the potential of passive stream restoration to improve stream habitat and minimize the impact of...

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The potential of passive stream restoration to improve stream habitat andminimize the impact of fish disease: a short-term assessmentAuthor(s): Eriek S. Hansen and Phaedra BudySource: Journal of the North American Benthological Society, 30(2):573-588. 2011.Published By: The Society for Freshwater ScienceDOI: http://dx.doi.org/10.1899/10-018.1URL: http://www.bioone.org/doi/full/10.1899/10-018.1

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The potential of passive stream restoration to improve streamhabitat and minimize the impact of fish disease:

a short-term assessment

Eriek S. Hansen1AND Phaedra Budy2

Department of Watershed Sciences, Utah State University, 5210 Old Main Hill, Logan, Utah, 84322-5210USA and Intermountain Center for River Rehabilitation and Restoration, US Geological Survey, Utah

Cooperative Fish and Wildlife Research Unit, 5210 Old Main Hill, Utah State University, Logan,Utah 84322-5210 USA

Abstract. We evaluated the potential of habitat restoration to improve stream and riparian habitat and tominimize the prevalence of whirling disease in a population of native cutthroat trout in northern Utah. Wefenced 67 ha of riparian habitat to exclude livestock and measured key response variables at impact andcontrol sites before and after the completion of the exclosure. Total N concentrations decreased in responseto the exclusion. Over this short time period (1–2 y postrestoration), the combination of natural variabilityand exclusion of livestock grazing appeared to alter the vegetation and riparian conditions throughincreased bank stability and decreased % cover of exotic plant species. The effect of the exclosure onwhirling disease was confounded by climatic variation. However, restoration appeared to reduce theprevalence of whirling disease during a nondrought year, but not during a drought year. Therefore, in theshort term, these beneficial effects of restoration on trout appeared to hinge on favorable climaticconditions. We expect the longer-term restoration response to be affected less than the short-term responseby climatic conditions. The results of our study indicate that passive stream restoration is an effectivemanagement approach for restoring stream habitat and has the potential to minimize interactive effects ofdisease and habitat degradation, especially when other options for disease management are not possible orpractical.

Key words: stream restoration, passive, in-stream habitat, synergistic effects, disease management,livestock exclusion, riparian vegetation, native fishes.

Aquatic ecosystems are increasingly threatened bychanges in land use and associated habitat degrada-tion. Interest in their restoration has grown consider-ably in the recent past, in part because of importantecological functions and services aquatic ecosystemsprovide (NRC 1992, Vitousek et al. 1997, Wilcove et al.1998). Many streams retain the potential to improverapidly from a degraded condition after restorationactivities because aquatic and riparian habitats arenaturally dynamic and frequently experience large-scale natural disturbances (e.g., floods; Kauffman etal. 1995, Moerke et al. 2004). Stream restoration oftenincorporates the goal of improving ecosystem func-

tion. In many cases, passive restoration (i.e., removalof the source of degradation to allow naturalprocesses to restore the system; Kauffman et al.1997) may be preferred over active techniques andmay be all that is necessary to restore stream function(Kauffman et al. 1997, Roper et al. 1997, Tullos et al.2009).

In ecosystems where natural function is impaired,the combination of habitat degradation and thespread and effect of pathogens has potentiallyunpredictable or synergistic consequences becausethe effects of habitat alteration can influence hosts,pathogens, or both (Barbour and Fish 1993, Wilson2000, Vilchis et al. 2005). This potential interactionbetween habitat degradation and disease could affectthe abundance, composition, and persistence of nativespecies, such as trout (Daszak et al. 2000, Deem et al.2001, Patz et al. 2004). For example, evidence isincreasing that effects of habitat alteration influence

1 Present address: Department of Zoology and Physiology,University of Wyoming, 1000 East University Ave., Laramie,Wyoming 82071 USA. E-mail: [email protected]

2 To whom correspondence should be addressed. E-mail:[email protected]

J. N. Am. Benthol. Soc., 2011, 30(2):573–588’ 2011 by The North American Benthological SocietyDOI: 10.1899/10-018.1Published online: 5 April 2011

573

the Tubifex tubifex host of Myxobolus cerebralis, theparasite that causes whirling disease in salmonids(Zendt and Bergersen 2000). This interaction hasobvious and significant implications for streamrestoration and disease management.

The effects of M. cerebralis are variable acrossdifferent environments, in part, because of its com-plex life cycle, which includes multiples stages andhosts, each of which is influenced differentially bystream habitat characteristics (Hiner and Moffitt 2002,de la Hoz Franco and Budy 2004, Kaeser et al. 2006).Nevertheless, habitat conditions favorable for prolif-eration of M. cerebralis, T. tubifex, and infectionprevalence and severity in fish generally include highwater temperatures (Reynoldson 1987, Hiner andMoffitt 2002, de la Hoz Franco and Budy 2004),nutrient concentrations (Lestochova 1994), conductiv-ity (Sandell et al. 2001), and sedimentation rates(McMurtry et al. 1983, Lazim and Learner 1987,Krueger et al. 2006). These factors are broadlyassociated with stream degradation by land usesincluding livestock grazing (Fig. 1). This associationsuggests that M. cerebralis production and T. tubifexproliferation and infection are likely to be greater instream habitats degraded by livestock grazing orother land uses (Hansen 2007, but see Granath et al.2007) than in intact streams.

Livestock grazing is a common land use in thewestern USA that can alter stream ecosystems directlyand indirectly through interrelated effects on vegeta-tion, nutrient processing, soil, water, and streammorphology (Platts 1981, del Rosario et al. 2002,Sweeney et al. 2004). Livestock congregate around

water, so the direct effects of livestock grazing onstream ecosystems include nutrient inputs (e.g., viamanure), consumption and trampling of vegetation,soil compaction, and collapse or shear of stream banks(Fleischner 1994, Belsky et al. 1999, del Rosario et al.2002). Consequently, this land use has the potential toincrease upland erosion, stream power, channelerosion, entrenchment or width-to-depth ratios, tur-bidity, and nutrient concentrations and to decreasestream shading, sinuosity, and water-table levels(Knapp and Matthews 1996, Owens et al. 1996, Belskyet al. 1999). Livestock exclusion often is used toinitiate passive restoration of aquatic and riparianhabitats (Bernhardt et al. 2005). Exploration of thepotential of passive restoration to improve ecosystemhealth and minimize the effect of disease is a frontierin ecology (NRC 2001) and management of whirlingdisease.

Native trout populations in the Intermountain West(USA) have been negatively affected by land uses thatinclude livestock grazing. Bonneville cutthroat trout(Oncorhynchus clarkii utah), an endemic and protectedsubspecies of cutthroat trout have been reduced toonly a portion of their historic ranges because ofcombinations of habitat degradation, invasions andintroductions of exotic species, and spread of disease(Behnke 1992). One of the largest remaining meta-populations of genetically pure Bonneville cutthroattrout is in the Logan River, northern Utah (Lentsch etal. 1997, Budy et al. 2007), where M. cerebralis wasdetected in 1999. Myxobolus cerebralis prevalence is: 1)positively associated with temperature, 2) greater inwild fish than sentinel fish (i.e., noninfected fishexposed on-site), and 3) greater in the mainstem of theLogan River than in its tributaries (de la Hoz Francoand Budy 2004). These patterns suggest that thetributaries may serve as a refuge from infection forfish and that changes in stream temperature mayinfluence the prevalence and negative effects of theparasite.

We worked within the context of fish conservationand the science of river restoration to investigate theefficacy of passive stream restoration via livestockexclusion alone to: 1) restore stream and riparianhabitat to a more natural condition (Moerke et al.2004) and 2) reduce the prevalence of whirling diseasein an important population of native Bonnevillecutthroat trout. We excluded cattle to initiate passivestream restoration of Spawn Creek, an importantspawning and rearing tributary for cutthroat trout inthe Logan River (Bernard and Israelsen 1982). SpawnCreek has a long history of livestock grazing. Wehypothesized that passive restoration would reducenutrient inputs and sedimentation over the short term

FIG. 1. Conceptual diagram of the potential relationshipsamong the effects of cattle grazing on the environment andthe stages and hosts of the Myxobolus cerebralis parasite.TAM = triactinomyxon.

574 E. S. HANSEN AND P. BUDY [Volume 30

and decrease stream temperatures over the long termbecause of increased riparian shading (Table 1). Wealso hypothesized that these stream- and riparian-habitat changes would result in a decrease in theprevalence of M. cerebralis in native cutthroat trout(Fig. 1). We evaluated the short-term responses ofbiota, habitat, and fish disease in Spawn Creek topassive restoration techniques and measured keyresponse variables before and after exclosure atimpact and control sites.

Methods

Study area and approach

We studied Spawn Creek, a 2nd-order headwatertributary in the Logan River watershed in northernUtah, USA (more detailed study area information is

available in de la Hoz Franco and Budy 2005 andBudy et al. 2007). Grazing occurred primarily in thelower sections where the gradient is moderate (,5%

for the grazed section) and the vegetation is primarilyherbaceous with some willows (Salix spp.) present.We used a Before-After Control-Impact (BACI) designand collected repeated samples over time at oneimpact site (Spawn Creek) and multiple control sites(Temple Fork and part of the mainstem Logan River)to detect change. We selected multiple control sites tohelp distinguish between variability in responsescaused by natural variability and that caused byexclusion of livestock grazing. The watershed area ofthe impact site was smaller than that of the controlsites, and the impact site had a less variablehydrograph because of groundwater inputs (Hansen2007).

TABLE 1. The hypothesized (expected) and observed direction of change and probable processes driving short- (,5 y) andlong-term (.5 y) physical, in-stream, and riparian-habitat responses to passive restoration (livestock exclusion) at the SpawnCreek site. Response categories were: I = restoration effect, II = natural variation, III = combination of exclosure and naturalvariation, IV = indirect (alternative 1 = change in another variable, alternative 2 = opposing responses at control sites), and V =

no response (see text for additional explanation). Directions of change were: decrease (Q), increase (q), and no change (=).* indicates variable-specific response.

Variable

Short-term

Long-termexpected ProcessExpected Observed

Responsecategory

Physical response

Nutrients Q Q=* I, V* Q Decreased fecal inputs and surfacerunoff

Chlorophyll a q = V Q Decreased turbidity; decreased solarirradiation

Turbidity Q Q I Q Decreased sediment inputsConductivity Q Q I Q Decreased nutrients and surface runoffTemperature = Q II Q Increased stream shading; decreased

solar irradiationDischarge = = V Q Increased hyporheic capacity and

exchange; decreased surface runoffSubstrate size q = V q Decreased sediment inputsPool tail fines = = V Q Decreased sedimentationStable banks q q II q Increased vegetative cover

Riparian habitat

Exotic species cover Q QQ II, IIa Q Native species response to decreasedherbivory and trampling

Woody cover q = V q Decreased herbivory and vegetationtrampling

Effective ground cover q Q II q Decreased herbivory and trampling

Disease

Disease prevalence(wild and sentinelcutthroat trout)

=, = QQ IV (1), IV (1, 2) QQ Decreased triactinomyxonproduction and decreased diseaseprevalence in response todecreased temperatures, nutrientconcentrations, and fine sediments

a First response listed is from greenline measurements and 2nd response is from cross-section measurements

2011] PASSIVE STREAM RESTORATION AND FISH DISEASE 575

We excluded cattle from the impact site by fencingmost of the Spawn Creek riparian area. We construct-ed a fence along ridges parallel to each side of thestream (0.25 km mean width) for 3 km to form a 67-haexclosure (Fig. 2). Steep topography at the upper endof the stream and the U-shaped exclosure design alsoexcluded livestock grazing from the upper 2 km of thestream. Thus, we effectively eliminated grazing along

the entire stream with the exception of the bottom200 m near the confluence with Temple Fork.

We established 3 primary index reaches (each 200 mlong; upper, middle, lower) within the impact site tocapture the longitudinal heterogeneity of the streamin the area frequented by livestock (Fig. 2). Wedesignated the middle index reach as an intensivesampling reach in which we monitored a full suite of

FIG. 2. Map of the Spawn Creek impact site showing primary (PR) and secondary (SR) index reaches and exclosure fencing inreference to the stream. Inset shows locations of impact and control sites.


abiotic and biotic response variables. We measuredonly a subset of response variables (see Table 2) at theupper and lower index reaches for logistical (cost andeffort) reasons. We monitored riparian habitat vari-ables (physical and vegetation) at 3 secondary indexreaches (each 160 m) during the before and afterperiods (Table 2).

We selected control sites based on similarity ofhabitat characteristics and fish assemblages with theimpact site and on the availability of pre-existing datafrom a companion long-term study (Budy et al. 2007).Control sites were unfenced and experienced varyingeffects of grazing. These effects were lower thaneffects at the impact site before fencing. Two controlsites were 100-m reaches in which we monitored fishand water quality, but not riparian habitat. TempleFork (control site 1) was sampled at its confluencewith the Logan River. Franklin Basin (control site 2)was part of the mainstem Logan River near theheadwaters. We monitored only in-stream and ripar-ian habitat at 2 additional control sites (each 160 m).Control site 3 was on Spawn Creek below theexclosure at its confluence with Temple Fork. Controlsite 4 was on Temple Fork upstream of its confluencewith Spawn Creek and ,2 km upstream of controlsite 1.

Monitoring

We initiated pilot monitoring in 2004, conductedfull before monitoring in 2005 (the final year ofgrazing), and conducted after monitoring in 2006 (the1st year of exclusion). We sampled fish again in 2007for a 2nd after year. The Spawn Creek subwatershed isgrazed on a rotational system, and grazing occursprimarily in July. The duration of grazing at theimpact site was 3 to 4 wk. The time required to move

the livestock on and off the grazing allotment was 2 to3 d before and after the grazing period. We collectedsamples during 3 matching periods (early, late, andpostgrazing) before and after restoration at the impactsite and during the postgrazing period at the controlsites. The early grazing period included the first fewdays of grazing, the late grazing period was the finalweek of grazing, and the postgrazing period was,1 mo after grazing ceased. These periods refer to theperiod during which grazing occurred at the impactsite and do not necessarily correspond to grazingactivities at the control sites.

Response categories

We monitored a set of abiotic and biotic variablesthat were likely to respond to restoration andpotentially were related to the prevalence and effectof M. cerebralis. Observed responses at the site of arestoration project may be attributed to multipleprocesses, so we established 5 categories of responsetypes to help determine the underlying process. Weused potential changes from before to after and fromimpact to control to categorize responses as:

I. Restoration effect.—Change occurred in the hy-pothesized direction at the impact site, but did notoccur at the control sites.

II. Natural variation.—The pattern of change (i.e.,direction and magnitude) in the response variable atthe impact site was similar to the pattern at the controlsites.

III. Combination of restoration and natural variation.—The direction of change at the impact site was thesame as at the control sites, but the magnitude ofchange was greater at the impact site.

IV. Indirect response.—1) The source process was achange in another variable and the observed response

TABLE 2. Sampling schedule for response variables measured at the impact and control sites during the before (2004, 2005) andafter (2006, 2007) years. Sampling was scheduled during 3 grazing periods (early, late, and postgrazing) relative to the grazingrotation at the impact site. Water temperature measurements were made year-round with continuously recording temperatureloggers. U = upper, M = middle, L = lower primary index reaches, C = control sites (C1, C2, C3, C4).

Response variable Year Early grazing Late grazing Postgrazing

Water temperature, turbidity, nutrients,discharge, substrate, chlorophyll a

Before 2005 U M L M C1 C2 U M LAfter 2006 U M L C1 C2 M C1 C2 U M L C1 C2After 2007 U M L C1 C2 M C1 C2 U M L C1 C2

Stream riparian habitat Before 2004 – – U M La C3 C4b

After 2006 – – U M La C3 C4b

Disease prevalence (wild fish) Before 2001–2005 – M C1 C2 –After 2006–2007 – M C1 C2 –

Disease prevalence (sentinel fish) Before 2005 M C1 C2 –After 2006 M C1 C2 –

a In-stream and riparian-habitat characteristics also were sampled at secondary sampling reaches at the impact siteb Before sampling of riparian and stream habitat occurred in 2004


was a consequence of that change (e.g., decreasedsedimentation during naturally low, drought dis-charge), or 2) responses at the control sites occurredin opposing directions (e.g., an increase in a responsevariable at one control site and a decrease in theresponse variable at the other control site).

V. No response.—No change was detected in theresponse variable.

Physical and chemical response variables

At each primary index reach and control site (seeTable 2 for timing), we collected grab samples ofstream water for nutrient analyses. We used standardtechniques (APHA 1989) to analyze water samples forconcentrations of total Kjeldahl N (TKN), NH3, NO3 +NO2, total P (TP), soluble reactive P (SRP), anddissolved P (DP). We used chlorophyll a in periphy-ton on rocks as an index of algal abundance (APHA1989). We extracted and measured chlorophyll aconcentration (mg/cm2) with the Welschmeyer fluo-rometric method (Welschmeyer 1994). We measuredturbidity and specific conductance with handheldinstruments (LaMotte 2020; LaMotte, Chestertown,Maryland; YSI 556; Yellow Springs Instruments,Yellow Springs, Ohio).

We collected temperature readings recorded hourlywith temperature loggers (HOBO Pendant logger;Onset Corporation, Bourne, Massachusetts). Weplaced 5 loggers at the impact site, and 1 each atcontrol sites 1 and 2. We used 2 additional measuresof temperature as test variables. We used the 1st

method to account for the development of triactino-myxons (TAMs; M. cerebralis stage) after the initiationof passive restoration. TAMs require 1300+ degreedays to develop within the T. tubifex host (Kerans andZale 2002). Therefore, we calculated degree days asthe sum of the daily average temperature across the 5Spawn Creek temperature loggers during 2 timeperiods. The 1st period was 1 September 2005(postgrazing) to 30 March 2006 when maximumtemperatures began to exceed 10uC, and the 2nd was1 September 2005 to 31 May 2006, which was the timebetween peak surface-water runoff and peak ground-water discharge. We used a 2nd method to account foroptimum temperatures for the T. tubifex host andTAM production after the initiation of passiverestoration. This association is relevant becauseseverity of infection is related to the level of TAMexposure (Hedrick et al. 1999). Therefore, we used thenumber of days per year with temperatures withinthe range considered optimal for T. tubifex (10–13uC;Reynoldson 1987) and TAM production (10–15uC; El-Matbouli et al. 1999).

Stream and riparian habitat

We measured discharge (m3/s) by the mid-sectionmethod (Harrelson et al. 1994). We characterizedsubstrate composition from pebble counts from §100particles per reach and sampling event (Table 2). Wecollected particles along a series of equidistant transectsplaced perpendicular to flow, measured all particleswith a gravelometer (measurement template), anddetermined particle size .16% of the sampled particles(D16; equal to 1 standard deviation from the median;Bunte and Abt 2001). The US Forest Service (USFS), Fishand Aquatic Ecology Unit, Logan, Utah, monitored in-stream and riparian-habitat characteristics with aprotocol developed to evaluate land managementpractices and the effects of maintaining or restoringaquatic and riparian habitats (PACFISH/INFISH Bio-logical Opinion Effectiveness Monitoring Program[PIBO]; Kershner et al. 2004; protocols available from:www.fs.fed.us/biology/ fishecology/new.html#pibo_reports). USFS personnel conducted PIBO effectivenessmonitoring at the impact primary and secondary indexreaches and control site 4 (see Table 2 for timing). Theyalso measured pool tail fines (% substrate fines ,2 and,6 mm at the downstream end of pool), bank stability,exotic species cover (greenline [first perennial vegeta-tion near stream edge] and cross-section measure-ments), woody cover (greenline measurement), andeffective ground cover (cross-section measurement; livevegetation, litter, rock).

Whirling disease

We used backpack electrofishing at the impact middleindex reach and at control sites 1 and 2 to sample troutto assess the prevalence of whirling disease before(2001–2005) and after (2006–2007) restoration. We alsoexposed sentinel fish in situ to determine the prevalenceof M. cerebralis (i.e., % fish testing positive for M.cerebralis) at the impact middle index reach and atcontrol sites 1 and 2 in 2005 and 2006. Use of sentinel fishallowed us to measure the relationship betweenprevalence and in-stream habitat characteristics and tocontrol for movement of wild fish to and from theexposure sites. At each site, we deployed 3 replicatecages, each containing 30 age-0 Bonneville cutthroattrout (mean total length = 32.5 mm) certified to be M.cerebralis negative. We conducted sentinel fish expo-sures for a minimum of 21 d in the field and reared fishin aquaria after exposure for ,90 d to allow sporedevelopment prior to euthanizing the fish. We testedfish for whirling diseases with single-round polymerasechain reaction (PCR) techniques with the heat shockprotein (HSP) 70 gene segment (J. Wood, PiscesMolecular LLC, personal communication).


Data analysis

We used several different types of comparisons(Table 2) because of the variation in temporal andspatial scales of our measurements and the types ofresponse variables (i.e., continuous vs discrete). Wesampled physical response variables and periphyton3 times (early, late, and postgrazing) during beforeand after years. We made comparisons at control sitesfor the late grazing period only.

We assessed the effects of period and year on eachresponse variable with a randomized block, 2-wayfactorial analysis of variance, where blocks weredefined by location (impact upper, middle, lowerindex reaches). Location was a random-effects factor,whereas year (before, after), period (early, late,postgrazing), and their interactions were fixed-effectsfactors. We also used effect sizes calculated as

d=(before{after)=spooled

where

spooled=

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi(½s2

beforezs2after�=2)

q

to assess responses to restoration (d increased whenresponse decreased from before to after; Cohen 1977).Effect-size values were variable-specific and weredescribed relative to the predicted response direction(Table 1). Effect sizes can be interpreted as small(d = 60.2), medium (d = 60.5), and large (d = 60.8),but these categories are somewhat subjective anddepend on the variable (Cohen 1977). We used pairedor 1-sample t-tests as appropriate to assess changebetween before and after of stream and riparian habitatvariables. In the 1-sample tests, we used the metric(after/before) and tested the hypothesis: Ho: m = 1.

We used tests of 2 binomial proportions andFisher’s exact test to quantify differences in preva-lence of M. cerebralis between before and after yearsfor sentinel and wild fish (MinitabH version 15.1; StateCollege, Pennsylvania). We used linear regression ofthe compilation of disease-prevalence data for wildcutthroat trout collected at all sites from 2001–2007(dependent variable; arcsine![x]-transformed) as afunction of the number of days that stream temper-atures at each site were within the optimal range forT. tubifex and TAM production (independent vari-ables). These prevalence data were collected as part ofour study (2005–2007) and as part of previous studiesand monitoring (2001–2004; de la Hoz Franco andBudy 2004, Budy et al. 2007).

Logistical limitations (e.g., equipment failure andfinancial constraints) limited sample size and design

symmetry. Therefore, we were limited to descriptivecomparisons for a few response variables and timeperiods at the control sites. Values of all responsevariables were measured and available at the controlsite for all years during the late grazing season, theseason most sensitive to cattle effects, and statisticalcomparisons were drawn accordingly. Unless other-wise noted, all statistical analyses were conducted inSAS (version 9.1; SAS Institute, Cary, North Carolina)and significance was evaluated at a = 0.05.

Results

Physical and chemical response variables

The responses of nutrient concentrations (mg/L) tolivestock exclusion were variable-specific. Only TKN,TP, and SRP differed significantly among years. TKNdecreased as predicted at the impact site (significantfor year and period; d = 1.360) but was similar amongyears at the control sites with an opposing effect-sizeresponse (d = 20.52; Table 3, Fig. 3A, B). TP de-creased as predicted at the impact site (significantfor year, period, and interaction; d = 1.67), but wassimilar among years at the control sites with anopposing effect-size response (d = 20.59; Table 3,Fig. 3A, B). SRP decreased as predicted at the impactsite (significant for year; d = 1.98), but was similaramong years at the control sites (d = 20.62; Table 3,Fig. 3A, B). In contrast, DP concentrations did notdiffer significantly among years at the impact site (d= 1.96), but had an opposite effect-size response at thecontrol sites (d = 20.64; Table 3, Fig. 3A, B). NH3 andNO3 + NO2 were similar among years at the impact(NH3: d = 21.33, NO3 + NO2: d = 21.64) and controlsites (NH3: d = 20.5, NO3 + NO2: d = 22.21; Table 3,Fig. 3A, B).

Other water-quality response variables (excludingnutrients and temperature) generally were similaramong impact and control sites within years butvaried among years. Chlorophyll a concentrationswere highly variable within sampling reaches at eachsite and effect sizes at the impact and control siteswere in opposing directions (d = 21.5 and 0.65,respectively). This high natural variability maskedany potential response to restoration (Table 3, Fig. 3A,B). Turbidity decreased at the impact site from thebefore early grazing period to the late and postgraz-ing periods and the after year (significant period andinteraction effects; d = 0.09). Turbidity was similar atthe control sites among years (d = 21.32; Table 3,Fig. 3A, B). Specific conductance decreased as pre-dicted across years at the impact site (significant foryear, period, and interaction; d = 2.15), but wassimilar among years at control sites, although effect


sizes responded in the same direction (d = 1.11;Table 3, Fig. 3A, B).

Stream temperatures varied considerably over the4-y period of our study. Daily average streamtemperatures at all sites were highest during 2004and 2007 and lower during 2005 and 2006. Thethermal patterns were parallel in 2005 and 2006(Fig. 4A–C). The greatest daily temperature changeoccurred at the impact site and the lowest occurred atcontrol site 2. At the impact site, the number of degreedays for TAM production was 1158 for the period 1September 2005 (postgrazing) to 30 March 2006, whenmaximum temperatures began exceeding 10uC, and1395 for the period 1 September 2005 to 31 May 2006,the period from peak surface water runoff and peakgroundwater discharge (Fig. 4A–C). Stream dischargewas highest at control site 2 and lowest at the impactsite during 2005 and 2006. During the correspondinggrazing periods, discharge was similar at the impactsite among years, but a significant decrease occurredduring the postgrazing period each year (Table 3,Fig. 3A, B).

Stream and riparian habitat

The response of in-stream and riparian habitats wasmost apparent in vegetation-related variables(Fig. 5A, B) and appeared to be influenced by thetransition from a drought year in 2004 to a non-drought year in 2006 at all sites. D16 was similaramong years at the impact and control sites (Fig. 3A,B). The largest D16 occurred at control site 2 and thesmallest at control site 1. Pool tail fines were similaramong years at the impact and control sites (Table 4).Percent stable banks increased at the impact andcontrol sites (d = 23.10 and 26.30, respectively;Table 4). Percent woody cover along the greenlinewas similar among years at impact and control sites(d = 20.09 and 20.68, respectively; Table 4). Overall,exotic species cover (greenline and cross-section) andeffective ground cover decreased across years at boththe impact and control sites (Table 4).

Whirling disease

Myxobolus cerebralis was present at all sites beforerestoration. Wild cutthroat trout collected at theimpact and control sites tested positive for M.cerebralis in all years (Table 5). During the 1st afteryear (2006), prevalence of M. cerebralis decreasedsignificantly in both wild and sentinel fish at theimpact site, whereas prevalence fluctuated with anoverall increasing trend at the control sites. Duringthe 2nd after year (2007), prevalence increasedsignificantly at the impact site (Table 5). Among all

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years and sites, a significant, positive relationshipexisted between the number of days that streamtemperatures were within the range consideredoptimal for both T. tubifex and TAM production(same number of days for both variables) and theprevalence of M. cerebralis in wild cutthroat trout (n =

21, p = 0.012, adj. R2= 0.29; Fig. 6).

Discussion

We evaluated the short-term potential of a passivestream restoration project to improve in-stream andriparian habitat and to minimize the potentiallysynergistic effects of habitat alteration and whirlingdisease on native trout. Some frequent issues continueto limit the science and practice of restoration(Bernhardt et al. 2005, 2007, Miller et al. 2010), sowe: 1) specified our overall restoration goal a prioriand hypothesized the expected direction of change fora suite of biological, chemical, and physical responsevariables, 2) used multiple control sites to evaluate theeffectiveness of restoration and compared patterns ofresponse variables temporally (before vs after) and

spatially (impact vs control), and 3) classified thetypes of responses observed into 5 categories. Thisapproach allowed us to address some sources ofinherent uncertainty and to determine whether aresponse was a product of the restoration, naturalvariation, a combination of both, or an indirectresponse to a change in another variable (Wheatonet al. 2008).

Over the short term (1–2 y postrestoration), weobserved responses that could be attributed to each ofthese causes. We attributed decreases in TN, TP, andSRP to the exclosure and removal of livestock andgrazing impacts. We attributed most of the decreasein average stream temperatures and specific conduc-tance to natural climatic variation. Last, we attributedcontrasting changes in cover of exotic plant species atthe impact site and control sites to combinedrestoration/natural variability in climate effects (non-drought conditions). The variability in types ofresponses demonstrates the potential difficulty ofdrawing strong conclusions about restoration re-sponses, even when the study design is fairly robust(Moerke et al. 2004, Miller et al. 2010). We identified

FIG. 3. Box plots (lines are medians, ends of boxes are 25th and 75th percentiles) for nutrient concentrations, chlorophyll a, andphysical response variables during the early, late, and postgrazing periods at the impact (A) and control (B) sites, data combined.Values were divided by 10 (*), 100 (**), and 1000 (***) to improve graphical representation. TKN = total Kjeldahl N, TP = total P,SRP = soluble reactive P, DP = dissolved P, D16 = diameter of particles in the 16th percentile.


statistically significant differences in some responsevariables (nutrients and conductivity), but continuedmonitoring will be necessary to determine whetherthese changes will be biologically significant over thelong term. We also observed statistically significantincreases in bank stability, decreases in exotic speciescover, and increases in effective ground cover. Theseriparian changes are biologically important becausethey reduce surface runoff and buffer sediment andnutrient inputs into the stream (Osborne and Kovacic1993, Owens et al. 1996, Belsky et al. 1999).

Several factors can contribute to an observed lack ofresponse to restoration. For example, the variablesmeasured simply might not be influenced by restora-

tion-related processes. Factors related to several of ourvariables could include, but are not limited to: 1)extremely high natural variability in the responsevariable, 2) sensitivity of the response variable tomethod of measurement, and 3) the short responsetime. For example, substrate composition has highwithin-reach variability that can dominate othersources of variation and could mask other responsesto stream restoration (Olsen et al. 2005). We detectedno significant change in substrate composition inresponse to restoration. In contrast, we detected asignificant increase in bank stability even though bankcharacteristics are sensitive to the measurementapproach used, and often, sample size is insufficientto detect a change (Roper et al. 2002).

Time since restoration also is an important factorwhen assessing the effectiveness of any restorationproject. Many variables require several years or even

FIG. 4. Mean (avg), maximum (max), and minimum(min) daily stream temperatures (uC) measured at theimpact (A) and control sites 1 (B) and 2 (C) from 2004 to2007. Shaded areas indicate the optimal range of tempera-tures for development stages of the Myxobolus cerebralis lifecycle and Tubifex tubifex host. The vertical dashed lineindicates when the exclosure was erected. The meantemperatures at the impact site during the summer 2005and 2006 were below the optimal development range forstages of the Myxobolus cerebralis life cycle and Tubifex tubifexhost (shaded area).

FIG. 5. Vegetation response to livestock exclusion at theimpact site lower index reach during the postgrazing periodfrom before (A) and after (B) restoration. The responsedepicted in the 2 photographs is representative of thechange in herbaceous vegetation. No woody riparianspecies were present. Photographs provided by PAC-FISH/INFISH Biological Opinion Effectiveness MonitoringProgram (United States Forest Service, Fish and AquaticEcology Unit, Logan, Utah).


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decades to respond (Kondolf 1993, Magilligan andMcDowell 1997). We measured the response topassive restoration over a relatively short period of3 y (including only 1 after year). After more timepasses, we expect to see responses in more variablesand stronger responses in some variables that havealready changed (e.g., continued decrease in exoticplant species cover). Comparison of the responsesmeasured over the short term relative to thoseexpected over the long term (i.e., direction of responsebased on our a priori hypotheses) should further ourunderstanding of recovery trajectory after restoration(Moerke et al. 2004, Tullos et al. 2009). In addition, bynecessity, both control sites were 3rd-order streams,whereas the impact site was a smaller, 2nd-orderstream. Comparisons between before and after yearsshould account for some of the spatial differencesamong control and impact sites, but importance ofsome stream processes (e.g., primary production) mayvary with watershed size.

For all restoration projects, the scale of therestoration effort relative to the scale of the problem(e.g., level and source of degradation) can limit ourability to meet restoration goals (Moerke et al. 2004,Booth 2005, Miller et al. 2010). Especially for exclosureprojects, the size and location of the restoration in thewatershed can determine potential for success (Sarr2002, Bayley and Li 2008). We attribute the short-term

success of our project to the large size of the exclosure(67 ha), effective exclusion of livestock grazing fromthe entire stream length (except the bottom 200 m),and the relatively wide riparian buffer (nearly ridge toridge).

One of the greatest influences on the success ofriparian restoration projects is the level of degradationbefore the restoration relative to the natural resilienceof riparian areas (Ebersole et al. 1997, Kauffman et al.1997). Spawn Creek was an ideal candidate forpassive stream restoration because the level ofdegradation was not severe (e.g., little or no channelincision), and the seed bank of the native vegetationwas still present and viable. Thus, active restorationwas not necessary, and initiation of an apparenttrajectory of change was immediate and positive.

One of our goals was to assess the potential forstream restoration to minimize effects of fish disease.We observed some intriguing, albeit inconclusive,responses in the prevalence of M. cerebralis in bothwild and sentinel fishes. We attribute the initialdecline in M. cerebralis prevalence in both wild andsentinel fish at the impact site primarily to decreasesin stream temperature (Baldwin et al. 2000, Hiner andMoffitt 2002, de la Hoz Franco and Budy 2004).However, both climatic and exclosure effects probablycontributed to changes in stream temperature. Thestudy period included hot, dry drought years (2004

FIG. 6. The relationship between disease prevalence (Myxobolus cerebralis) in wild cutthroat trout collected at all sites from 2001to 2007 as a function of the number of days that stream temperatures at each site were within the optimal range for both Tubifextubifex and triactinomyxon (TAM) production. n = 21, p = 0.012, adjusted R2 = 0.29.


and 2007) and cooler, wet years (2005 and 2006).Average stream temperatures differed .2uC betweenthe 2 climatic regimes. This type of natural climateand geomorphic variability can mask or alter theresponse of water-quality variables to stream restora-tion (Booth 2005, Wheaton et al. 2008), but in thisecosystem, a decline in stream temperature of even2uC can produce a temperature regime that is belowthe optimal range for the M. cerebralis and T. tubifex.Across all years and sites (where data were available),prevalence of M. cerebralis was positively associatedwith the number of degree days in the optimal rangefor both T. tubifex and TAM production. Thecomplexity (and length) of the M. cerebralis life cycleand the influence of multiple habitat variables makespecific or independent processes controlling theprevalence of the parasite difficult to identify withcertainty, but this positive relationship is notable.Potential exists for stream temperatures to continue todecrease over the longer term if riparian vegetationgrows enough to shade the stream (Van Velson 1979,Li et al. 1994, Sweeney et al. 2004). Maximum streamtemperatures were 2 to 3uC lower at a restored reachof a nearby watershed than at an adjacent reachdownstream of the exclosure 5 to 6 y after restoration(Duff 1977).

Many responses to restoration occur over the longterm, but the immediate decrease in the prevalence ofM. cerebralis at the restoration site during coldernondrought years is important. Relatively smalldecreases in temperature may be even more impor-tant if the climate warms. In addition, the immediatedecrease in stream enrichment (N, P, and sediment)may result in habitat less suitable to enrichment-loving invertebrates (e.g., chironomids; del Rosario etal. 2002) including the T. tubifex host (Lestochova1994). Thus, given the relationship between theprevalence of the parasite and these stream-habitatcharacteristics with potential for change, streamrestoration appears to have potential to minimizethe prevalence and impact of disease.

Acknowledgements

Our research was funded primarily by Utah Divisionof Wildlife Resources (UDWR), Project XV, SportFisheries Research, Grant Number F-47-R, Amend-ment 20, and by the Utah Division of Water Quality,Environmental Protection Agency Clean Water ActSection 319. Additional contributions were made byUtah State University, US Geological Survey UtahCooperative Fish and Wildlife Research Unit, CacheAnglers Chapter of Trout Unlimited (TU), LoganRanger District Cache National Forest US Forest

Service, UDWR Dedicated Hunter Program, Fish andAquatic Ecology Unit USFS, TU Embrace-a-StreamProgram, UDWR Blue Ribbon Fisheries Program, JohnCarter and Western Watersheds, Bonneville Chapter ofthe American Fisheries Society, Utah Council of TU,Weber Basin Anglers Chapter of TU, The StoneflySociety, Bridgerland Audubon Society, BridgerlandOutdoor Coalition, and Sportsmen for Fish andWildlife. Specifically, we offer sincere gratitude to PaulChase (USFS), Chris Thomas (Cache Anglers), andChris Wilson (UDWR, FES) for spearheading theexclosure project and evaluation, raising .200,000USD, and enduring endless and painful negotiationswith all the political entities involved. We also thankGary Thiede, Charles (Chuck) Hawkins, John (Jack) C.Schmidt, and numerous UDWR Fisheries ExperimentStation (FES) staff and other volunteers and techniciansfor scientific and logistical contributions and generalsupport. Brett Roper, Ronald Ryel, Scott Miller, GaryThiede, and anonymous referees reviewed previousdrafts of this manuscript and provided constructivecriticism and insight.

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Received: 10 February 2010Accepted: 11 February 2011


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