,000 or more spawning adults annually. Deep Creek (Bumping) contains approximately 500 adult fish (James 2002). Current dam operations Kachess and Keechelus Reservoirs are primarily used to meet upper Yakima River Basin irrigation demands. Irrigation demands are met by releases from Keechelus dam through bypassed reservoir inflows early in the season (mid-March) or stored water releases starting mid-April to mid-June. Draw-down is currently more severe in Keechelus than Kachess (Figures A1 and A2, Appendix A). On average (1981-2010), water storage in Keechelus drops by 78%, which corresponds to a drop in surface elevation of ~80 ft. In both Kachess and Keechelus, water is discharged from the lower depths of the metalimnion and upper depths of the hypolimnion early in the spring and summer, but from the metalimnion and epilimnion later in summer given the extent of draw-down and fixed elevation of the outlet structures (unpublished report provided by USBOR). In addition to irrigation demands, Keechelus dam operations are shaped by spring Chinook salmon spawning requirements in the upper Yakima River. Water releases alternate between storage reservoirs in the Yakima and Naches arms of the basin. Releases from the Yakima arm predominate in the late spring and summer. Releases then flip to the Naches arm in September when spring Chinook salmon spawning begins in the upper Yakima River. This managed hydrologic regime encourages spring Chinook salmon to spawn in areas of the river channel that will remain wetted throughout the eggincubation period (February–March) when releases are minimized to allow the reservoirs to refill. Releases also switch from Keechelus to Kachess Reservoir in September of most years (Figure 1). This management scheme is tailored toward maintaining suitable spawning flows for spring Chinook salmon in the upper Yakima River beneath Keechelus dam (information provided by USBOR). Kachess drought relief pumping plant (KDRPP)

The outlet structure in Kachess Reservoir does not provide access to water stored below an elevation of 2,192 ft, 70 ft below the surface at full pool. The KDRPP would

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Figure 1. Average daily releases in cubic feet per second (cfs) from Kachess (grey line) and Keechelus (black line) Reservoirs during the 2001-2010 water years. Data provided by USBOR.

allow up to 200,000 additional ac-ft of water to be withdrawn from currently inactive storage, providing supplementary water supply during drought years. A 1,000 cfs pumping station, with intake below the thermocline in the hypolimnion, would withdraw the inactive storage. Discharging 200,000 ac-ft of inactive storage would draw the reservoir down by an additional 80 ft below the current outlet structure (USBOR and WSDOE 2015). Primary considerations for bull trout include: A. How will increased draw-down during periods of drought change the intensity and timing of thermal stratification, and the volume of cold-water habitat for bull trout? B. Will increased draw-down during periods of drought confine juvenile bull trout with their potential predators, and adult bull trout with their prey? If so, how might this impact predation mortality and growth? C. Will increased draw-down during periods of drought restrict passage by juvenile and adult bull trout to and from tributaries during key periods (e.g., spawning)?

Keechelus-to-Kachess conveyance (KKC)

The KKC would convey water (gravity fed) from Keechelus to Kachess reservoirs via a tunnel with a maximum capacity of 500 cfs. The 3.7 mile long tunnel would likely extend from the existing outlet of Keechelus to the west shoreline of Kachess. The purpose of this conveyance is to provide more operational flexibility when managing releases from Keechelus and Kachess dams. Specific goals include (1) reducing flows in the upper Yakima River to improve rearing conditions for juvenile salmonids (e.g., steelhead) during the irrigation season, (2) enable storage of more runoff from the Keechelus Reservoir drainage in Kachess to provide additional water supply for municipal, domestic, and agricultural use, and (3) augment flows to refill Kachess 8



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Reservoir during and after drought years (USBOR and WSDOE 2015). Altering the timing, extent, and frequency of this conveyance will have different impacts on the surface elevation, thermal environment, hydraulic retention time, nutrient supply, and access to tributaries by fish in both Keechelus and Kachess Reservoir. The KKC could potentially buffer heavy draw-downs of Kachess by the KDRIPP during drought years.

OBJECTIVES AND APPROACH The primary objective of this report is to evaluate the contemporary food web structure of Kachess and Keechelus Reservoirs and guide future work regarding the potential impacts of proposed water management alterations on bull trout. We address this objective by combining existing information with contemporary field data collected July 2014 through October 2016 on the temporal-spatial dimensions of the thermal environment, food supply (density of edible zooplankton and pelagic planktivores), distribution, size, age, and diet of key predators and prey, and the overall trophic structure of each food web through diet and stable isotope analyses. We use these data to guide bioenergetics model simulations to estimate the predation impact imposed by bull trout and other predators on fish prey, and the consumption demand of the dominant planktivores on the seasonal supply of zooplankton. We use these modeling results to gauge the current carrying capacity of each reservoir for key species (Beauchamp et al. 2007; Hansen et al. 2016; Sorel et al. 2016b). The remainder of this report is broken into four sections, each addressing a specific objective related to evaluating food web structure, and describing and quantifying key interactions: 1. Food web structure informed by stable isotopes and diet analysis.—We first characterize the food web structure of each reservoir using stable isotope analysis. We use this information to identify key trophic pathways and predator-prey interactions that affect sub-adult and adult bull trout in these systems. The stable isotope analysis provided context and guidance on size-related trophic relations for the more intensive diet analysis. Diet analysis provided higher taxonomic resolution for prey, added insights into seasonal shifts in diet composition and identified the vulnerable size fraction of zooplankton and prey fishes eaten by different species and sizes of consumers. Collectively, results from the stable isotope and diet analyses guided how diet variability through time and among sizes of consumers was modeled in bioenergetics simulations. 2. Foraging and growth environment for bull trout and kokanee.—Here, we link data on the seasonal thermal regime, depth- and density-distribution of zooplankton, and bioenergetics simulations of temperature-dependent growth to characterize the contemporary foraging and growth environment for bull trout and kokanee (important prey for bull trout based on results of section 1) in Kachess Reservoir. 3. Consumption demand versus food supply for key predators and prey.—In this section, we model the consumption demand of bull trout, burbot, and northern pikeminnow feeding on kokanee and alternative fish prey and kokanee feeding on zooplankton to evaluate the relative importance of food supply, temperature, and predation mortality as limits to the production of each species in Kachess Reservoir. 9



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4. Conclusions and considerations for bull trout.—Last, we summarize key findings, outline potential impacts of the KDRPP and KKC on bull trout in Kachess and Keechelus, and review remaining data gaps and future research needs.

1. FOOD WEB STRUCTURE and TROPHIC INTERACTIONS Introduction Trophic interactions among predators, prey, and competitors play a central role in determining which processes influence production of key species in food webs. Diet composition and stable isotope analysis provide complementary perspectives on the structure and function of food webs. These two methods differ in the level of effort required and temporal resolution represented. Diet analysis is quite labor-intensive and typically represents the very recent feeding history of a consumer (i.e., 6-24 h depending on temperature and gut fullness). Diet analysis can offer the advantage of high-resolution data on seasonal, size- and habitat-specific composition of food, including the species and size of important prey. Since diets and feeding behavior often change through time and across different habitats and sizes of consumers, repeated intensive sampling is needed to account for these important dimensions of variability. When sample sizes for diet analysis are limited by logistical challenges or conservation concerns regarding ESAlisted species, the more integrative, but lower taxonomic resolution of stable isotope analysis can offer a valuable corroboration for diet data. Carbon and nitrogen stable isotope ratios (δ13C and δ15N in ‰ or parts per thousand) are effective tracers of energy-flow in aquatic food webs (Vander Zanden et al. 2003). Stable isotopes map the integrated feeding history (i.e., 6-12 months) of different members of a food web, and inform the primary energy pathways (benthic versus pelagic) supporting different predator and prey groups. In general, a 3-4‰ increase in δ15N represents a full step trophic level from prey to predator; therefore, δ15N can be used to estimate the trophic position (e.g., primary consumer versus top predator) of different size-classes of consumers (Cabana and Rasmussen 2001). In addition, the δ13C of pelagically derived phytoplankton is isotopically depleted relative to benthic algae (Hecky and Hesslein 1995). This means that phytoplankton contains relatively fewer, heavier 13C atoms, and more of the lighter 12C atoms, when compared to an isotopic standard. This leads to lower (more negative) δ13C values for phytoplankton relative to benthic algae. Unlike nitrogen isotopes, differences in carbon isotopes from pelagic and benthic habitats remain relatively constant from prey to predator, and therefore, can be used to inform the contribution of pelagic versus benthic (littoral zone) resources to fish production at higher trophic levels (Vander Zanden et al. 2003). We characterized the food web structure of each reservoir using stable isotope and diet analysis to identify key trophic pathways and predator-prey interactions that affect sub-adult and adult bull trout in these systems. The stable isotope analysis provided context and guidance on size-related trophic relations for the more intensive diet analysis. Diet analysis provided higher taxonomic resolution for prey, added insights into seasonal shifts in diet composition and identified the vulnerable size fraction of zooplankton and 10



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prey fishes eaten by different species and sizes of consumers. Collectively, results from the stable isotope and diet analyses guided how diet variability through time and among sizes of consumers was modeled in bioenergetics simulations. Methods Stable Isotope Analysis.—We used stable isotope analysis to characterize the contemporary food web structure of Kachess and Keechelus Reservoirs. We collected zooplankton with a Clarke-Bumpus sampler in Kachess during August 2014 and in Keechelus during May 2015. Fish used for stable isotope analysis were sampled August 2014 through August 2016 using gill nets, set-lines, boat electrofishing, hook-and-line, and midwater trawling. Additional tissue samples from adult bull trout collected in 2012 were included to supplement the analyses (N = 8 from Kachess, N = 1 from Keechelus). Caudal fin tissue from approximately N = 5-10 specimens from each species and size class of fish and their potential prey were processed (dried, ground, homogenized and weighed), and submitted to the *IsoLab at the University of Washington for elemental analysis of δ13C and δ15N. Samples were analyzed using a Costech Elemental Analyzer, Conflo III, and a MAT253, which enables continuous flow based measurement of solid organic material. The reference material for carbon was Vienna Pee Dee Belemnite and atmospheric N2 for nitrogen. The integrative nature of stable isotopes enabled relatively high-precision estimates of trophic position with relatively low sample sizes (McIntyre et al. 2006; Schoen and Beauchamp 2010; Lowery and Beauchamp 2010). Diet Analysis.—We estimated the seasonal and size-related diet composition of bull trout, northern pikeminnow and burbot, the other presumptive piscivores, and kokanee, an important prey species for bull trout. Fish used for diet analysis were sampled August 2014 through October 2016. The blotted-wet mass of each prey fish species and functional group of invertebrate prey was measured and recorded to the nearest 0.1 mg. Prey fishes were identified to species, and lengths (total, fork, standard, diagnostic head bones) were recorded to estimate reconstructed size at consumption whenever possible (Hansel et al. 1988). Diet composition was calculated separately for each non-empty stomach sample and was expressed as the proportional wet-weight contribution of each prey species or category to the total diet of a consumer (Chipps and Garvey 2007). The individual diet compositions were averaged within each species of consumer x size class x season combination to capture the primary sources of trophic variability for the major piscivores and kokanee (Beauchamp et al. 2007).

Results Stable Isotope Analysis.—The top predators in both reservoirs exhibited ontogenetic shifts in trophic position and energy pathways (Figure 2), whereas intermediate and lower trophic levels relied to differing degrees on pelagic and benthic energy pathways in Kachess and Keechelus Reservoirs (Figure 3). Isotopic signatures for bull trout (FL >300 mm) were consistent with a heavy reliance on pelagic prey fishes in both reservoirs. Both northern pikeminnow and burbot became increasingly piscivorous (increasing δ15N) and showed greater reliance on pelagic prey (declining δ13C) with 11



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increasing body size (FL 400 mm). Cannibalism on smaller northern pikeminnow and predation on smaller burbot was evident during all seasons and across most size classes of northern pikeminnow. Crayfish and redside shiners were important prey during summer, whereas kokanee and other salmonids showed no apparent seasonal pattern in the diet (Figure 4). Smaller burbot (TL 400

< 400

> 400

8

0.5 No Data

August

1.0

24

20

20

3

4

4

5

0.5

0.0 1.0

September

Proportion of Diet by Wet Weight

0.0

0.5 No Data

0.0 9

October

1.0

7

0.5 No Data

Kokanee Other/Unk. Salmonid Cottid Northern Pikeminnow Redside Shiner Burbot Other/Unk. Fish Crayfish Insect Other Invertebrates

0.0 < 200

200-300 300-400

Size Class (Fork Length in mm) Figure 4. The proportional weight contribution of fish and invertebrate prey by sampling month and size class of predator for northern pikeminnow, burbot, and bull trout in Kachess Reservoir during 2014-2016.

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Northern Pikeminnow

May

4

9

8

1

3

1

< 200

> 200

< 400

> 400

0.5

1.0

Kokanee Other/Unk.Salmonid Cottid Northern Pikeminnow Redside Shiner Burbot Other/Unk. Fish Crayfish Insect Other Invertebrates

Burbot

0.0

September

Proportion of Diet by Wet Weight

1.0

0.5

0.0

Size Class (Fork length in mm) Figure 5. The proportional weight contribution of fish and invertebrate prey by sampling month and size class of northern pikeminnow and burbot in Keechelus Reservoir during 2014-2015. Low reservoir levels prevented adequate boat access and sampling which severely limited data collection.

Figure 6. Relationship of prey length to predator length for diets sampled from piscivorous burbot and northern pikeminnow in Kachess Reservoir during 2014-2016.

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(2SE). Lengths of Daphnia (N = 86) consumed by kokanee in Keechelus averaged 1.22 ± 0.03 mm (2SE).

Discussion Keechelus Reservoir is supported more by pelagic production when compared to Kachess, and consequently, more burden is placed on pelagic energy pathways in Keechelus. This pattern is likely influenced by the greater draw-down and more extensive drying of the littoral zone during the growing season of Keechelus under current water management. Similarity in the bathymetry of Kachess and Keechelus (Hiebert 1999) indicates that more frequent and extensive draw-down of Kachess with the KDRPP could also erode any existing littoral production, placing more burden on the pelagic energy pathways important for bull trout and their prey. The primary piscivores in Kachess Reservoir feed on a variety of benthic and pelagic fish and benthic invertebrates, with larger piscivores shifting to larger and more pelagic prey like kokanee. Similar patterns in diet and stable isotopes were reported for northern pikeminnow in Lake Washington (McIntyre et al. 2006). Northern pikeminnow and burbot also exhibited a measurable amount of predation on smaller size classes of piscivores. In nearby Merwin Reservoir on the Lewis River, cannibalism and additional predation by tiger muskellunge, reportedly reduced the recruitment and abundance of northern pikeminnow that became large enough to be effective predators on pelagic salmonids (Sorel et al. 2016a). Too few diet samples from bull trout were available to detect cannibalism or predation on other species of piscivores. Both stable isotope and diet data reiterated the importance of kokanee and other pelagic oriented fish as the primary forage base for bull trout, while verifying that kokanee and other pelagic oriented fish were also important prey for larger northern pikeminnow and burbot. Thus, the bull trout population could be affected by several types of trophic interactions including competition among piscivores for kokanee if kokanee becomes a limiting food resource, and the effects of predation mortality within and among species of piscivores. The size at which adfluvial bull trout first migrate into the reservoirs can dictate whether predation mortality, food availability, or both are important influences on the survival and production of the populations utilizing Kachess or Keechelus Reservoirs. For juvenile bull trout in Bumping and Rimrock Lakes, downstream trapping in the fall during 1994-2000 in Indian Creek (Rimrock), South Fork of the Tieton River (Rimrock), and Deep Creek (Bumping) captured juvenile and sub-adult bull trout ranging from 60-290 mm total length (James 2002). The juvenile and sub-adult bull trout captured during those surveys were larger in South Fork of the Tieton River and Deep Creek (modal length of ~230 mm) than in Indian Creek (modal length of ~100 mm). Catch in downstream traps suggested that bull trout immigrated into these reservoirs at lengths ≥200 mm, although no samples were available from within the reservoirs to confirm the size frequency of the smallest size 17



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classes utilizing lentic habitats. Nonetheless, the size modes observed from downstream trapping provide the basis for useful scenarios. If entering the reservoirs at a modal size of 100 mm FL, bull trout would be too small to be effective piscivores on any prey fishes except some sculpin, the smallest available redside shiners, and benthic invertebrates, whose production is inhibited by fluctuating reservoir elevations. Moreover, 100-mm bull trout would be susceptible to predation by piscivores as small as 200-250 mm which are naturally more numerous than their older conspecifics. In contrast, juvenile bull trout that first migrate to the reservoirs at FL ≥200 mm would be capable of feeding on a wider array of species and sizes prey fishes (e.g., sculpins or redside shiners ≤80-100 mm FL) and would only be vulnerable to predation by piscivores ≥400-450 mm FL. Stable isotope samples from juvenile and sub-adult bull trout, and data on bull trout spatial distribution, size-structure, and size at immigration into each reservoir would help inform the potential for cannibalism, and the vulnerability of juvenile bull trout to predation by burbot or northern pikeminnow. Kokanee and other salmonids consistently represent significant fractions of the diet for adfluvial bull trout during lake residence in many western lakes and reservoirs (Jeppson and Platts 1959; Bjornn 1961; Fraley and Shepard 1989; Beauchamp and Van Tassell 2001; Clarke et al. 2005). Additionally, adfluvial bull trout and lake trout Salvelinus namaycush fill very similar niches in lake food webs. Both exhibit an affinity for eating kokanee and other salmonids, and may continue to feed on these prey even when availability declines (Jeppson and Platts 1959; Leathe and Graham 1982; Johnson and Martinez 2000; Beauchamp and Van Tassell 2001; Beauchamp and Shepard 2008; Schoen and Beauchamp 2010; Ellis et al. 2011). When kokanee represent the primary forage base for bull trout, the abundance and availability of kokanee can influence the growth, reproductive success, and degree of cannibalism exhibited by the bull trout population (Beauchamp and Van Tassell 2001). Therefore, factors that influence the abundance, availability, and productivity of kokanee, such as stocking, the magnitude and duration of thermal stratification, seasonal zooplankton production, and predation could have direct bearing on the productivity of bull trout. The seasonal diet composition of kokanee from the limited number of samples we obtained in Kachess and Keechelus corresponded well with the diet composition of sockeye salmon feeding in Lake Washington (Beauchamp et al. 2004; Scheuerell et al. 2005; D.A. Beauchamp, unpublished data); however, many of the stomachs analyzed contained high fractions of unknown or unidentifiable cladocerans. Due to our small sample size and the similarity of diet, we used data from juvenile sockeye salmon feeding in Lake Washington to inform the monthly diet composition for each age-class of kokanee in Kachess in further analyses. Results of our kokanee diet analysis were consistent with previous findings that kokanee preferentially feed on Daphnia (Koski and Johnson 2002; Scheuerell et al. 2005), and generally select those that are greater than or equal to the average size in the population (Beauchamp et al. 1995; Baldwin et al. 2000), but routinely ingest 1-mm Daphnia and are capable of eating 0.6-0.8 mm zooplankton (Beauchamp et al. 2004). 18



2017

Conclusions 1. Keechelus Reservoir is supported more by pelagic production when compared to Kachess. This is likely a result of the more extensive draw-down during the growing season. Similarity in the bathymetry of Kachess and Keechelus (Hiebert 1999) indicates that more frequent and extensive draw-down of Kachess with the KDRPP could also erode existing littoral production, placing more burden on the pelagic energy pathways important for bull trout and their prey. 2. Adult bull trout are top predators and highly piscivorous. Kokanee and other pelagic oriented fish are key prey, which rely heavily on Daphnia when available. 3. Stable isotope samples from juvenile and sub-adult bull trout, and data on bull trout spatial distribution, size-structure, and size at immigration into each reservoir would help inform the potential for cannibalism, and the vulnerability of juvenile bull trout to predation by burbot or northern pikeminnow. 4. Adult burbot and northern pikeminnow are piscivorous and could impact populations of prey important to bull trout, or consume juvenile bull trout. Both northern pikeminnow and burbot eat a mix of benthic and pelagic prey, but incorporate progressively higher proportions of pelagic prey fishes like kokanee into their diet at larger sizes (>400 mm).

19



2017

2. FORAGING AND GROWTH ENVIRONMENT FOR BULL TROUT AND KOKANEE Introduction Vertical gradients in food supply, temperature, oxygen, light, and turbidity influence the distribution, growth, and survival of predators and prey. Diel-seasonal changes in these factors could aggregate or segregate predators and prey depending on how each variable affects the growth efficiency and foraging capability of different functional groups of fish, and the profitability and predation risk associated with feeding in different habitats (Martinez and Wiltzius 1995; Hardiman et al. 2004; Hansen et al. 2013a). Most importantly, knowing how the existing thermal environment influences the temporalspatial overlap between bull trout and kokanee, kokanee and concentrations of Daphnia, and kokanee with other potential predators in Kachess and Keechelus will help determine potential mechanisms through which altered water management regimes might influence distribution, growth, and predation mortality. Methods Based on the seasonal thermal regime and supply of zooplankton, we describe how changes in vertical temperature profiles and the density- and depth-distribution of zooplankton structures the foraging and growth environment for kokanee and adult bull trout. We focus on the period of peak thermal stratification, since environmental conditions can either enable a higher growth period that corresponds with spatiallyoverlapping beneficial temperatures and food availability, or can be the most limiting for salmonids due to poor thermal conditions or a poor or inaccessible food supply (Hansen et al. 2013a). We combined monthly vertical temperature profiles with empirical data on depth-specific densities of Daphnia and adult copepods, the diel-, depth-, and densitydistribution of kokanee estimated from hydroacoustics and midwater trawling, and the nearshore distribution of other fishes from catches in short-term gill net sets in Kachess to determine thermally-influenced seasonal patterns in spatial overlap among species of predators, prey, and competitors. We linked these data with bioenergetics model simulations of temperature-dependent growth for bull trout and kokanee to assess whether the extent of overlap between these species should increase or decrease with shifts in the thermal environment, and during drought years when the KDRPP could be in operation. See Polacek (2014) for specific methods on measuring seasonal temperature profiles, and sampling and processing of zooplankton. Hydroacoustics.—A hydroacoustics survey was conducted on 18-19 August 2014 in Kachess to estimate the abundance, size structure, and depth-distribution of pelagic fishes. The survey consisted of two components: (1) sampling a single offshore transect repeatedly over a day-dusk-night sequence to characterize diel changes in fish density and depth-distribution, and (2) a reservoir-wide night-time survey to estimate size structure, density, and abundance of different sized pelagic fish targets. The night-time survey consisted of 8 contiguous zig-zag transects along the main body of Kachess. Little Kachess was not surveyed due to shallow water depths. 20



2017

For these surveys, a calibrated split-beam 430 kHz down-looking transducer (6.8° full beam angle) was towed 1 m below the surface at 5-7 kph. The transducer was connected to a Biosonics DE-6000 scientific echosounder (target strength threshold = 65 dB; ping rate = 3 pps; pulse width = 0.3 ms; detection range = 60 m). Hydroacoustics data were analyzed using a target counting algorithm in EchoView version 5.0 software (by Myriax Pty. Ltd.). Post-processed data were exported from EchoView to Microsoft Excel where size-specific densities (fish per 1000 m3), stratified by depth (5 m intervals), were computed. These densities were based on the total number of targets of different sizes detected and the total volume of water sampled by the acoustic beam in each depth interval (Beauchamp et al. 1997; Beauchamp et al. 2009). A minimum target strength acceptance criterion of -60 dB (20 mm total length; Love 1977) was employed to exclude organisms smaller than postlarval fish. Depth- and size-specific fish densities from the nocturnal hydroacoustics survey were partitioned into different species based on catches in midwater trawls. Fish schools were not encountered during any of the day, dusk or night transects. Midwater trawling.—Nocturnal midwater trawling (N = 7 tows) was conducted offshore along the longitudinal axis of Kachess Reservoir on 20-21 August 2014 using a 7-m planing V-hulled aluminum boat (Almar Sounder 22). Each tow was either 15 min (3 tows) or 30 min (4 tows). The Almar was outfitted with a 3 m wide × 7 m deep × 18 m long opening-closing bar midwater trawl with graduated mesh sizes terminating in 3-mm knotless mesh in the cod end (Enzenhofer and Hume 1989). Midwater trawls were deployed at depths containing distinct layers of fish targets observed during the hydroacoustics survey (20 to 50 m depths). Bioenergetics simulations of growth.—Understanding the bioenergetic growth responses of bull trout and kokanee to ambient food sources and thermal regimes is needed to conceptualize how a change in water elevation and thermal structure from an altered water management regime might affect their depth-distribution and growth in Kachess and Keechelus. Growth by individual fish responds to four major factors: body mass, temperature, feeding rate, and energy density of the prey (Beauchamp 2009). We used a bioenergetics model specific to each species (Beauchamp et al. 1989; Mesa et al. 2013) to simulate the growth (expressed as % body weight per day) for different sizes of bull trout and kokanee feeding at typical rates (25-75% of their maximum theoretical consumption rate per day; Cmax) on key prey (5,500 J/g kokanee for bull trout and 1,950 J/g Daphnia for kokanee; Baldwin et al. 2003; D.A. Beauchamp, unpublished data) over a range of temperatures (1-25°C). We compared these simulated growth responses to the seasonal thermal environment empirically measured in each reservoir, and the observed distribution of kokanee. Results and Discussion Seasonal thermal environment.—Each reservoir exhibited similar seasonal patterns of spring warming, thermal stratification and destratification with depths of 0-10 m representing the epilimnion, 10-20 m the thermocline (metalimnion), and depths greater 21



2017

than 20 m representing the hypolimnion where temperatures consistently remained below 5-6°C throughout the year (Figure 7). We report the thermal profiles for 2015 here, because it was the most complete record for Kachess Reservoir (Keechelus became inaccessible after August due to low water levels), but comparisons with the more sporadic measurements from other years suggested that the duration and magnitude of thermal stratification were relatively similar among years during 2014-2016, despite the generally warmer summer in 2015. Surface warming progressed from April (6-7oC) through May (11-12oC). Measurable thermal stratification formed in June and peaked in early July with epilimnetic temperatures of 20-22oC. Epilimnetic temperatures declined to 19-20oC during mid-July and August. Epilimnetic cooling progressed rapidly through September (15oC) and into autumn, but thermal stratification persisted through October (11oC) with some residual stratification remaining till early November. Current and previous studies suggest that the temperature of the epilimnion during peak thermal stratification varies between 18°C and 22°C among years (Mongillo and Faulconer 1982; Hiebert 1999). In Keechelus Reservoir during August 2014, the epilimnion became shallower, the strength of thermal stratification increased (i.e., more abrupt thermocline), and temperatures in 10-15 m depths were significantly cooler relative to late July (Figure 7). This could be the effect of the heavy draw-down of Keechelus and compression of the hypolimnion over that period. Temperature oC 4

6

8

10

12

14

16

18

20

22 2

4

6

8

10

12

14

16

18

20

22

0

0

10

10

Kachess April May June July 7-8, 2015 July 20, 2015 August September October November

20

30

40

Keechelus 20

Depth (m)

Depth (m)

2

Temperature oC

30

40

Figure 7. Monthly vertical temperature profiles for Kachess and Keechelus Reservoirs were measured during 2015, but were generally representative of thermal conditions observed during 2014-2016. The August profile in Keechelus was taken from August 29, 2014.

Seasonal supply of zooplankton.—The monthly average density of Daphnia and copepods in Kachess and Keechelus were relatively low and ranged from near zero to 3.2/L within any given depth interval (Figure 8). Densities of adult copepods were relatively high in April and May, and provided an alternative prey source for kokanee and other planktivorous fishes prior to the Daphnia blooms that peaked in June-July in 22



Copepods (#/L)

Daphnia or cladocerans (#/L)

5

Kachess

Keechelus

Epilimnion (0-10 m) Metalimnion (10-20 m) Hypolimnion (>20 m)

4 3

15

2017

Cle Elum

12 9

2

6

1

3

0

0

5

15

4

12

3

9

2

6

1

3 0

0 Apr May Jun Jul Aug Sep Oct Nov Apr May Jun Jul Aug

Apr May Jun Jul Aug Sep Oct

Figure 8. Monthly density of zooplankton in different depth-strata in Kachess, Keechelus, and Cle Elum Reservoirs during the growing season. Data for Kachess and Keechelus are from 20142016. Each point represents the average of two sampling stations in each reservoir (1/3 and 2/3 along the longitudinal axis of each reservoir). Comparative data from Cle Elum Reservoir were collected in 2005 (Lieberman and Grabowski 2007). Data points for Cle Elum in the 0-10 m depth stratum are the average of three sampling stations (upper, middle, and lower parts of reservoir). Error bars represent 1 SE. Note that the y-axis range spans much higher zooplankton densities for Cle Elum than for Kachess and Keechelus.

Kachess and July-August in Keechelus. In general, densities of Daphnia and copepods were higher in the warm epilimnion than in the cooler meta- and hypolimnion in Keechelus, a common pattern observed by Daphnia in many western lakes and reservoirs (Edmondson and Litt 1982; Baldwin et al. 2000; Hardiman et al. 2004). Daphnia were both available and peaked earlier in Kachess, and remained available at moderate densities in the epi- and metalimnion through summer and fall (Figure 8). The mean number of eggs per female Daphnia during different months and at different depths was low in both Kachess (mean range: 0.07-0.58) and Keechelus (0.0-0.51). Similarly, the body length (mean ± 2SE) of Daphnia was relatively low, and ranged from 0.80 ± 0.04 mm in April to 1.22 ± 0.04 mm in October for Kachess, and 0.83 ± 0.08 mm to 1.12 ± 0.06 mm over the months sampled in Keechelus. Comparative data from Cle Elum showed different patterns of zooplankton density. Most apparent were: (1) the relatively high density of copepods in April and May, and (2) the strong peak in cladocerans (mostly Daphnia, some Bosmina, and few Leptodora) in June, both of which were largely absent or less prominent in Keechelus and Kachess (Figure 8). These patterns have important implications for the feeding and growth of kokanee (or reintroduced sockeye salmon). Daphnia were not readily available until June in Kachess, but copepods were present in April and May, which should allow natural or stocked kokanee fry to persist over spring as long as early feeding demand does not 23



2017

exceed supply (Beauchamp et al. 2004). In Keechelus, Daphnia were not readily available until July, however in June, Holopedium were present at 1.5/L and showed up in kokanee diets, indicating that kokanee use alternate prey sources when Daphnia are unavailable, a pattern not seen in Kachess (Appendix Figure A3). In Cle Elum and Keechelus, Daphnia and other cladocerans were concentrated in the upper 10 m of the water column throughout the growing season, which corresponds to the epilimnion during thermal stratification. Given surface temperatures in June (Figure 8), kokanee should have full access to the strong spring bloom of Daphnia in Cle Elum. However, the apparent delayed bloom of Daphnia in Keechelus corresponded with much warmer surface temperatures, which could force kokanee to feed on the lower supply of Daphnia in the cooler metalimnion during summer stratification. Seasonal depth distribution of the nearshore fish community in Kachess Reservoir.—We inferred the seasonal depth distribution of fishes in nearshore and benthic regions from catches using depth-stratified multi-mesh gill nets and surfaceoriented electrofishing in Kachess Reservoir during August 2015 and May, August, and October 2016 (Table 2). Although the steep bathymetry of the basin made it challenging to sample discrete depth intervals consistently (except for the 0-10 m interval), if catch rates were lower in nets spanning 0-20 m than in nets concurrently fishing at 0-10 m, then we inferred that most of the fish were concentrated in the upper 0-10 m. If catch rates were similar between 0-10 m and 0-20 m depths, then we inferred that fish were evenly distributed across 0-20 m. If catches were higher in the 0-20 m than 0-10 m nets, then we inferred that most of the fish were concentrated in 10-20 m depths. Kokanee were rare in nearshore gillnet catches except during October as adults adopted pre-spawning staging along slope zones. Adult bull trout were also rare (N = 3) in nearshore gill net catches and were only encountered in May sampling. Burbot primarily occupied 0-10 m depths during spring, were more evenly distributed across depths during peak summer stratification, then shifted primarily to depths below 10 m during fall (Table 2). Northern pikeminnow appeared to be relatively evenly distributed across 0-20 m during all three seasons. These catch data suggest that both piscivorous burbot and northern pikeminnow could forage above and within the thermocline during thermallystratified periods. Although redside shiners were too small to be captured in gill nets, they were captured at relatively high rates with an electrofishing boat and minnow traps within the 0-10 m depth interval in May (electrofishing only) and August, but were not encountered in deeper samples using midwater trawls; therefore, we inferred that redside shiners primarily utilized the 0-10 m nearshore and epilimnetic zone. The high spatial-temporal overlap among pre-spawning kokanee and predatory burbot and northern pikeminnow during October suggests that maturing kokanee could be particularly vulnerable to predation at that time. This notion was supported by observed increases in the proportion of kokanee and unidentified salmonids in large northern pikeminnow and burbot diets during October (Figure 4). Similar to burbot and northern pikeminnow, adult bull trout occupied shallow nearshore habitat during May before establishment of thermal stratification. Interactions and potential competition among these predators could be most important during that period. However, due to the small 24



2017

sample size of bull trout captured, conclusions must be conservative regarding their temporal-spatial overlap with nearshore predators and prey. Table 2. Mean catch per set of key species in Kachess Reservoir during August 2015 and May, August and October 2016 by depth strata using gill nets (upper table) and samples from just the surface layer using an electrofishing boat (lower table).

Gill nets

N

Bull trout

Kokanee

Burbot

Northern pikeminnow

Mountain whitefish

Largescale sucker

Redside shiner

May 0-10 10-20 0-20

8 1 5

0.3 0.0 0.2

0.4 0.0 0.0

0.3 0.0 0.2

8.6 0.0 5.0

0.0 0.0 0.2

2.9 0.0 2.6

0.0 0.0 0.0

August 0-10 10-20 0-20

6 1 7

0.0 0.0 0.0

0.0 0.0 0.0

0.0 0.0 0.0

5.5 3.0 4.9

0.2 0.0 0.1

1.5 1.0 1.1

0.0 0.0 0.0

October 0-10 2 0-20 8

0.0 0.0

1.5 5.0

0.5 2.3

3.0 5.5

0.0 0.3

1.5 1.6

0.0 0.0

Mountain whitefish

Largescale sucker

Redside shiner

Boat electrofishing May 0-10 August 0-10

N

Bull trout

Kokanee

Burbot

Northern pikeminnow

18

0.0

0.0

0.1

3.1

0.4

3.2

15.2

33

0.0

0.0

0.2

4.8

0.1

2.4

11.3

Kokanee density, distribution, size-structure, and growth.—A hydroacoustic and midwater trawl survey in Kachess Reservoir during August 2014 was used to characterize the abundance, vertical distribution, and size structure of kokanee and other pelagic fishes during thermal stratification as a precursor to estimating the consumption demand versus accessible supply of zooplankton available to kokanee and other pelagic planktivores that might compete for these resources. Catches in midwater trawls were low, but were comprised of mostly kokanee (83% of catch). Two pygmy whitefish were also captured in the trawls (Table 3). In Kachess, the largest kokanee caught in the midwater trawl was 230 mm FL, whereas the largest kokanee captured in gill nets were ≤300 mm FL. Individuals greater than 220 mm total length (N = 2) sampled during 25



2017

previous surveys were aged at 3+ (Mongillo and Faulconer 1982), and kokanee likely spawn as age-3+ adults in these systems (Beauchamp and Shepard 2008). In Keechelus, midwater trawling in May 2015 only caught kokanee fry 67% Cmax for older kokanee, and 40-55% for bull trout >375 mm FL (see Section 3).

autumn, but thermal stratification persisted through October (11oC) with some residual stratification even remaining in early November. The epilimnetic temperatures during peak thermal stratification of 20-22°C can significantly reduce the growth potential of kokanee and adult bull trout, and thus could inhibit or exclude access to epilimnetic prey during 1-2 months of the growing season. Based on hydroacoustics and midwater trawling, all age-classes of kokanee generally avoid the epilimnion (0-10 m depths) during peak thermal stratification, remaining within or below the thermocline (10-20 m depths) at all times of day.

29



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2. The density of Daphnia (key prey for kokanee) peaks in June or July in Kachess, Keechelus, and Cle Elum Reservoirs, but densities of both Daphnia and adult copepods were considerably higher in Cle Elum than the other reservoirs through most of the growing season. Daphnia were available earlier (April-June) in Kachess than Keechelus. Daphnia densities in Kachess were similar in all depth strata during June-August, then remained at similar densities in the epi- and metalimnion during September-October while declining markedly in the hypolimnion. 3. In Keechelus and Cle Elum Reservoirs, Daphnia were concentrated in the epilimnion during the growing season while densities in the metalimnion were generally ~50% lower and hypolimnetic densities were minimal. Based on the seasonal thermal regime, kokanee should have full access to the peak bloom of Daphnia in June in Cle Elum, but they may be more restricted in Keechelus since the peak bloom of Daphnia appears later in July when surface temperatures are warmer. 4. The high spatial-temporal overlap among pre-spawning kokanee and predatory burbot and northern pikeminnow during October suggests that maturing kokanee could be particularly vulnerable to predation at that time. Similar to burbot and northern pikeminnow, adult bull trout occupied shallow nearshore habitat during May (the only time they were detected) before establishment of thermal stratification. Therefore, interactions and potential competition among these predators could be most prominent during that period.

30



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3. CONSUMPTION DEMAND VERSUS FOOD SUPPLY FOR KEY PREDATORS AND PREY Introduction We estimated the annual consumption demand of burbot, northern pikeminnow, and bull trout feeding on kokanee and alternative fish, and the monthly consumption demand of kokanee feeding on copepods and Daphnia in Kachess with a bioenergetics model specific to each species (Beauchamp et al. 1989; Rudstam et al. 1995; Peterson and Ward 1999; Mesa et al. 2013). These models operate on a daily time-step and estimate the feeding rate (% of Cmax) and consumption rate (g of prey/d) necessary to achieve the annual, seasonal, or monthly growth rates observed by different age-classes of consumers. These feeding and prey consumption rates account for monthly or seasonal changes in diet composition, prey energy density, thermal experience, and the species-specific parameters that describe the temperature-dependent and allometric effects of body-mass on consumption, metabolism, and waste (Hanson et al. 1997). We compared consumption demand by each predator to the biomass of kokanee and other pelagic fish prey in Kachess, and the consumption demand of kokanee to the monthly biomass of edible zooplankton in Kachess to gauge the current carrying capacity of Kachess for adult bull trout and kokanee over the course of the growing season. Evidence for food limitation could be considered if feeding rates by predators and kokanee are low during the growing season (i.e., 50 Average elevation (ft) Min elevation (ft) Max elevation (ft) 2014 months 2015 months 2016 months

Full pool 85.77 80.28 67.48 64.15 65.77 59.67 60.65 54.22 51.51 50.54 454.83

90-94.9% 76.51 72.25 64.31 62.08 63.63 57.33 57.89 51.68 47.73 49.32 411.46

85-89.9% 69.70 69.14 62.56 60.54 61.68 55.26 55.71 48.38 47.14 47.20 378.46

80-84.9% 66.13 67.27 61.22 58.91 59.74 53.37 53.76 46.62 45.35 45.45 349.33

75-79.9% 63.67 65.38 59.21 56.66 57.15 51.02 50.03 45.68 43.10 43.81 313.38

2260 2255 2262

2248 2246 2251

2236 2232 2239

2225 2222 2230

2211 2207 2215

Jun-Aug Apr-Jun May-Jul

Sep Jul Aug

Oct Aug Sep

Sep Oct-Nov

Oct-Nov -

Monthly production was calculated for Daphnia and copepods following Shuter and Ing (1997). The model of Shuter and Ing (1997) predicts taxon-specific daily production to biomass ratios (P/B) from mean daily water temperature (Tdaily): P/B = 10(αtaxon + β·Tdaily),

where αtaxon is -1.725 for cladocerans and -2.458 for calanoid copepods, and β = 0.044 for cladocerans and 0.050 for calanoid copepods. For these calculations, we linearly interpolated the mean water temperature measured in 0-10 m and 10-20 m depths between sampling dates from April to November (Figure 7), calculated the P/B ratio on each day within each depth-interval, multiplied these ratios by the average biomass of Daphnia and copepods available each month, then summed the daily productions across the time series. We defined food supply for kokanee as 50% of production of Daphnia in 0-10 m and 10-20 m depths available each month in Kachess (Hansen et al. 2016; Sorel et al. 2016b). We further refined this definition by assuming kokanee have access to Daphnia in the 0-10 m depth interval only during cooler parts of the growing season (April-June and October), and are restricted to feeding within the cooler metalimnion (10-20 m depths 35



2017

only) during peak thermal stratification (July-September). Conservatively defining food supply in this way guarded against uncertainties regarding whether kokanee can effectively exploit concentrations of Daphnia in the warm epilimnion, consumption demand by competitors, and interannual variability in food supply. Abundance, growth, and thermal experience of adult bull trout.—Little is known about the size structure and growth of bull trout in Kachess and Keechelus with the exception of the length frequency distributions from recent collections in 2012 and for this study in 2015 and 2016 (Figure 13). Therefore, we based our bioenergetics model simulations for adult bull trout in Kachess and Keechelus on the observed annual growth of bull trout floy tagged, captured, and recaptured during the 1999 and 2000 spawning seasons in Indian Creek (Rimrock Reservoir), South Fork of the Tieton River (Rimrock Reservoir), and Deep Creek (Bumping Reservoir), all of which are populations in the Yakima River Basin (James 2002). James (2002) summarized their growth data for individually marked bull trout into an average annual growth increment (total length in mm) for 400, 450, 500, 550, 600, 650, and 700 mm total length bull trout. We converted their initial and final total lengths (TL) into FL’s based on the relationship developed by James (2002) (TL = 1.0098*FL + 20.482), and used the weight-FL relationship developed for bull trout in Lake Billy Chinook (Beauchamp and Van Tassell 2001): Weight (g) = 0.00000326·FL3.2253, to generate annual starting and ending weights for each size-class of bull trout for the bioenergetics simulations (Table 7). This range of sizes compared favorably to the sparse length frequency data for bull trout in Kachess and Keechelus Reservoirs (Figure 13). We did not partition these changes in weight into periods of high and low growth, since there was no reliable information for doing so. 4

Bull trout

Frequency

3

Kachess Keechelus

2

1

0 250

300

350

400

450

500

550

600

650

700

Fork length (mm) Figure 13. Length frequency of bull trout sampled in Kachess and Keechelus Reservoirs during 2012 and 2015-2016.

36



2017

Table 7. Mean annual growth inputs and estimated feeding rates (% Cmax) used in the bioenergetics simulations (starting on September 15th [simulation day 1], and ending September 14th [simulation day 365]) for different size-classes of bull trout in Kachess and Keechelus based on the mark-recapture data of James (2002) for bull trout in Rimrock and Bumping Reservoirs. Estimated ages are based on data from bull trout in Lake Billy Chinook (Beauchamp and Van Tassell 2001). % Cmax values in parentheses represent the feeding rates estimated under the “drought scenario”. Mean Final Final Initial Final Initial Initial Estimated growth FL weight weight % Cmax TL FL TL age (yrs) in TL (g) (mm) (g) (mm) (mm) (mm) (mm) 400 450 500 550 600 650 700

482 500 550 595 631 673 706

82 50 50 45 31 23 6

376 425 475 524 574 623 673

457 475 524 569 605 647 679

3-4 4-5 5-6 5-6 6-7 6-7 6-7

658 981 1399 1927 2578 3367 4308

1237 1403 1923 2507 3055 3786 4432

54.48 (28.19) 41.14 (22.01) 48.67 (25.54) 47.26 (24.89) 42.81 (22.81) 40.69 (21.82) 35.36 (19.30)

Trapping and measurements of bull trout by James (2002) in 1999 and 2000 occurred between early and mid-September, or mid-September and early October depending on the year and creek. To track this growth interval, we started bioenergetics simulations on September 15th (day 1), ending September 14th of the next year (day 365), and assumed bull trout ≥500 mm total length (likely age-5 or age-6; Beauchamp and Shepard 2008) spawn and lose an average (females and males pooled) 13.7% body weight (Lowery and Beauchamp 2015) on October 1st. For simplicity, we assumed that bull trout have the same thermal experience as kokanee while in the reservoir, based on the results of Section 2 (Table 5). Lastly, we assumed bull trout feed exclusively on kokanee or other pelagic fish prey (5,500 J/g; Baldwin et al. 2003). Therefore, per-capita consumption rates reflect the maximum predation rate we would expect by different sizeclasses of bull trout on pelagic sources of fish prey over an annual cycle. We scaled the per-capita consumption rates estimated for each size-class of bull trout up to a potential population-level predation rate based on redd counts and direct snorkel observations of adults in the tributaries of Kachess and Keechelus. Both of these metrics indicated that the population size of adult spawning bull trout in Kachess and Keechelus is below 50 individuals (Reiss et al. 2012). To be conservative, we assumed each system contained an age-structured population of 100 age-3 to age-7 individuals, and that each population exhibits an annual survival rate (48%; Z = 0.7368) of that observed in Lake Billy Chinook (Beauchamp and Van Tassell 2001). We compared these population-level predation rates to the available biomass of pelagic fish prey (kokanee, pygmy whitefish, redside shiners, possibly others) at night in the upper 60 m of the water column estimated during August 2014 in Kachess via midwater trawling and hydroacoustics. For simplicity, we based these biomass calculations on the weight-length regression for kokanee developed earlier, the nocturnal size-structure and density of pelagic fish targets estimated from hydroacoustics (Figures 9 and 10), and the depthspecific water volume estimates generated for Kachess in August 2014 (Table 6). 37



2017

Predation by northern pikeminnow and burbot on kokanee and other fish.— We constructed bioenergetics model simulations for consumption demand by sizestructured populations of 1,000 piscivorous sized northern pikeminnow ≥200 mm FL and 1,000 burbot ≥200 mm TL. Because the relative abundance indices for burbot and northern pikeminnow suggested that they were 1-2 orders of magnitude more numerous than bull trout, we used size structured populations of 1,000 predatory-sized burbot and northern pikeminnow instead of the size-structured population of 100 used for bull trout. As with the other consumers, we constructed model inputs for changes in size-specific seasonal diets (Figure 4, Appendix Tables A2 and A3) and the associated prey energy densities of the diet (Table 8). The thermal experience for each consumer was estimated by combining temporal depth distributions of each species of piscivore with corresponding monthly vertical temperature profiles (Table 9). Since we found no evidence for sizedependent differences in temporal depth distributions for northern pikeminnow or burbot, the same thermal experience was assigned to all age classes for each piscivore. In general, burbot exhibited a deeper depth distribution than northern pikeminnow; thus, burbot experienced cooler temperatures throughout the year. April 1st represented day 1 for these simulations, and March 31st of the following year was designated day 365. Table 8. Energy density (J/g wet weight) for diet categories used in predator diets (northern pikeminnow, burbot, bull trout).

Prey category

Insect Cottid Redside shiner Kokanee Other/unknown salmonid Other/unknown fish Northern pikeminnow Burbot Signal crayfish Other invertebrates

Energy density Reference (J/g) Average of immature aquatic, adult aquatic and 4200 terrestrial* 4305 Mazur (2004) 5172 Author's estimate* 5200 Lowery and Beauchamp (2010) 5200 4997 6703 5125 3318 3055

Lowery and Beauchamp (2010) Author's estimate* Peterson and Ward (1999) Johnson et al (1999) Mazur (2004) Composite average of other invertebrates*

*see Appendix Table for references for values averaged to get authors estimate

Annual growth increments were used as inputs in bioenergetics model simulations to fit consumption to observed growth for each age class of northern pikeminnow ≥200 mm FL (Table 10) and burbot ≥200 mm TL (Table 11). Size-at-age was determined by opercle-based aging for northern pikeminnow and otolith-based aging for burbot. We fit a von Bertalanffy growth curve to the length-at-age data for each species. Lengths were then converted to weights using length-weight regressions derived empirically for each 38



2017

species (Appendix Figures A4-A7). The abundance of each age-class of predators within a size-structured population of 1,000 was allocated proportionally based on an annual survival rate S estimated from catch curve analysis for northern pikeminnow (S = 76.5%) and burbot (S = 83.8%). The per capita monthly biomass of each major prey category consumed was computed for each age class, expanded by age-specific abundance, and summed across all age classes of predators to produce an estimated monthly and annual predation imposed on each prey category by a size-structured population of 1,000 predators. Results and Discussion Consumption demand versus food supply for kokanee.—The simulated population-level consumption demand on Daphnia by the “natural cohort” of kokanee with annual survival S = 27% increased through the summer and peaked in August, then declined over the remainder of the growing season (Figure 14a; Appendix Table A1). The ratio of population-level consumption to monthly Daphnia production (C/P) remained below 50% of monthly production during all months of the growing season, but C/P reached 48% during August, when warm epilimnetic temperatures restricted access by kokanee to just the Daphnia production within the thermocline in the 10-20 m depths (Figure 14 b-d). Although a measurable biomass of adult copepods was also available, they did not contribute substantively to the diet except during spring and fall-winter when consumption demand by kokanee was considerably lower than during summer (Figure 14). This indicates that under the current physical and ecological constraints in these systems, stocking more fish above the 365,000 fry considered here, could create a feeding and growth bottleneck during summer (July-September) during peak thermal stratification when environmental conditions are most restrictive, particularly if the annual survival rate of kokanee is higher than 27%. C/P ratios computed when simulating the hydroacoustics based estimate of S = 48% far exceeded our conservative estimate of food supply during peak thermal stratification (Appendix Table A1). This potential bottleneck could be buffered by the relatively high densities of Daphnia in the hypolimnion (depths > 20 m) during these months in Kachess, but not in Keechelus or Cle Elum Reservoirs where hypolimnetic zooplankton densities were extremely low (Figure 8). Feeding rates (%Cmax) estimated from the bioenergetics simulations to support the observed growth and per-capita consumption rates for kokanee ranged from 19-104% and averaged 61% across all growth periods and age-classes of kokanee (Table 4). The estimated feeding rates during summer stratification ranged 34-66% Cmax for age 0-1 kokanee, and >67% Cmax for older kokanee. Values of %Cmax exceeding 100% can be expected for fish feeding on Daphnia, since Daphnia are compressed in the gut (Luecke and Brandt 1993; Stockwell et al. 1999). Feeding rates and modeled per-capita consumption rates changed little under the “drought scenario”, when the thermal experience of kokanee was increased by 2°C each month (Table 4). Across months, population-level consumption demand of all three prey categories combined (Daphnia,

39



2017

Table 9. Monthly (1st of each month) thermal experience used to model the consumption demand of each age-class of northern pikeminnow and burbot in Lake Kachess. Water temperatures were linearly interpolated between the dates listed here. Dates in bold represent empirical measurements in Kachess during 2014-2015. Start and end temperatures were estimated from previous measurements by USBOR (unpublished data).

Age-class

Calendar day

Simulation day

N. pikeminnow thermal experience (°C)

All All All All All All All All All All All All All All All All All All All All All All All

4/1/2015 4/21/2015 5/1/2015 5/19/2015 6/1/2015 6/18/2015 7/1/2015 7/8/2015 7/21/2015 8/1/2015 8/6/2015 8/25/2015 9/1/2015 9/16/2015 9/30/2015 10/1/2015 11/1/2015 11/4/2015 12/1/2015 1/1/2016 2/1/2016 3/1/2016 3/30/2016

1 21 31 49 62 79 92 99 112 123 128 147 154 169 183 184 215 218 245 276 307 336 365

4.9 6.1 7.7 10.7 13.4 16.8 19.2 20.5 19.3 18.6 18.3 17.6 16.5 14.2 12.8 12.7 8.8 8.4 7.8 7.0 6.3 5.6 4.9

40

Burbot thermal experience (°C) 4.5 5.7 6.9 9.2 11.5 14.5 15.3 15.7 18.7 18.0 17.6 14.7 12.9 8.9 9.1 9.1 8.3 8.3 7.6 6.8 6.0 5.3 4.5



2017

Table 10. Mean annual growth inputs for northern pikeminnow and estimated feeding rates (% Cmax) used in the bioenergetics simulations (starting on April 1, 2015 [simulation day 1], and ending March 30, 2016 [simulation day 365]) for different age-classes in Lake Kachess. Nt represents the abundance of each age class in a size-structured population of 1,000 predators >200 mm FL.

Final FL (mm)

Age 1-2

Initial FL (mm) 125

Age 2-3

Simulation

Nt

160

Initial weight (g) 20

Final weight (g) 41

Growth (g) 22

% Cmax 43.6%

160

194

41

72

31

40.8%

Age 3-4

236

194

225

72

112

40

39.4%

Age 4-5

181

225

254

112

161

49

38.3%

Age 5-6

138

254

281

161

217

57

36.7%

Age 6-7

106

281

307

217

281

64

35.5%

Age 7-8

81

307

331

281

351

70

33.6%

Age 8-9

62

331

353

351

419

69

32.4%

Age 9-10

47

353

374

419

516

97

32.9%

Age 10-11

36

374

393

516

620

104

32.1%

Age 11-12

28

393

412

620

730

110

31.4%

Age 12-13

21

412

429

730

845

115

28.3%

Age 13-14

16

429

445

845

964

119

27.8%

Age 14-15

12

445

460

964

1086

122

27.3%

Age 15-16

9

460

474

1086

1210

124

26.9%

Age 16-17

7

474

487

1210

1335

125

26.5%

Age 17-18

6

487

499

1335

1460

125

26.2%

Age 18-19

4

499

510

1460

1584

124

25.9%

Age 19-20

3

510

521

1584

1707

123

25.6%

Age 20-21

2

521

531

1707

1828

121

25.4%

Age 21-22

2

531

540

1828

1947

119

25.1%

Age 22-23

1

540

549

1947

2063

116

24.9%

41



2017

Table 11. Mean annual growth inputs for burbot and estimated feeding rates (% Cmax) used in the bioenergetics simulations (starting on April 1, 2015 [simulation day 1], and ending March 30, 2016 [simulation day 365]) for different age-classes in Lake Kachess. Nt represents the abundance of each age class in a sizestructured population of 1,000 predators >200 mm TL.

Simulation

Nt

Initial TL (mm)

Age 1-2

170

202

240

42

74

32

61.1%

Age 2-3

143

240

276

74

117

44

60.7%

Age 3-4

120

276

312

117

174

57

62.6%

Age 4-5

100

312

347

174

245

71

62.6%

Age 5-6

84

347

380

245

331

86

62.7%

Age 6-7

70

380

413

331

433

102

62.8%

Age 7-8

59

413

444

433

550

117

47.9%

Age 8-9

49

444

475

550

684

133

47.9%

Age 9-10

41

475

505

684

833

149

48.0%

Age 10-11

35

505

533

833

998

165

48.0%

Age 11-12

29

533

561

998

1179

181

48.1%

Age 12-13

24

561

588

1179

1375

196

48.1%

Age 13-14

20

588

615

1375

1585

210

48.1%

Age 14-15

17

615

640

1585

1809

224

48.2%

Age 15-16

14

640

665

1809

2047

238

48.2%

Age 16-17

12

665

689

2047

2298

250

49.0%

Age 17-18

10

689

712

2298

2560

263

49.0%

42

Final TL (mm)

Initial weight (g)

Final weight (g)

Growth (g)

% Cmax



2017

Population consumption (kg)

8000 7000

A

Daphnia Copepods Other Drought

6000 5000 4000 3000 2000 1000 0

Biomass (kg)

Apr 45000 40000 35000 30000 25000 20000 15000 10000 5000 0

May Jun

Jul

Aug Sep

Oct

Nov Dec

Jan

Feb

Mar

Daphnia (0-10 m) Daphnia (10-20 m) Copepods (0-10 m) Copepods (10-20 m)

B

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Production (kg)

60000 50000

C

40000 30000 20000 10000 0 1.0

C/P

0.8

D

Daphnia (0-20 m) Copepods (0-20 m)

0.6 0.4 0.2 0.0 Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Month

Figure 14. (A) Monthly population-level consumption demand (C) of all age-classes of kokanee assuming an annual recruitment of 365,000 fry (25 mm FL) on April 1st, an annual survival rate of 27%, spawning at age-3, and under the contemporary thermal regime (colored bars). Crosshatched bars represent the increase in consumption of all prey categories combined that we’d expect under the “drought scenario”, assuming observed growth remains the same. (B) Total monthly biomass of zooplankton in Kachess, and (C) the corresponding total monthly production (P) of each group of zooplankton in each depth-interval. (D) The ratio of population-level consumption demand by kokanee to available zooplankton production (C/P) estimated for each month during the growing season under the contemporary thermal regime in Kachess. These ratios were computed assuming kokanee have full access to surface waters during April-June, October and November, but are restricted to feeding within the metalimnion (10-20 m depths only) during peak thermal stratification in July-September. The dotted line represents our conservative definition of food supply (i.e., 50% of total biomass and production available each month).

43



2017

copepods, and other) only increased by 7-19% under simulated drought and extensive reservoir draw-down conditions in Kachess. Food supply, under our conservative definition, was sufficient to support this small increase in consumption demand during most of the growing season, except during mid-summer under the current stocking rate examined (Figure 14). Absolute feeding rate (in terms of numbers of prey) is largely dependent on prey density. The feeding rate of kokanee (# Daphnia eaten per min) increases linearly with prey density over an ecologically-relevant range of 0-30 Daphnia/L under both low and high light conditions (Koski and Johnson 2002). The density of Daphnia measured in Kachess, Keechelus, and Cle Elum were relatively low in the epilimnion and metalimnion during most of the growing season. Therefore, kokanee in these systems are feeding at the lower end of the functional response curve. For example, they are likely only able to consume 5-10 Daphnia per minute of foraging (375 mm FL during summer stratification were 40-55%. Under the “drought scenario”, feeding rates dropped by nearly half (range: 19-28% Cmax; Table 7), and annual consumption demand increased by 6-11% after increasing the average monthly thermal experience for bull trout by 2°C. This non-intuitive result was created by an increased consumption capacity of bull trout under higher thermal experience (Table 5). Thus, a smaller fraction of their now expanded maximum feeding rate under the higher temperatures could satisfy the observed growth rate. In other words, their scope for growth increased under the “drought scenario”, suggesting that small increases in thermal experience could enhance the growth and consumption of bull trout if sufficient prey were available. Given their low population size, the current standing stock biomass of pelagic fish prey estimated in Kachess should absorb any increase in consumption demand that might occur during periods of drought and more extensive reservoir draw-down, which will increase overlap and encounter rates between bull trout and kokanee. However, the consumption demand of burbot and northern pikeminnow on 44



2017

pelagic fish prey must be considered when gauging whether bull trout could become food limited under future water management regimes, or whether predation mortality is a significant factor limiting the production of kokanee in these systems. Consumption demand by northern pikeminnow and burbot.—The magnitude of predation by the more numerous northern pikeminnow and burbot on different prey varied considerably among months and between species of piscivore (Figure 15). Northern pikeminnow exhibited a strong temperature-dependent response in monthly consumption which peaked during the warm summer stratification period (Figure 15a). The highest predation on kokanee and other or unidentified salmonids occurred during June through October. Redside shiners and sculpins were the other major fish prey eaten, while a lesser degree of cannibalism and predation on burbot was also evident.

Figure 15. Estimated monthly consumption demand by a size-structured population of: A. 1,000 northern pikeminnow ≥200 mm FL, and B. 1,000 burbot ≥200 mm TL in Kachess Reservoir from bioenergetics model simulations.

Burbot exhibited little difference in total consumption among months, and the sizestructured unit population of 1,000 burbot consumed a considerably greater biomass of kokanee, other salmonids, and northern pikeminnow than did northern pikeminnow (Figure 15b). Measurable predation on kokanee and other salmonids spanned all months 45



2017

but appeared heaviest on kokanee during fall and winter. The higher proportions of other or unidentified salmonids and unidentified fish during the warmer months coincided with higher degrees of digestion. Thus, the majority of unidentified salmonids during these periods were likely kokanee, and the unidentified fish prey could reasonably be proportionally allocated to the northern pikeminnow and kokanee categories of prey. Crayfish also contributed consistently to the energy budget of burbot throughout the year, particularly during fall through spring.

Figure 16. Annual consumption demand (kg) on kokanee and other pelagic fish prey from a sizestructured population unit of 100 bull trout, 1,000 northern pikeminnow, and 1,000 burbot in relation to the available biomass (kg) of kokanee and other pelagic fish prey estimated from nocturnal hydroacoustics in Kachess Reservoir during mid-to-late August 2014. Bars for kokanee prey represent the peak monthly biomass (September) of kokanee available during late summer predicted by the population model presented in Figure 12 under the two annual survival rates (S) examined. The different estimates for kokanee biomass are meant to provide a minimum and maximum expectation for the biomass of kokanee available during late summer (i.e., what remained after a few months of predation from piscivores over the primary growing season) for comparison to the hydroacoustics based estimate for the biomass of all pelagic prey fish (kokanee, pygmy whitefish, redside shiners, potentially others) at large during the same period.

The relative predation impact of bull trout, northern pikeminnow, and burbot on common prey resources, especially kokanee and other pelagic fish prey, is largely determined by the abundance of each species of predator and the consumption imposed by a unit size-structured population. Based on catch rates in standardized gill net sets, the relative abundance of northern pikeminnow and burbot was 65-fold and 9-fold greater than that of bull trout, respectively. Due to the scarcity of bull trout and their low catch relative to the other predators, we used a unit size-structured population of 100 bull trout for comparison to size-structured populations of 1,000 for burbot and northern 46



2017

pikeminnow as a way to partially account for the disparity in abundance among piscivore species. We estimated that the unit population of bull trout consumed 186 kg of kokanee or other pelagic fish prey a year compared to 230 kg by 1,000 northern pikeminnow and 662 kg by 1,000 burbot (Figure 16). So, although the per capita predation impact by bull trout was higher, their “population-level” impact was considerably lower than impacts by the other piscivores. Under the apparent current relative abundances of these predators, burbot would eat approximately 3x more kokanee than bull trout and northern pikeminnow would eat approximately 8x more. So, collectively, the other piscivores impose 11x more predation demand on kokanee/other pelagic fish prey than do bull trout. Conclusions 1. Based on the bioenergetics simulations, stocking more kokanee than the 365,000 fry examined here (represents current stocking rates) could lead to a feeding and growth bottleneck during mid-summer for kokanee. Even though food supply exceeds consumption demand for most of the growing season, the biomass of Daphnia is spread thinly, such that low densities limit encounter and feeding rates of kokanee. This, combined with the cold thermal experience, exclusion from the epilimnion during peak thermal stratification, and behavioral thermoregulation/predator avoidance are all contributing to the low growth and consumption by kokanee. 2. The potential competition between kokanee and the other major planktivores is likely minimized due to thermal segregation during the growing season. Additional consumption demand for Daphnia by redside shiners during the summer likely has minimal impact on the food available to kokanee, because redside shiners feed in the warmer epi-pelagic zone while it is inaccessible to kokanee during peak stratification. 3. More refined estimates of mortality rate for kokanee in Kachess and Keechelus, and a better understanding of natural recruitment would better inform the carrying capacity of these systems for kokanee, and potentially reintroduced sockeye salmon. Future analyses could provide expectations for the number and size of sockeye salmon smolts that might be produced within the current physical and ecological constraints of each reservoir. Note that if the kokanee population converted to 100% anadromous fry and age-1 smolts, the older age classes of kokanee which currently consume at least 10-fold more zooplankton biomass, would no longer impose that consumption demand and would increase the carrying capacity for juvenile sockeye by a proportional amount (e.g., Hansen et al. 2016). 4. Feeding rates of bull trout estimated from the bioenergetics model suggested that bull trout are not limited by foraging opportunities in Kachess under contemporary conditions. Our nocturnal hydroacoustics-based estimate of the pelagic forage base in Kachess during August—an estimate of what was present after a few months of predation from piscivores during the primary growing season and when temperature-dependent consumption of northern pikeminnow (the most abundant piscivore) was greatest—could support a higher population of adult bull trout, or any expected increase in consumption during periods of drought or increased reservoir draw-down from the current population. 47



2017

5. Annual stockings of kokanee are an important source of prey for all piscivores in Kachess and should continue. Northern pikeminnow and burbot collectively could eat 11fold more kokanee biomass than bull trout each year due to their much higher abundance. The energy budgets of these two piscivores are also supported by considerable fractions of alternative benthic-littoral and nearshore epi-pelagic fishes and benthic invertebrates. Consequently, water operations that limit the productivity of these alternative prey species would likely increase consumption demand on and potential competition for kokanee and other prey shared by adult bull trout, and reduce the suite of potential feeding opportunities available for smaller, younger age-classes of bull trout entering the reservoir. Because the estimate for the biomass of kokanee available during late summer from the population model assuming S = 27% was low relative to the amount of kokanee consumed by unit populations of 1,000 northern pikeminnow and burbot, it is possible that kokanee may not be able to absorb much additional predation mortality at current stocking rates. 6. The estimated biomass of kokanee at large during late summer from the population model was well below the nocturnal hydroacoustics based estimate for the biomass of all pelagic prey fish available under each annual survival rate examined. This suggests that considerable numbers of fish other than kokanee (e.g., redside shiners, whitefish, and suckers) that (1) could occupy more nearshore or benthic habitats during daylight, and (2) were not detected by the limited midwater trawling effort, occupy offshore or slopezone habitats at night and were sampled by the hydroacoustics system. Therefore, when interpreting the hydroacoustics based estimate of “total pelagic prey fish biomass” available to piscivores, it is important to note that (1) it includes an unknown fraction of species that would otherwise be considered benthic-littoral/nearshore fish, and (2) is not strictly in addition to what is available to piscivores nearshore. 7. Based on stomach content analysis, kokanee were most accessible to the largest, most piscivorous northern pikeminnow and burbot during late summer and fall, a period that coincided with kokanee occupation of nearshore habitat prior to spawning. These piscivores consumed larger age-2 and age-3 kokanee at that time, which supported the notion that both predators consume pre-spawning kokanee.

48



2017

4. SUMMARY AND CONSIDERATIONS FOR BULL TROUT AND MANAGEMENT OF WATER STORAGE Previous discussions with agency personnel determined that the effects of the KKC on food web interactions and bull trout in Keechelus (that add to the effects of current water operations) should be negligible, so we focus discussion on Kachess and the KDRPP for the remainder of this report. Our food web analysis of Kachess yielded a number of key findings that inform and have important implications for (1) potential limitations to bull trout productivity under current water management regimes, and (2) the response of current food web interactions to pumping. The following paragraphs discuss key findings within the context of potential limiting factors for bull trout and management of water storage in Kachess. Extensive reservoir draw-down can compress habitat for fish. One important question is whether increased draw-down by the KDRPP could lead to unsustainable predator-prey interactions (i.e., prey important to bull trout become limited by predation from the other piscivores) in Kachess by concentrating predators with prey. To address this question, we simulated the effect of draw-down on the diel- and depth-specific density of prey observed from hydroacoustics (Figure 17). We based this analysis on the density and distribution of prey-sized targets (20-300 mm FL) observed during daylight, dusk, and night in Big Kachess in August 2014 when Kachess was 97-98% full. Key assumptions included: (1) thermal structure (i.e., warm epilimnion in upper 10 m of water column) remains intact with drawdown; (2) the depth-distribution of pelagic prey fish in relation to the warm epilimnion also remains the same; and (3) at 2,225 ft surface elevation, fish in Big Kachess lose connectivity to Little Kachess (Figure 17). To calculate prey density, we only considered depths within and below the thermocline that contained the majority of fish targets (15-30 m for daylight, 15-35 m for dusk, and 15-45 m for night; Figure 9). Overall, the effect of draw-down on prey fish density was negligible within the proposed new region of operation for KDRPP (Figure 17) given the deep and steep-sided nature of Kachess. Prey densities at depths within or below the thermocline during peak thermal stratification did not appear to change enough to where it would cause a measurable increase in predation mortality on kokanee/other pelagic fish prey. The drop in the total capacity curve shown for Big Kachess at 2,225 ft surface elevation is because we assumed fish lose connectivity to habitat in Little Kachess at that point. During peak thermal stratification in August, fish may lose access to Little Kachess at higher surface elevations if they actively avoid warm surface temperatures. It is important to note that this analysis was only concerned with predator-prey interactions in the reservoir, and did not consider how increased drawdown would influence connectivity between the reservoir and spawning tributaries for bull trout during key migration periods, and potential downstream impacts. Additionally, at the current proposed elevation for the pump intake (2,112 ft), water managers would not be able to utilize the entire 200,000 ac-ft of what is currently dead storage without pumping water directly from the thermocline and epilimnion, which has important implications for reservoir productivity, thermal structure, and food web interactions.

49



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Figure 17. Diel and depth-specific pelagic prey fish density estimated from hydroacoustics in August 2014 and total storage capacity as a function of surface elevation for Kachess Reservoir in relation to the existing outlet structure and the new proposed pump intake for the KDRPP. Holding all else equal, the expected surface elevation and corresponding density of prey during August of a typical drought year when the KDRPP would be in operation is also indicated on the graph. Prey density calculations are only meant to provide a conceptual understanding of how the extent of habitat compression and potential for higher predation mortality is changing with differing levels of reservoir drawdown. Reservoir capacity within different depth intervals of the reservoir vary: from full pool (2,263 ft surface elevation) to the existing outlet (2,192 ft elevation) is 239,000 ac-ft; capacity of Big Kachess from the existing outlet to the proposed pump intake (elevation of 2,112 ft) is 200,000 ac-ft; remaining capacity in Big Kachess below the intake for KDRPP is 386,000 ac-ft.

The drawdown analysis above assumed the contemporary thermal structure of Kachess would remain intact during and after pumping. Seasonal changes in thermal structure influenced the productivity and temporal-spatial distribution patterns of zooplankton and fish in meaningful ways. First, warm surface temperatures during summer greatly increased the production of Daphnia and other zooplankton important for supporting kokanee, other coldwater fish prey, and warm-water fish (e.g., redside shiners) that feed in the epi-pelagic zone and support the feeding and growth of piscivores yearround. Next, bull trout overlapped with the most abundant piscivore, northern pikeminnow, during the cooler spring period prior to peak thermal stratification, whereas warm surface temperatures during summer (when temperature-dependent consumption by northern pikeminnow was greatest) reduced, but did not eliminate, spatial overlap between these two predators. Bull trout probably overlap with burbot throughout the year. Unlike northern pikeminnow, burbot showed little temperature-dependence in consumption demand indicating that they are effective piscivores over a broad range of thermal conditions (even 50



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at cold temperatures). Additionally, for an equally sized age-structured unit population of 1,000 fish, burbot ate a much greater biomass of prey shared by bull trout than northern pikeminnow. Even though increased drawdown should not concentrate predators and prey, pumping scenarios that significantly degrade thermal stratification and cool surface water temperatures through the growing season could (1) reduce the productivity of zooplankton that supports intermediate trophic levels, (2) limit productivity of other prey fish and invertebrates in the benthic-littoral zone, (3) degrade the partial thermal refuge from northern pikeminnow that forms during summer, (4) generate conditions that start favoring burbot, a more effective piscivore on prey shared by bull trout than northern pikeminnow, and (5) place more burden on shared prey resources. The piscivore community in Kachess is supported by considerable fractions of benthic-littoral fishes and invertebrates and nearshore epi-pelagic fishes. These prey help reduce predation pressure on coldwater pelagic prey like kokanee that is important for adult bull trout while also providing alternative feeding opportunities for adult bull trout, burbot and northern pikeminnow. These prey could also provide a diverse suite of feeding opportunities for juvenile bull trout entering the reservoir. The productivity of these prey resources along shorelines and shallow shelf habitat is sensitive to fluctuations in reservoir surface elevation, particularly during the spring spawning and incubation period (for small bodied fish like redside shiners) and over the warm summer months. As indicated by the stable isotope data collected from fish and invertebrates in Kachess and in Keechelus, current water operations in Kachess (drawdown delayed until late summer or early fall in a normal water year) are less limiting to benthic-littoral production when compared to Keechelus which experiences relatively rapid drawdown at the start of the growing season. It follows that pumping scenarios/water operations that lower the surface elevation of Kachess more rapidly and sooner in the irrigation season (and more consistently year-to-year), or severely delay reservoir refilling, could also start limiting benthic-littoral production and place more burden on pelagic energy pathways. Our food web analysis of Kachess spanned three years, which included a drought year and two average water years. From a feeding and growth perspective, data and modeling simulations suggested that the reservoir has the capacity to support a larger population of bull trout under current management, which raises the question as to why more bull trout were not observed in the reservoir and redd counts in spawning tributaries were low. There are several possibilities: (1) competitive interactions with the more abundant and established burbot and northern pikeminnow could be more severe than was detected by our analysis, making it difficult for the low numbers of existing bull trout to increase in abundance, (2) predation by burbot and northern pikeminnow on juvenile bull trout could be limiting the survival of bull trout to adulthood (this could not be evaluated in our study due to a lack of encounters with smaller bull trout), (3) spawning or rearing habitat in spawning tributaries could be limiting, particularly during low water years, or access to tributaries from the reservoir by adult fish could be compromised (e.g., as in 2015), or (4) a combination of these factors. Because of these additional uncertainties and potential limiting factors, the importance of reservoir productivity and maintaining a diverse suite of feeding opportunities for bull trout in Kachess should not be overlooked when developing new water management regimes involving the KDRPP. 51



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REFERENCES Abbreviations: USBOR: United States Bureau of Reclamation USFWS: United States Fish and Wildlife Service WSDOE: Washington State Department of Ecology Baldwin, C.M., D.A. Beauchamp, and J.J. Van Tassell. 2000. Bioenergetic assessment of temporal food supply and consumption demand by salmonids in the Strawberry Reservoir food web. Transactions of the American Fisheries Society 129:429-450. Baldwin, C. M., J. G. McLellan, M.C. Polacek, and K. Underwood. 2003. Walleye predation on hatchery releases of kokanees and rainbow trout in Lake Roosevelt, Washington. North American Journal of Fisheries Management 23:660-676. Beauchamp, D.A., D.J. Stewart, and G.L. Thomas. 1989. Corroboration of a bioenergetics model for sockeye salmon. Transactions of the American Fisheries Society 118:597-607. Beauchamp, D.A., M.G. LaRiviere, and G.L. Thomas. 1995. Evaluation of competition and predation as limits to the production of juvenile sockeye salmon in Lake Ozette. North American Journal of Fisheries Management 15:121-135. Beauchamp, D.A., C. Luecke, W.A. Wurtsbaugh, H.G. Gross, P.E. Budy, S. Spaulding et al. 1997. Hydroacoustic assessment of abundance and diel distribution of sockeye salmon and kokanee in the Sawtooth Valley Lakes, Idaho. North American Journal of Fisheries Management 17:253-267. Beauchamp, D.A. and J.J. Van Tassell. 2001. Modeling seasonal trophic interactions of adfluvial bull trout in Lake Billy Chinook, Oregon. Transactions of the American Fisheries Society 130: 204-216. Beauchamp, D.A., C.J. Sergeant, M.M. Mazur, J.M. Scheuerell, D.E. Schindler, M.D. Scheuerell, K.L. Fresh, D.E. Seiler, and T.P. Quinn. 2004. Temporal-spatial dynamics of early feeding demand and food supply of sockeye salmon fry in Lake Washington. Transactions of the American Fisheries Society 133:10141032. Beauchamp, D.A., D. Wahl, and B.M. Johnson. 2007. Predator-Prey Interactions. Pages 765-842 in C.S. Guy and M.J. Brown, editors. Analysis and interpretation of freshwater fisheries data. American Fisheries Society, Bethesda, Maryland. Beauchamp, D.A., and M.F. Shepard. 2008. Evaluation of factors affecting kokanee production in Lake Billy Chinook. Final Report to Portland General Electric, Portland, OR. 36 pages. 52



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Beauchamp, D. A. 2009. Bioenergetic ontogeny: linking climate and mass-specific feeding to life-cycle growth and survival of salmon. Pages 53–71 in C. C. Krueger and C. E. Zimmerman, editors. Pacific Salmon: ecology and management of western Alaska’s populations. American Fisheries Society, Symposium 70, Bethesda, Maryland. Beauchamp, D.A., D. Parrish, and R. Whaley. 2009. Salmonids/coldwater species in large standing waters. Chapter 7. Pages 97-117 In S. Bonar, D. Willis, and W. Hubert, editors. Standard Sampling Methods for North American Freshwater Fishes. American Fisheries Society. Bethesda, Maryland. Beauchamp, D.A., A. McCoy, and A.G. Hansen. 2014. Quantifying Pelagic Food Web Interactions in Lake Tahoe: A Road Map for Re-Introduction of Lahontan Cutthroat Trout. Annual Report to U.S. Fish and Wildlife Service. Reno, NV. 56 pages. Bieber, A. J. 2005. Variability in juvenile Chinook foraging and growth potential in Oregon estuaries: implications for habitat restoration. Master's Thesis. University of Washington, Seattle, Washington. Bjornn, T. C. 1961. Harvest, age structure, and growth of gamefish populations from Priest to Upper Priest Lakes. Transactions of the American Fisheries Society 90:27–31. Bryan, S. D., C. A. Soupir, W. G. Duffy, and C. E. Freiburger. 1996. Caloric densities of three predatory fishes and their prey in Lake Oahe, South Dakota. Journal of Freshwater Ecology 11:153–161. Cabana, G. and J.B. Rasmussen. 1996. Comparison of aquatic food chains using nitrogen isotopes. Proceedings of the National Academy of Sciences, USA 93:10844-10847. Clarke, L.R., D.T Vidergar, and D.H. Bennett. 2005. Stable isotopes and gut content show diet overlap among native and introduced piscivores in a large oligotrophic lake. Ecology of Freshwater Fish 14:267-277. David, A. 2014. The effects of wetland loss and restoration on the foraging performance and growth potential of juvenile Chinook salmon in Pacific Northwest estuaries. Master’s Thesis. University of Washington, Seattle, Washington. Edmondson, W.T., and A.H. Litt. 1982. Daphnia in Lake Washington. Limnology and Oceanography 27: 272–293. Ellis, B.K., J.A. Stanford, D. Goodman, C.P. Stafford, D.L. Gustafson, D.A. Beauchamp, and five others. 2011. Long-term effects of a trophic cascade in a large lake ecosystem. Proceeding of the National Academy of Sciences 108: 1070-1075. 53



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Enzenhofer, H. J., and M. B. Hume. 1989. Simple closing midwater trawl for small boats. North American Journal of Fisheries Management 9:372-377. Fraley, J.J., and B.B. Shepard. 1989. Life history, ecology, and population status of migratory bull trout (Salvelinus confluentus) in the Flathead Lake and River system, Montana. Northwest Science 63:133–143. Gray, A. 2005. The Salmon River Estuary: Restoring Tidal Inundation and Tracking Ecosystem Response. Ph.D. dissertation. University of Washington School Aquatic and Fishery Sciences, Seattle, Washington. Hansel H.C, S.D. Duke, P.T. Lofy, and G.A. Gray. 1988. Use of diagnostic bones to identify and estimate original lengths of ingested prey fishes. Transactions of the American Fisheries Society 117:55-62. Hansen, A.G., D.A. Beauchamp, and C.M. Baldwin. 2013a. Environmental constraints on piscivory: insights from linking ultrasonic telemetry to a visual foraging model for cutthroat trout. Transactions of the American Fisheries Society 142:300-316. Hansen, A.G., J.R. Gardner, D.A. Beauchamp, R. Paradis, and T.P. Quinn. 2016. Restoration potential for sockeye salmon in the Elwha River, Washington after dam removal: rearing capacity of Lake Sutherland for landlocked and anadromous Oncorhynchus nerka. Transactions of the American Fisheries Society 145:1303-1317. Hansen, M. J., C. P. Madenjian, J. H. Selgeby, and T. E. Helser. 1997. Gillnet selectivity for Lake Trout (Salvelinus namaycush) in Lake Superior. Canadian Journal of Aquatic and Fisheries Science 54:2483–2490. Hanson, P.C., T.B. Johnson, D.E. Schindler, and J.F. Kitchell. 1997. Fish bioenergetics 3.0. University of Wisconsin, Sea Grant Institute, Technical Report WIS-CU-T-97001, Madison. Hardiman, J.M., B.M. Johnson, and P.J. Martinez. 2004. Do predators influence the distribution of age-o kokanee in a Colorado Reservoir? Transactions of the American Fisheries Society 133:1366-1378. Hecky, R.E., and R.H. Hesslein. 1995. Contributions of benthic algae to lake food webs as revealed by stable isotope analysis. Journal of the North American Benthological Society 14:631-653. Hiebert, S. 1999. Limnological surveys of five reservoir in the Upper Yakima River Basin, Washington. USBR Draft Progress Report. 32 pages. Hyatt, M.H., and W.A. Hubert. 2000. Proposed standard-weight (W s) equations for 54



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kokanee, golden trout and bull trout. Journal of Freshwater Ecology 15:559-563. James, P.W. 2002. Population status and life history characteristics of bull trout in the Yakima River Basin. Final report to USBOR. Department of Biological Sciences, Central Washington University, Ellensburg, WA. 87 pages. Jeppson, P.W., and W.S. Platts. 1959. Ecology and control of the Columbia River squawfish in northern Idaho lakes. Transactions of the American Fisheries Society 88:197–203. Johnson, B.M., and P.J. Martinez. 2000. Trophic economies of lake trout management in reservoirs of differing productivity. North American Journal of Fisheries Management 20:127-143. Johnson, B.M., and P.J. Martinez. 2012. Hydroclimate mediates effects of a keystone species in a coldwater reservoir. Lake and Reservoir Management 28:70-83. Johnson, T.B, D.M. Mason, S.T. Schram, J.F. Kitchell. 1999. Ontogenetic and Seasonal Patterns in the Energy Content of Piscivorous Fishes in Lake Superior. Journal of Great Lakes Research 25 (2): 275-281. Koski, M.L., and B.M. Johnson. 2002. Functional response of kokanee salmon (Oncorhynchus nerka) to Daphnia at different light levels. Canadian Journal of Fisheries and Aquatic Sciences 59:707-716. Kuns, M.M., and W.G. Sprules. 2000. Zooplankton production in Lake Ontario: a multistrata approach. Canadian Journal of Fisheries and Aquatic Sciences 57:2240-2247. Leathe, S.A., and P.J. Graham. 1981. Flathead Lake fish food habits study final report. Environmental Protection Agency, Montana Fish, Wildlife, and Parks contract number R0008224–01–4, Denver, Colorado. Luecke, C., and D. Brandt. 1993. Estimating the energy density of daphnid prey for use with rainbow trout bioenergetics models. Transactions of the American Fisheries Society 122:386-389. Lieberman, D.M., and S.J. Gabowski. 2007. Physical, chemical, and biological characteristics of Cle Elum and Bumping Lakes in the upper Yakima River basin, Storage Dam Fish Passage study, Yakima Project, Washington, Technical Series No. PN-YDFP-005, Bureau of Reclamation, Boise, Idaho, March 2007. 83 pages. Lowery, E.D., and D.A. Beauchamp. 2010. Baseline Food Web assessment of the Upper Clackamas River Basin prior to reintroduction of bull trout. Final Report to the Upper Clackamas Bull Trout Working Group. Washington Cooperative Fish and Wildlife Research Unit Report #WACFWRU-010-02. 55



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Lowery, E.D., and D.A. Beauchamp. 2015. Trophic ontogeny of fluvial Bull Trout and seasonal predation on Pacific Salmon in a riverine food web. Transactions of the American Fisheries Society 144:724-741. Love, R.H. 1977. Target strength of an individual fish from any aspect. Journal of the Acoustical Society of America. 62:1397-1403. Martinez, P.J., and W.J. Wiltzius. 1995. Some factors affecting a hatchery-sustained kokanee population in a fluctuating Colorado reservoir. North American Journal of Fisheries Management 15:220-228. Matter, M.A., L.A. Garcia, D.G. Fontane, and B. Bledsoe. 2010. Characterizing hydroclimate variability in tributaries of the Upper Colorado River Basin-WY19112001. Journal of Hydrology 380:260-276. Mazur, M. 2004. Linking visual foraging with temporal prey distribution to model trophic interactions in Lake Washington. Doctoral dissertation. University of Washington School of Aquatic and Fisheries Sciences, Seattle. McGurk, M.D. 1999. Size dependence of natural mortality rate of sockeye salmon and kokanee in freshwater. North American Journal of Fisheries Management 19:376-396. McIntyre, J.K., D.A. Beauchamp, M.M. Mazur, and N.C. Overman. 2006. Ontogenetic trophic interactions and bentho-pelagic coupling in Lake Washington: evidence from stable isotopes and diet analysis. Transactions of the American Fisheries Society 135:1312-1328. Mesa, M.G., L.K. Weiland, H.E. Christiansen, S.T. Sauter, and D.A. Beauchamp. 2013. Development and evaluation of a bioenergetics model for bull trout. Transactions of the American Fisheries Society 142:41-49. Mongillo, P.E., and L. Faulconer. 1982. Final report: Yakima fisheries enhancement study phase II. Washington Department of Game Report. 130 pages. Petersen, J.H., and Ward, D.L. 1999. Development and corroboration of a bioenergetics model for northern pikeminnow feeding on juvenile salmonids in the Columbia River. Transactions of the American Fisheries Society 128(5): 784-801. Polacek, M. 2014. Food web structure of Kachess and Keechelus Reservoirs: factors limiting bull trout production. Project Status Report. Washington Department of Fish and Wildlife. 14 pages. Riess, K.Y., J. Thomas, E. Anderson, and J. Cummins. 2012. Yakima bull trout action plan. Final Report. 424 pages.

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Rudstam, L.G., P.E. Peppard, T.W. Fratt, R.E. Bruesewitz, D.W. Coble, F.A. Copes, and J.F. Kitchell. 1995. Prey Consumption by the burbot (Lota lota) population in Green Bay, Lake Michigan, based on a bioenergetics model. Canadian Journal of Fisheries and Aquatic Sciences 52: 1074-1082. Saito, L., B.M. Johnson, J. Bartholow, and R.B. Hanna. 2001. Assessing ecosystem effects of reservoir operations using food-web energy transfer and water quality models. Ecosystems 4:105-125. Scheuerell, J.M., D.E. Schindler, M.D. Scheuerell, K.L. Fresh, T.H. Sibley, A.J. Litt, and J.H. Shepherd. 2005. Temporal dynamics in foraging behavior of a pelagic predator. Canadian Journal of Fisheries and Aquatic Sciences 62:2494-2501. Schoen, E.R., and D.A. Beauchamp. 2010. Predation impacts of lake trout and Chinook salmon in Lake Chelan, Washington: Implications for prey species and fisheries management. Final Report to Chelan Public Utility District and Lake Chelan Fisheries Forum. Report # WACFWRU-010-01. 84 pages. Shuter, B.J., and K.K. Ing. 1997. Factors affecting the production of zooplankton in lakes. Canadian Journal of Fisheries and Aquatic Sciences 54:359-377. Sorel, M.H., A.G. Hansen, K.A. Connelly, A.C. Wilson, E.D. Lowery, and D.A. Beauchamp. 2016a. Predation by Northern Pikeminnow and tiger muskellunge on juvenile salmonids in a high–head reservoir: implications for anadromous fish reintroductions. Transactions of the American Fisheries Society. 145:521-536. Sorel, M.H., A.G. Hansen, and D.A. Beauchamp. 2016b. Prey supply and consumption demand by resident and reintroduced anadromous salmonids in three reservoirs on the North Fork Lewis River, Washington. Transactions of the American Fisheries Society 145:1331-1347. Stockwell, J.D., K.L. Bonfantine, and B.M. Johnson. 1999. Kokanee foraging: a Daphnia in the stomach is worth two in the lake. Transactions of the American Fisheries Society 128:169–174. Thiesfeld, S. L., J. C. Kern, A. R. Dale, M. W. Chilcote, and M. A. Buckman. 1999. Lake Billy Chinook sockeye salmon and kokanee research study: 1996–1998 contract completion report. Pelton Round Butte Hydroelectric Project, FERC Number 2030. Research and Development Division, Oregon Department of Fish and Wildlife, Portland. April 1999. 153 pages. USBOR and WSDOE. 2012. Yakima River Basin Integrated Water Resource Management Plan. Final Programmatic Environmental Impact Statement. Benton, Kittitas, Klickitat, and Yakima Counties. USBOR and WSDOE. 2015. Kachess Drought Relief Pumping Plant and Keechelus 57



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Reservoir-to-Kachess Reservoir Conveyance. DRAFT Environmental Impact Statement. Kittitas and Yakima Counties, Washington. 842 pages. USFWS. 1998. Endangered and threatened wildlife and plants: determination of threatened status for the Klamath River and Columbia River distinct population segments of bull trout. 50 CFR Part 17. USFWS, Dept. of Interior. 1018-AB94. Vander Zanden, M.J., S. Chandra, B.C. Allen, J.E. Reuter, and C.R. Goldman. 2003. Historical food web structure and restoration of native aquatic communities in the Lake Tahoe (California-Nevada) Basin. Ecosystems 6:274-288. WSDOE. 2009. Final Environmental Impact Statement. Yakima River Basin Integrated Water Resource Management Alternative. Conducted as part of the Yakima River Basin Water Storage Feasibility Study. Ecology publication #09-12-009.

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APPENDIX A Table A1. Total monthly Daphnia biomass, production (mean and one standard deviation), and corresponding kokanee population-level consumption demand (assuming an annual survival rate of S = 27%) to total production of zooplankton ratios (C:P) calculated using mean monthly zooplankton densities measured 2014-2016 in Lake Kachess. C:P values of >0.5 indicate months in which kokanee consumption exceeded 50% of production, our conservative definition of food supply. Values for C:P in parentheses are from simulations using the hydroacoustics based estimate of S = 48%, and is for comparison only. Values in bold indicate the months when kokanee were excluded from feeding in the epilimnion due to warm temperatures. Total biomass (kg) Month

Total Production (kg)

N

C:P 0-10 m

10-20 m

0-10 m

10-20 m

Daphnia Apr May Jun Jul Aug Sep Oct Nov

1 2 2 3 3 3 3 2

1,955 2,946 ± 1,972 13,066 ± 2,289 14,610 ± 14,530 15,199 ± 8,733 16,821 ± 10,154 17,786 ± 2,911 15,166 ± 6,014

221 314 ± 132 5,972 ± 4,097 15,099 ± 5,784 8,889 ± 7,040 5,365 ± 4,548 3,328 ± 3,932 5,053 ± 6,364

3,093 4,743 ± 3,027 32,178 ± 394 48,134 ± 43,468 51,070 ± 23,489 46,735 ± 33,494 33,363 ± 8,698 22,419 ± 3,250

321 367 ± 165 7,953 ± 5,751 22,192 ± 8,627 13,581 ± 11,229 6,863 ± 6,040 3,957 ± 4,789 5,863 ± 6,765

0.03 (0.13) 0.27 (0.93) 0.10 (0.39) 0.25 (0.99) 0.48 (1.74) 0.30 (0.90) 0.05 (0.14) 0.03 (0.09)

Copepods Apr May Jun Jul Aug Sep Oct Nov

1 2 2 3 3 3 3 2

19,270 18,974 ± 13,732 5,763 ± 3,507 4,245 ± 4,115 6,803 ± 4,791 7,462 ± 2,194 9,774 ± 2,712 12,443 ± 2,493

3,867 1,101 ± 687 3,597 ± 2,938 5,265 ± 4,689 9,783 ± 11,845 3,512 ± 2,443 3,384 ± 4,193 5,710 ± 7,696

6,002 6,485 ± 4,469 3,066 ± 1,297 3,382 ± 3,201 6,105 ± 5,398 4,602 ± 2,438 4,041 ± 1,675 3,839 ± 142

1,089 261 ± 171 999 ± 853 1,615 ± 1,428 3,292 ± 4,260 906 ± 649 825 ± 1,041 1,314 ± 1,708

0.32 (1.08) 0.22 (0.76) 0.17 (0.66) 0.04 (0.14) 0.02 (0.07) 0.02 (0.07) 0.00 (0.01) 0.13 (0.43)

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Table A2. Monthly (1st of each month) diet proportions used to model the consumption demand of each age-class of northern pikeminnow in Lake Kachess with a bioenergetics model. Diet proportions were linearly interpolated between the dates and simulation days listed here. Dates in bold are when diet proportions were empirically measured in Kachess during 2014-2016. Ageclass

Sim. day

1-3 1-3 1-3 1-3 1-3 1-3 1-3 1-3 1-3 1-3 1-3 1-3 1-3 1-3 1-3 1-3 4-6 4-6 4-6 4-6 4-6 4-6 4-6 4-6 4-6 4-6 4-6 4-6 4-6 4-6 4-6 4-6

1 42 62 92 123 131 154 165 184 211 215 245 276 307 336 365 1 42 62 92 123 131 154 165 184 211 215 245 276 307 336 365

60

Kokanee

Other unknown salmonid

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.022 0.028 0.021 0.012 0.002 0.000 0.000 0.000 0.000 0.000 0.001 0.005 0.009 0.013 0.018 0.022

0.035 0.042 0.032 0.018 0.004 0.000 0.000 0.000 0.003 0.008 0.009 0.014 0.019 0.024 0.029 0.034 0.164 0.178 0.138 0.078 0.016 0.000 0.166 0.245 0.190 0.111 0.112 0.123 0.133 0.144 0.154 0.163

Cottid

Northern pikeminnow

Redside shiner

0.000 0.000 0.016 0.040 0.064 0.070 0.023 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.025 0.031 0.049 0.077 0.105 0.112 0.036 0.000 0.000 0.000 0.001 0.005 0.010 0.015 0.020 0.025

0.000 0.000 0.019 0.047 0.076 0.083 0.027 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.022 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.043 0.104 0.102 0.086 0.070 0.053 0.038 0.022

0.038 0.000 0.000 0.000 0.000 0.000 0.152 0.224 0.206 0.181 0.178 0.150 0.121 0.093 0.066 0.039 0.023 0.000 0.022 0.056 0.091 0.100 0.201 0.250 0.193 0.111 0.109 0.092 0.074 0.057 0.040 0.024

Burbot

Otherunknown fish

Crayfish

Insect

Other invertebrates

0.000 0.000 0.019 0.046 0.075 0.082 0.027 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.027 0.000 0.019 0.047 0.076 0.084 0.027 0.000 0.053 0.129 0.127 0.107 0.086 0.066 0.047 0.028

0.008 0.010 0.020 0.035 0.050 0.054 0.017 0.000 0.001 0.002 0.002 0.003 0.004 0.006 0.007 0.008 0.029 0.022 0.020 0.018 0.015 0.015 0.005 0.000 0.024 0.058 0.057 0.051 0.046 0.040 0.035 0.030

0.000 0.000 0.008 0.020 0.032 0.036 0.012 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.080 0.201 0.325 0.357 0.116 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.895 0.942 0.863 0.745 0.623 0.592 0.642 0.667 0.688 0.719 0.723 0.758 0.793 0.828 0.861 0.894 0.687 0.742 0.603 0.395 0.180 0.125 0.359 0.472 0.476 0.482 0.487 0.527 0.568 0.609 0.648 0.686

0.024 0.007 0.024 0.049 0.076 0.082 0.101 0.109 0.101 0.090 0.088 0.076 0.062 0.049 0.037 0.025 0.001 0.000 0.047 0.116 0.189 0.207 0.090 0.033 0.021 0.004 0.004 0.004 0.003 0.002 0.002 0.001



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Table A2continued. Kokanee


Cottid

Northern pikeminnow

Redside shiner

Burbot

Otherunknown fish

Crayfish

Insect

Other invertebrates

1

0.000

42

0.000

0.092

0.166

0.000

0.090

0.129

0.000

0.007

0.106

0.109

0.083

0.333

0.105

0.000

0.124

0.100

0.053

0.372

0.132

7-11

62

0.000

0.082

0.132

0.002

0.001

0.097

0.138

0.082

0.354

0.113

7-11 7-11

92

0.000

0.070

123

0.000

0.058

0.136

0.004

0.002

0.055

0.194

0.126

0.328

0.085

0.141

0.007

0.003

0.012

0.253

0.171

0.300

0.056

7-11

131

0.000

7-11

154

0.000

0.054

0.142

0.008

0.003

0.001

0.268

0.183

0.293

0.048

0.023

0.046

0.080

0.097

0.000

0.246

0.228

0.264

0.016

7-11

165

0.000

0.008

0.000

0.114

0.143

0.000

0.236

0.250

0.250

0.000

7-11 7-11

184

0.000

0.045

0.127

0.067

0.097

0.015

0.197

0.228

0.224

0.000

211

0.000

0.097

0.308

0.000

0.033

0.037

0.143

0.196

0.187

0.000

7-11

215

0.000

0.097

0.304

0.000

0.032

0.039

0.142

0.193

0.191

0.003

7-11

245

0.000

0.096

0.277

0.000

0.027

0.052

0.135

0.171

0.219

0.023

7-11

276

0.000

0.095

0.248

0.000

0.022

0.066

0.129

0.148

0.248

0.044

7-11

307

0.000

0.094

0.220

0.000

0.017

0.080

0.122

0.126

0.278

0.065

7-11

336

0.000

0.093

0.194

0.000

0.012

0.093

0.115

0.104

0.305

0.084

7-11

365

0.000

0.092

0.167

0.000

0.007

0.106

0.109

0.083

0.332

0.104

12-22

1

0.331

0.228

0.000

0.000

0.109

0.000

0.114

0.000

0.133

0.085

12-22

42

0.353

0.156

0.000

0.000

0.138

0.000

0.078

0.000

0.168

0.107

12-22

62

0.363

0.121

0.000

0.000

0.152

0.000

0.061

0.000

0.186

0.118

12-22

92

0.379

0.068

0.000

0.000

0.173

0.000

0.034

0.000

0.211

0.134

12-22

123

0.395

0.014

0.000

0.000

0.194

0.000

0.007

0.000

0.238

0.151

12-22

131

0.399

0.000

0.000

0.000

0.200

0.000

0.000

0.000

0.245

0.156

12-22

154

0.356

0.144

0.000

0.000

0.143

0.000

0.072

0.000

0.175

0.111

12-22

165

0.336

0.213

0.000

0.000

0.115

0.000

0.106

0.000

0.141

0.090

12-22

184

0.300

0.331

0.000

0.000

0.067

0.000

0.166

0.000

0.083

0.053

12-22

211

0.250

0.500

0.000

0.000

0.000

0.000

0.250

0.000

0.000

0.000

12-22

215

0.252

0.493

0.000

0.000

0.003

0.000

0.246

0.000

0.003

0.002

12-22

245

0.268

0.440

0.000

0.000

0.024

0.000

0.220

0.000

0.029

0.019

12-22

276

0.284

0.386

0.000

0.000

0.046

0.000

0.193

0.000

0.056

0.036

12-22

307

0.300

0.332

0.000

0.000

0.067

0.000

0.166

0.000

0.083

0.052

12-22

336

0.315

0.281

0.000

0.000

0.088

0.000

0.140

0.000

0.107

0.068

12-22

365

0.331

0.230

0.000

0.000

0.108

0.000

0.115

0.000

0.132

0.084

Ageclass

Sim. day

7-11 7-11

61



2017

Table A3. Monthly (1st of each month) diet proportions of burbot used to model the consumption demand of each age-class in Lake Kachess with a bioenergetics model. Diet proportions were linearly interpolated between the dates and simulation days listed here. Dates in bold are when diet proportions were empirically measured in Kachess during 2014-2016. Ageclass

Sim. day

1-6 1-6 1-6 1-6 1-6 1-6 1-6 1-6 1-6 1-6 1-6 1-6 1-6 1-6 1-6 1-6 7-18 7-18 7-18 7-18 7-18 7-18 7-18 7-18 7-18 7-18 7-18 7-18 7-18 7-18

1 31 40 62 92 123 131 154 163 184 215 245 276 307 336 365 1 31 62 92 123 129 154 184 211 215 245 276 307 336

7-18

365

62

Kokanee


0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.244 0.186 0.127 0.070 0.011 0.000 0.164 0.361 0.538 0.531 0.474 0.415 0.356 0.301

0.023 0.026 0.027 0.066 0.120 0.175 0.189 0.053 0.000 0.002 0.006 0.009 0.013 0.016 0.019 0.023 0.164 0.172 0.181 0.190 0.198 0.200 0.176 0.147 0.121 0.122 0.130 0.139 0.148 0.156

0.245

0.164

Cottid

Northern pikeminnow

Redside shiner

0.055 0.013 0.000 0.000 0.000 0.000 0.000 0.247 0.343 0.314 0.270 0.227 0.183 0.139 0.098 0.057 0.035 0.027 0.018 0.010 0.002 0.000 0.023 0.052 0.077 0.076 0.068 0.059 0.051 0.043

0.032 0.037 0.039 0.029 0.017 0.003 0.000 0.000 0.000 0.003 0.008 0.013 0.018 0.023 0.028 0.032 0.266 0.298 0.330 0.361 0.394 0.400 0.310 0.202 0.105 0.109 0.140 0.172 0.205 0.235

0.083 0.095 0.099 0.075 0.042 0.009 0.000 0.000 0.000 0.009 0.021 0.034 0.046 0.059 0.071 0.083 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.035

0.265

0.000

Burbot

Otherunknown fish

Crayfish

Insect

Other invertebrates

0.000 0.000 0.000 0.004 0.010 0.015 0.017 0.005 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.079 0.076 0.075 0.094 0.120 0.147 0.154 0.119 0.105 0.103 0.099 0.095 0.091 0.087 0.083 0.080 0.222 0.263 0.307 0.348 0.392 0.400 0.280 0.136 0.006 0.011 0.053 0.096 0.139 0.180

0.503 0.540 0.551 0.477 0.377 0.273 0.246 0.249 0.250 0.276 0.315 0.352 0.391 0.429 0.465 0.501 0.070 0.053 0.036 0.020 0.003 0.000 0.047 0.103 0.154 0.152 0.135 0.119 0.102 0.086

0.224 0.213 0.210 0.254 0.315 0.377 0.394 0.327 0.301 0.293 0.282 0.270 0.259 0.247 0.236 0.225 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.000 0.001 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000

0.220

0.070

0.000

0.000



2017

Table A4. Energy Density values (J/g wet weight) that were averaged to estimate composite prey categories or missing values for use in Table 9 for diet items in predator diets (northern pikeminnow, burbot, bull trout).

Prey category Insect Redside shiner Other/unknown fish

Other invertebrates

63

Prey categories averaged to get overall value

ED (J/g)

Reference

Terrestrial Insects Aquatic insects Largescale sucker Northern Pikeminnow

5000 3400 3641 6703

Lowery and Beauchamp (2010) Hansen et al (1997) Bryan et al (1996) Peterson and Ward (1999)

Cottid Salmonid Northern Pikeminnow Burbot Largescale sucker

4305 5200 6703 5125 3641

Mazur (2004) Lowery and Beauchamp (2010) Peterson and Ward (1999) Johnson et al (1999) Bryan et al (1996)

Worm Mysid Amphipod Ostracod Crustacean Gastropod/Mollusk

1980 3550 2970 3370 3370 3092

Authors’ estimate Gray (2005) David (2014) Bieber (2005) Bieber (2005) Authors’ estimate



2017

Figure A1. Surface elevation, inflow, and discharge for Keechelus Reservoir from 1998 to 2002. Data extracted from an unpublished report provided by USBOR.

64



2017

Figure A2. Surface elevation, inflow, and discharge for Kachess Reservoir from 1998 to 2002. Data extracted from an unpublished report provided by USBOR.

65



2017

Figure A3. Spring and summer diet composition of kokanee captured in either Kachess or Keechelus between summer 2014 and spring 2015. “Other” includes insects and rare cladocerans (Bosmina, Sididae and Leptodora).

66



2017

3500 FL >350 mm W = 0.0000002739FL3.6051667372 R² = 0.92

Weight (g)

3000 2500

FL 350 mm fork length (FL) and