Discrimination of Chinook Salmon, Coho Salmon, and Steelhead

Home , Chinook salmon, Coho salmon

North American Journal of Fisheries Management 25:284±300, 2005 ᭧ Copyright by the American Fisheries Society 2005 [Article] DOI: 10.1577/M04-016.1

Discrimination of Chinook Salmon, Coho Salmon, and Steelhead Redds and Evaluation of the Use of Redd Data for Estimating Escapement in Several Unregulated Streams in Northern California

SEAN P. G ALLAGHER* California State Department of Fish and Game, 1031 South Main Street, Suite A, Fort Bragg, California 95437, USA

COLIN M. GALLAGHER1 Department of Mathematics and Statistics, Holt Hall, California State University±Chico, Chico, California 95929, USA

Abstract.ÐWe developed and evaluated a strati®ed index redd area method to estimate Chinook salmon Oncorhynchus tshawytscha, coho salmon O. kisutch, and steelhead O. mykiss escapement in several coastal streams in northern California based on the assumption that redd size is related to the number of redds a female builds. Sources of error in redd counts were identi®ed, including the use of logistic regression to classify redd species (necessary due to temporal overlap in the spawning of these species in coastal northern California). Redd area escapement estimates were compared with estimates from more conventional methods and releases above a counting structure. Observer ef®ciency in redd detection ranged from 0.64 (SE ϭ 0.10) to 0.75 (SE ϭ 0.14) and was signi®cantly associated with stream¯ow and water visibility (analysis of variance [ANOVA]: F ϭ 41.8; P Ͻ 0.001). Logistic regression reduced uncertainty in redd identi®cation. Redd area and date observed were signi®cant in predicting coho salmon and steelhead redd species (Wald's z ϭ 11.9 and 18.09, respectively; P Ͻ 0.001). Pot substrate and redd area were signi®cant in classifying Chinook and coho salmon redds (Wald's z ϭ 5.88 and 4.03; P ϭ 0.015 and 0.04, respectively). Strati®ed index redd area escapement estimates and estimates based on capture±recapture experiments, area-under-the-curve estimates, and known releases above the counting structure (coho salmon only) were not signi®cantly different (ANOVA: F Ͻ 13.6; P Ͼ 0.06). Escapement estimates assuming one redd per female were only signi®cantly different from other methods for steelhead (ANOVA: F ϭ 13.11; P ϭ 0.006). Redd counts were signi®cantly correlated with escapement estimates (r Ͼ 0.82; P Ͻ 0.04). Reduction of counting errors and uncertainty in redd identi®cation, biweekly surveys throughout the spawning period, and the use of redd areas in a strati®ed index sampling design produced precise, reliable, and cost-effective escapement estimates for Chinook salmon, coho salmon, and steelhead.

Accurate estimates of escapement are essential need for reliable, cost-effective, and precise tech- for effective management and conservation of sal- niques for monitoring salmonid escapement. monids (Busby et al. 1996; McElhany et al. 2000). While redd counts are commonly used to index In northern California coastal Chinook salmon On- adult escapement and assess population trends corhynchus tshawytscha, coho salmon O. kisutch, (Beland 1996; Rieman and Myers 1997; Isaak et and steelhead O. mykiss are listed as threatened al. 2003), their accuracy as a measure of abun- species under the U.S. Endangered Species Act dance has rarely been evaluated (Dunham et al. (U.S. Of®ce of the Federal Register 1997, 1999, 2001). As the product only of reproductive adults, 2000). Estimates of abundance at the population redd counts provide an index of effective popu- level are likely to be an important, though not lation size (Meffe 1986). Maxell (1999) suggests independent, part of delisting criteria. There is a that the sources of counting errors involved in redd counts be identi®ed and reduced before they will be useful for long-term monitoring. Dunham et al. * Corresponding author: [email protected] 1 Present address: Department of Mathematical Sciences, (2001) suggest that redd counts are less intrusive Clemson University, Clemson, South Carolina 29634-0975, and expensive than tagging, trapping, underwater USA. observation, weirs, and genetics for inventorying Received February 4, 2004; accepted June 8, 2004 bull trout Salvelinus con¯uentus populations, and Published online March 4, 2005 that with limited resources more populations can

284 ESTIMATING SALMON AND STEELHEAD REDD ESCAPEMENT 285 be inventoried over a longer period. However, they Egg Collecting Station (ECS) between 2000 and conclude that substantial improvements are needed 2001 and between 2002 and 2003. To test if coho to reduce counting errors before redd counts will salmon and steelhead redd counts and redd-based be useful for population monitoring. The use of escapement estimates are related to true abun- redd counts for population monitoring may be fur- dance, we examined the relationship between these ther complicated if females make more than one data collected over 4 years in one river (steelhead redd. Crisp and Carling (1989) found that female only) and 3 years in two rivers and three creeks. salmonids occasionally make more than one redd, To determine if female salmonids make more than and Reingold (1965) documents a steelhead mak- one redd we compared the number of redds ob- ing two redds in different locations within a served to our AUC and capture±recapture esti- stream. Salmonids may also make false or ``test'' mates of the number of females. The two-fold pur- redds, which are abandoned before eggs are de- pose of this study was to determine if escapement posited (Crisp and Carling 1989). estimates, based on redd counts or on the as- The use of redd counts for population monitor- sumption that redd size is related to the number ing may be further complicated if there is uncer- of redds a female salmonid makes, can be applied tainty in redd species identi®cation. Identi®cation to all three species, and if they are more reliable, of Chinook and coho salmon and steelhead redds cost effective, and precise than conventional ap- in coastal northern California streams is dif®cult proaches. because of overlap in spawning time and redd sizes. Chinook and coho spawn from late October Methods through January, and steelhead spawn from De- Study Area and Data Collection cember through March in coastal northern Cali- fornia (Weitkamp et al. 1995; Busby et al. 1996; The streams studied were Caspar, Hare, and Myers et al. 1998). Redd surface areas range from Pudding creeks and the Albion, Little, Noyo, and 0.84 to 15 m2 for Chinook salmon, from 0.80 to Ten Mile rivers (Figure 1). These streams range 8.4 m2 for coho salmon (Burner 1951), and from in drainage area from 13 to 296 km2, ¯ow directly 2.4 to 11.2 m2 for steelhead (Orcutt et al. 1968). into the ocean, are unregulated, and are ground- Thus, to use redd counts for population monitoring water fed with peak ¯ows in winter following in coastal northern California it was necessary to heavy rains. develop a technique to distinguish redd species. All available spawning habitat in Caspar, Hare, To resolve some of the weaknesses listed above, and Pudding creeks and Little River was surveyed we evaluated the amount of bias in estimates due approximately biweekly from early December to errors in redd species identi®cation, detection 2000 to mid-February 2001 and from early De- of redds, and duration under variable survey con- cember 2001 to mid-April 2002 and approximately ditions. We used data collected over 2 years in weekly from mid-December 2002 to mid-April four rivers and three creeks to develop a logistic 2003. The entire extent of spawning habitat in the regression model based on physical redd charac- Noyo River was surveyed biweekly from late Feb- teristics and spawning time to distinguish between ruary 2000 to late April 2000 and from early De- coho salmon and steelhead redds and tested it with cember to mid-April during 2000±2001 and 2001± data collected in the third year of the study. To 2001. During 2002±2003 nine segments ranging distinguish between Chinook and coho salmon from 2 to 8 km were surveyed weekly in the Noyo redds, a similar model was developed and evalu- River. The Albion and Ten Mile rivers were sur- ated with data collected in two rivers during 1 year. veyed sporadically between 2000 and 2003. We evaluated the validity and some sources of bias Crews of two walked or kayaked 2- to 9-km- involved with using redd counts and redd sizes to long stream reaches searching for redds, live ®sh, estimate escapement by estimating surveyor ef®- and carcasses. Stream¯ow (m3/s) was estimated ciency, the duration redds remain visible, and the from ¯ow rated staff gauges and water visibility in¯uence of stream¯ow and water visibility on quanti®ed as the maximum depth (m) the stream redd detection. To determine if redd-based esti- substrate was visible. All redds observed were mates differed from conventional escapement ap- measured and uniquely marked with labeled ¯ag- proaches, we examined the relationship between ging, tied to the nearest branch directly upstream these estimates and estimates based on capture± of the pot, to avoid double counting. Live ®sh were recapture experiments, area-under-the-curve identi®ed to species, counted, and fork length and (AUC) estimates, and counts at the Noyo River sex visually estimated. Carcasses were identi®ed 286 GALLAGHER AND GALLAGHER

FIGURE 1.ÐMap showing the locations of the streams surveyed during this study in coastal Mendocino County, California. to species and sex, measured, inspected for tags, Brusven index (Platts et al. 1983). Tailspill length marks, and ®n clips, and unmarked carcass were (longitudinally parallel to stream¯ow) and tailspill uniquely marked with numbered metal tags. To width at one-third and two-thirds from the down- ensure consistency in data collection and identi- stream edge of the pot to the end of the tailspill ®cation of redds and ®sh, surveyors were provided (perpendicular to the length axis) were measured. with 4 h of laboratory training and2hof®eld The dominant tailspill substrate was visually es- training at the beginning of each season. In ad- timated as the undisturbed substrate upstream of dition, surveyors were rotated so that experienced the pot following Gallagher and Gard (1999) from and inexperienced surveyors were paired. December 2000 to April 2001 and in the middle All newly constructed redds observed were of the tailspill during following years. Redd areas identi®ed to species, treated as unknown, or de- were the sum of pot and tailspill areas calculated noted as test or redds under construction; marked by treating the pot as a circle or ellipse and the with ¯agging; counted; and measured during each tailspill as square, rectangle, or triangle. Redd lo- visit. Tests (redds which appeared incomplete to cations were recorded on ®eld maps. the observers) and redds under construction were To assess redd longevity and observer ef®ciency reexamined on consecutive surveys and were re- all ¯agged and newly constructed redds were ex- classi®ed if appropriate based on their apparent amined in each survey during 2002±2003. To ex- completion. Redd measurements consisted of area, amine redd longevity, redds were classi®ed as new, substrate, and depth. Pot length (measured parallel measurable, no longer measurable, or no longer to stream¯ow), pot width (perpendicular to the apparent. Weekly observer ef®ciency was esti- length axis), and pot depth (the maximum depth mated as the percentage of known ¯agged redds of the excavation relative to the undisturbed (minus those classi®ed as no longer apparent) ob- streambed) were measured, and the dominant pot served during each survey. Weekly ¯ag observer substrate was visually estimated using a modi®ed ef®ciency for each species was averaged for all ESTIMATING SALMON AND STEELHEAD REDD ESCAPEMENT 287

TABLE 1.ÐNumber of known coho salmon and steelhead redds observed by river and year used as a training data set for logistic regression analysis. Numbers in pa- rentheses are assumed known steelhead redds (based on date) added to increase the training data set.

2000±2001 2001±2002 Coho Coho Water body Salmon Steelhead Salmon Steelhead Albion River 1 3 10 0 Caspar Creek 3 0 11 (14) Hare Creek 0 0 2 1 (5) Little River 0 0 5 0 (8) Noyo River 26 7 (13) 11 9 (33) Pudding Creek 12 0 2 0 (6) Ten Mile River 0 0 24 0 FIGURE 2.ÐPercent of positively identi®ed Chinook and coho salmon and steelhead redds observed by week survey segments in each stream throughout the in several coastal Mendocino County streams, 2001± season to estimate total ef®ciency for the season. 2003. Multiple regression was used to examine the relationship between weekly ¯ag-based observer ef- ®ciency, stream¯ow, and water visibility. To fur- ing data collected in three creeks and four rivers ther examine observer ef®ciency, on two occasions during 2000±2001 and 2001±2002 (Tables 1±2). during early March 2003 four crews of two fol- To develop a training data set for discrimination, lowed each other on one survey segment and re- the redd data from each river was examined and corded only newly constructed redds. Average all known redds identi®ed. Because so few steel- ®eld observer ef®ciency was calculated by assum- head were observed on redds (Table 1), the number ing the largest number of redds observed by any of known steelhead redds in the training data set one crew was the known number, and the totals was increased so that the number of coho salmon from each survey crew observing fewer redds was and steelhead redds was equal. To do this, we de- divided by this number and these averaged. veloped a subset of all ®eld-identi®ed steelhead redds containing only redds ®eld identi®ed as Classi®cation of Redd Species steelhead after 16 February (the last date which Examination of the number of known redds live or dead coho salmon adults were observed). (redds which were positively identi®ed with one From this data set, ®eld-identi®ed steelhead redds species or another building or guarding them) ob- from each river each year were randomly selected served by week indicated a large overlap in the until number of steelhead and known coho salmon time of spawning among the three species of sal- redds per river was equal. Because no steelhead monids in this study (Figure 2). redds were observed in the Albion and Ten Mile Known coho salmon and steelhead redd data rivers during 2001±2002 (due to the surveys end- were used as a training data set in logistic regres- ing in mid-February), more late-season, ®eld-iden- sion analysis to differentiate redds by species us- ti®ed steelhead redds were randomly selected from

TABLE 2.ÐAverage and SE of Chinook salmon, coho salmon, and steelhead redd variables used in the training data set for logistic regression; na ϭ not applicable.

Coho salmon Steelhead Chinook salmon Variable Average SE N Average SE N Average SE N Day 32.4 1.6 102 101.8 2.6 102 28 10.1 5 Distance from ocean (km) 14.4 0.7 86 24.3 1.4 99 40.9 3.2 5 Fork length (cm) 67.9 1.1 81 71.7 2.9 20 Pot depth (m) 0.21 0.01 95 0.14 0.01 102 0.12 0.01 5 Pot substrate (cm) 2.1±4.5 na 102 2.1±4.5 na 102 15.2 1.3 5 Redd area (m 2) 6.03 0.34 102 1.78 0.14 102 6.72 0.87 5 Tail spill substrate (cm) 2.0±4.5 na 61 1.3±3.7 na 75 6.75 0.99 5 288 GALLAGHER AND GALLAGHER the other rivers to equalize the number of known of redds by the male-to-female ratio observed in redds (Table 1). each river and summing this with the number of In logistic regression analysis, the species mak- redds. Because Susac and Jacobs (1999) found ing a redd was the dependent variable and the var- steelhead redds per female to range from 0.5 to iables listed in Tables 1 and 2 were independent 4.45 and results reported herein were within this variables. Survey date was changed to day with range, we assumed the number of redds per steel- the ®rst survey date set as one. Modeling with head female to range from one to four. logistic regression continued iteratively, removing To estimate the number of female steelhead those variables least signi®cantly associated with based on redd area and a range of one to four redds predicting species and rerunning the regression. per female, we estimated the number of females The ®nal model was tested by applying it to all from redd area by multiplying the maximum-sized known redds observed during 2002±2003 and fur- known steelhead redd by three-quarters, one-half, ther evaluated by applying it to known steelhead and one-quarter. Redds larger than 4.6 m2 were redds measured in the American River during assumed to represent one female. Each redd be- 2002±2003 (J. Hannon, U.S. Bureau of Recla- tween 3.05 and 4.6 m2 was assumed to represent mation, unpublished data). The following equation three quarters of a female, redds between 1.52 and was applied to all redds observed to reclassify 3.04 m2 were assumed to represent one half of a them as steelhead or coho±Chinook: female, and redds smaller than 1.52 m2 were assumed to represent one quarter of a female. Coho ϭϪ ϩ Logit P 4.074 (0.13´ day) salmon redd area escapement estimates were based Ϫ (0.918´ redd area); on ®ndings from releases above the ECS during 1996, where it was estimated that females make Ն steelhead 0.5; between one and four redds and redd areas larger otherwise, coho or Chinook salmon. (1) than 5.1 m2 represent one female, redds between 2.1 and 5.0 m2 represent one half a female, and Chinook salmon redds were only positively redds smaller than 2.0 m2 represent one-quarter of identi®ed during 2002±2003. Equation (1) pre- a female (M. Maahs, Salmon Trollers Marketing dicted all known Chinook salmon redds observed Association, unpublished data). Female coho during 2002±2003 to be coho salmon redds. All salmon and steelhead redd area escapement esti- known Chinook and coho salmon redds during mates were multiplied by the male-to-female ratio 2002±2003 were used in logistic regression anal- observed in each stream each year and summed ysis following a procedure similar to that used to with female estimates to estimate populations. Ob- develop equation (1). The resulting equation server ef®ciency estimated during 2002±2003 and (equation 2) was used to classify redds as Chinook predicted for 2000±2001 and 2001±2002 was used or coho salmon, that is, to expand redd counts and redd area estimates. Uncertainty in redd identi®cation was derived ϭϪ ϩ Logit P 5.962 (0.441´ pot substrate) from logistic regression, and ®eld uncertainty was ϩ (0.253´ redd area); calculated from observer uncertainty in species making redds. Ն Chinook salmon 0.5; otherwise, coho salmon. Strati®ed index.ÐTo determine whether escape- (2) ment estimates could be made with reduced sampling effort using a strati®ed index approach (Ir- This model was evaluated by comparing the num- vine et al. 1992), steelhead and coho salmon redd ber of known redds in the original data set mis- area densities in the Noyo River during 2001±2002 classi®ed by equation (2). were plotted against sample reach (Figure 3a). Fig- ure 3a indicated that after nine reaches the variance Escapement Estimates around the mean did not substantially decrease. Redd area.ÐEscapement estimates based on Nine reaches were selected, and the average den- redd data were made by expanding total redd sity was calculated and multiplied by the total counts by the male-to-female ratio and by a meth- length of spawning habitat in each category to es- od which assumes the number of redds a female timate steelhead escapement for 2000, 2000±2001, makes is related to the size of the redd (redd area and 2001±2002. Coho salmon escapement was es- method). Escapement estimates assuming one redd timated by the strati®ed index approach for the per female were made by multiplying the number Noyo River during 2001±2002. Coho salmon and ESTIMATING SALMON AND STEELHEAD REDD ESCAPEMENT 289

FIGURE 3.ÐCumulative mean density of coho salmon and steelhead (ϮSE) plotted against the number of sample reaches for (A) the Noyo River, (B) Caspar Creek, (C) Hare Creek, (D) the Little River, and (E) Pudding Creek.

steelhead escapement was estimated with a strat- the Noyo River and resulting escapement estimates i®ed index approach in Caspar, Hare, and Pudding compared to capture±recapture estimates. creeks and Little River for 2001±2002. Speci®- Capture±recapture method.ÐSteelhead escape- cally, we divided the streams into 0.5-km segment in the Noyo River was estimated using the ments, developed performance curves of redd area Petersen capture±recapture method during 2000, densities (Figure 3b±e), randomly selected the 2000±2001, 2001±2002, and 2002±2003 (Krebs number of segments indicated by the performance 1989). During 2000 steelhead were captured, curves, and multiplied the average density by the marked, and recaptured using gill nets set in the length of spawning habitat in each stream. These lower river, at the ECS, in fyke traps set throughout estimates were compared with estimates from sur- the river, and by anglers. During 2000±2001 a weir veying the entire river and capture±recapture es- was operated in the lower river and ®sh were cap- timates. To further evaluate this method during tured, marked, and recaptured at the weir, at the 2002±2003, only nine reaches were surveyed in ECS, in fyke traps set throughout the river, by 290 GALLAGHER AND GALLAGHER anglers, and during spawning surveys. During by correlation. Statistical signi®cance was ac- 2001±2002 and 2002±2003 steelhead were cap- cepted at P less than 0.05. tured, marked, and recaptured by angling, at the ECS, in fyke traps set throughout the river, and Results during spawning surveys. Steelhead redd observer ef®ciency based on ¯ag Coho salmon populations were estimated by recaptures during 2002±2003 was 0.74 (SE ϭ capture and recapture of carcasses during spawn- 0.02) and was very similar to the ®eld observer ing surveys in all streams following the Jolly± ef®ciency of 0.75 (SE ϭ 0.14). Coho salmon redd Seber method, or the Schnabel method when re- observer ef®ciency based on ¯ag recaptures was captures were less than seven (Krebs 1989). Dur- 0.64 (SE ϭ 0.10). There was no difference in the ing 2002±2003 live coho salmon were captured percentage of redds smaller than 1.5 m2 and redds and tagged in the lower Noyo River using gill nets larger than 1.5 m2 observed more than once (t ϭ and recaptured during spawning surveys; we es- 1.06; P ϭ 0.31; df ϭ 16); however, the power of timated escapement using the Peterson method. this test was low (␤ϭ0.06). Weekly stream¯ow Known numbers of coho salmon were released and water visibility were signi®cant in predicting above the Noyo River ECS during 2000±2001, weekly ¯ag-based observer ef®ciency (ANOVA: F 2001±2002, and 2002±2003. ϭ 41.8; P Ͻ 0.001; df ϭ 66), and the resulting Area-under-the-curve estimates.ÐSpawning pop- equation (equation 3) was used to predict observer ulation estimates each year were also derived from ef®ciency for 2000±2001 and 2001±2002, that is, live ®sh observations using the AUC method (En- ϭ glish et al. 1992; Hilborn et al. 1999). Steelhead Observer efficiency 0.435 stream residence time (rt) was estimated separately Ϫ (0.00278 ϫ streamflow) for tributaries and main-stem sections by averag- ϩ (0.256 ϫ visibility). (3) ing observations of ®sh on redds, time between capture and recapture of tagged ®sh, and from data Predicted observer ef®ciency was 0.74 (SE ϭ from Shapovalov and Taft (1954) and Korman et 0.03) for 2000±2001 and 0.67 (SE ϭ 0.02) for al. (2002), and was 12.6 and 41.3 d, respectively. 2001±2002. Treating weeks as samples, predicted Coho salmon rt was 11 d (Beidler and Nickelson and estimated observer ef®ciency was not different 1980). Chinook rt of 9.3 d was the average of among years (ANOVA: H ϭ 3.62; P ϭ 0.17; df values presented by Parken et al. (2003) and Neil- ϭ 2). son and Geen (1981). Observer ef®ciency (v), the The percentage of steelhead redds still measur- ratio of total ®sh seen to the total present (Korman able after 2 weeks was 73.4%, whereas only 39% et al. 2002), was estimated by dividing the total of coho salmon redds and 43% of Chinook salmon number of ®sh of each species observed during redds were still measurable after 2 weeks during spawning surveys by the capture±recapture esti- 2002±2003. If surveys were conducted monthly mates each season. Thus, con®dence intervals for only 25% of steelhead redds, 18% of coho salmon AUC and capture±recapture estimates were inter- redds, and 14% of Chinook salmon redds would related. still have been measurable. After 8 weeks only 1% Data analysis.ÐPhysical characteristics of of steelhead, 0.2% of coho salmon, and no Chi- redds and associated variables were compared by nook salmon redds were still measurable. means of correlation, logistic regression, and Mann±Whitney U-ort-tests. Signi®cance of var- Classi®cation of Redd Species iables in predicting redd species was based on ex- Logistic regression reduced uncertainty in redd amination of the signi®cance of Wald's z-values. identi®cation. Field uncertainty in redd identi®- Population estimates were compared with ANOVA cation was 16% during 2000, 22.4% during 2000± or the Kruskal±Wallis ANOVA on ranks when 2001, 18.2% during 2001±2002, and 11.1% during standard kurtosis P-values were less than 0.05. 2002±2003. The apparent error rate from logistic Correlation was used to determine whether redd regression was 3.9% (i.e., in the training data set counts or redd area escapement estimates were re- known-species redds [Tables 1±2], only 8 out of lated to capture±recapture or AUC escapement es- 204 redds were misclassi®ed by logistic regres- timates by treating year- and river-speci®c data for sion). When this model (equation 1) was applied each species as samples. Relationships between to all redds observed during 2000±2001 and 2001± redd sizes and female fork lengths were examined 2002, no redds were classi®ed as coho after 16 ESTIMATING SALMON AND STEELHEAD REDD ESCAPEMENT 291

FIGURE 4.ÐFrequency distributions for female coho salmon and steelhead fork length (upper panels) and redd size (lower panels) in several coastal Mendocino County streams, 2001±2003.

February, the last day live or carcass coho salmon Ͻ 0.001; and K±S ϭ 0.12, P Ͻ 0.009, respec- were observed. All known steelhead and coho tively), and were skewed towards larger size ®sh salmon redds observed during 2002±2003 were (Figure 4a). Steelhead and coho salmon redd sizes correctly predicted to species by equation (1). were not normally distributed (K±S Ͻ 0.11; P Ͻ Three of 44 known steelhead redds (6.8%) ob- 0.02) and were skewed towards smaller redds (Fig- served in the American River during 2002±2003 ure 4b). were misclassi®ed by equation (1). The apparent error rate for classi®cation of Chi- For discrimination of steelhead and coho salm- nook and coho salmon redds (equation 2) was on, only redd area and the date redds were ob- 5.9%. Only pot substrate and redd area were sig- served were signi®cantly associated with predict- ni®cant in classifying Chinook and coho salmon ing species (Wald's z ϭ 11.9 and 18.09, respec- redds (Wald's z ϭ 5.88 and 4.03; P ϭ 0.015 and tively; P Ͻ 0.001). Year and river were not sig- 0.04, respectively). Only ®ve Chinook salmon ni®cantly associated with predicting species redds were positively identi®ed during 2002± (Wald's z ϭ 0.02, P ϭ 0.88; and z ϭ 0.08, P Ͼ 2003, so it was not possible to examine river and 0.93, respectively). Distance from the river mouth year effects on predicting redd species or rela- was not signi®cant in predicting species (Wald's z tionships between redd size and female size. The ϭ 0.53; P ϭ 0.47). For redds where ®sh were low number of known redds used in the training observed in enough detail to estimate ®sh length, data set for logistic regression and the lack of mul- fork length was not signi®cantly correlated with tiple years' data limited the evaluation of this mod- pot size (r ϭ 0.05; P ϭ 0.62) or redd size (r ϭ el. 0.06; P ϭ 0.57) and was not signi®cantly associated with predicting species (Wald's z ϭ 0.98; P Escapement Estimates ϭ 0.32). Steelhead and coho salmon fork lengths The uncertainty associated with each method of were not different in 2000±2001 (u ϭ 6787; P ϭ estimating coho salmon escapement, while gen- 0.05) nor in 2001±2002 (t ϭ 1.27, p ϭ 0.21; Table erally higher for capture±recapture and AUC es- 2), were not normally distributed (K±S ϭ 0.15, P timates, overlaps the point estimates, suggesting 292 GALLAGHER AND GALLAGHER

FIGURE 5.ÐCoho salmon population estimates in several coastal Mendocino County streams, 2000±2003. Panel (A) shows estimates for the area above the Noyo River egg collecting station in several time periods; panels (BϪD) show estimates for various sites during 2002±2003, 2001±2002, and 2000±2001, respectively. The thin lines are 95% con®dence intervals for the carcass capture±recapture estimates and observer uncertainty in the area-under- the-curve (AUC) estimates, the uncertainty in redd identi®cation for the redd area and one-redd-per-femaleestimates, and the SE for the strati®ed index redd area estimates. that all methods were similar (Figure 5a±d). Treat- low (␤ϭ0.05). Escapement estimates based on ing years as samples known numbers of coho salm- one redd per female were not different from AUC on released above the ECS were not signi®cantly estimates (ANOVA: F ϭ 3.39; P ϭ 0.09; df ϭ 30), different from AUC and redd area escapement es- yet the power of this test was low (␤ϭ0.05). timates (ANOVA: F ϭ 6.54, P ϭ 0.06, df ϭ 8; Treating rivers as samples, strati®ed index based Figure 5a) nor were they different from estimates escapement estimates for coho salmon during based on assuming one redd per female (ANOVA: 2001±2002 were not signi®cantly different from F ϭ 6.30; P ϭ 0.06; df ϭ 8). However, the power AUC estimates (ANOVA: F ϭ 0.41, P ϭ 0.54, df of these tests was low (␤ϭ0.51 and 0.50, re- ϭ 30, ␤ϭ0.05; Figure 5b). spectively). The coho salmon carcass based The uncertainty associated with estimating capture±recapture estimate above the ECS, made steelhead escapement by the capture±recapture only during 2002±2003 because of low numbers method and the AUC was large and overlaps that of recaptures in other years, was much lower than of other methods, suggesting that all methods gave the known release and other estimates (Figure 5a). similar results (Figure 6a±c). Treating years as Treating years as samples and including data from samples steelhead capture±recapture escapement all streams, coho salmon carcass-based population estimates in the Noyo River (Figure 6a) were not estimates were not signi®cantly different from signi®cantly different from redd area or strati®ed redd area estimates (ANOVA: F ϭ 3.13, P ϭ 0.12, index-based estimates (ANOVA: F ϭ 1.20 and df ϭ 30; Figure 5b±d). The power of this test (␤ 0.15; P ϭ 0.35 and 0.73, respectively; df ϭ 12). ϭ 0.24) was low. Coho salmon carcass-based es- The power of these tests was low (␤Ͻ0.06). Steel- timates were signi®cantly lower than assuming one head capture±recapture estimates were signi®- redd per female (ANOVA: F ϭ 13.57; P ϭ 0.04; cantly different from those based on one redd per df ϭ 15; ␤ϭ0.90). Coho salmon AUC and redd female (ANOVA: F ϭ 11.85; P ϭ 0.04; df ϭ 8), area estimates did not signi®cantly differ (ANOVA: but the tests power was low (␤ϭ0.60). The AUC F ϭ 0.35; P ϭ 0.57; df ϭ 36), but the power was escapement estimates from the Noyo River were ESTIMATING SALMON AND STEELHEAD REDD ESCAPEMENT 293

FIGURE 6.ÐSteelhead population estimates in several Mendocino county streams, namely, (A) the Noyo River from 1999±2000 to 2002±2003, (B) four streams in 2002±2003, and (C) four streams in 2001±2002. The thin lines are 95% con®dence intervals for the capture±recapture and area-under-the-curve (AUC) estimates, the uncertainty in redd identi®cation for the redd area and one-redd-per-female estimates, and the SE for the strati®ed index redd area estimates. not signi®cantly different from those of the redd assuming one redd per female (ANOVA: F ϭ area (ANOVA: F ϭ 0.64; P ϭ 0.48; df ϭ 8), as- 13.11; P ϭ 0.006; df ϭ 21; ␤ϭ0.88). The AUC suming one redd per female (ANOVA: F ϭ 7.88; escapement estimates were not signi®cantly dif- P ϭ 0.07; df ϭ 8), or strati®ed index estimates ferent from strati®ed index estimates (ANOVA: F (ANOVA: F ϭ 0.19; P ϭ 0.69; df ϭ 8). However, ϭ 0.04; P ϭ 0.85; df ϭ 17). However, the power the power of these tests was low (␤Ͻ0.44). Treat- of these tests was low (␤ϭ0.05). ing years as samples and including all streams As with the coho salmon and steelhead escape- data, AUC escapement estimates were not signif- ment estimates, the uncertainty associated with the icantly different from redd area estimates (ANOVA: different Chinook salmon escapement estimate F ϭ 0.64, P ϭ 0.48, df ϭ 21; Figure 6a±c). The methods overlapped, was large for the capture± AUC estimates were signi®cantly different from recapture and AUC methods, and indicates that all 294 GALLAGHER AND GALLAGHER

to 6.91. In the Noyo River over 2 years Chinook salmon averaged one redd per female. Redd counts signi®cantly re¯ect Chinook and coho salmon and steelhead escapement (Figure 8a±c). Treating years as samples, coho salmon redd counts and known numbers of females above the ECS were signi®cantly correlated (r ϭ 0.99; P ϭ 0.04). Treating years as samples and including all streams data, coho salmon redd counts and capture±recapture escapement estimates were signif- icantly correlated (r ϭ 0.83, P ϭ 0.001, n ϭ 11; Figure 8a). Similarly, coho salmon redd counts were signi®cantly correlated with AUC escapement estimates (r ϭ 0.83; P Ͻ 0.001; n ϭ 14). FIGURE 7.ÐChinook salmon population estimates in Treating years as samples and including data from the Noyo River from 2000±2001 to 2002±2003. The thin all streams, steelhead redd counts were signi®- lines are 95% con®dence intervals for the capture±re- cantly correlated with AUC escapement estimates capture and AUC estimates and the uncertainty in redd ϭ ϭ ϭ identi®cation for the redd area and one-redd-per-female (r 0.82, P 0.003, n 10; Figure 8b). With estimates. only 2 years of data for Chinook salmon it was not possible to correlate redd counts with capture± recapture estimates, although they appear related methods produced similar estimates (Figure 7). (Figure 8c). Chinook salmon were only observed in the Albion (2002±2003 only) and Noyo rivers. The Albion Discussion River was not surveyed completely in 2002±2003 We were able to account for and reduce many such that it was not possible to make escapement sources of bias and uncertainty in redd counts. By estimates. Only two Chinook salmon carcasses marking redds and reexamining ¯agged redds on were marked and none were recaptured during subsequent surveys we were able to account for 2000±2001 such that capture±recapture estimates undercounting errors (i.e., missed redds). Because were not made for this season. Although sample ¯ag and ®eld observer ef®ciency was not different, sizes were small (n ϭ 2), treating years as samples, it appears that marked (¯agged) and unmarked (no Chinook salmon capture±recapture estimates did ¯ags and assumed to be new) redds were equally not differ signi®cantly from redd area estimates detectable as were small and large redds. Rather (ANOVA: F ϭ 0.36; P ϭ 0.66; df ϭ 4) or from than examine sources of individual variation in estimates based on one redd per female (ANOVA: redd counts, we estimated it for all surveys and F ϭ 1.86; P ϭ 0.40; df ϭ 4). The power of these averaged it for the season, which tends to minimize tests was low (␤ϭ0.05 and 0.11, respectively). the effects of individual errors (Krebs 1989). Dun- Based on capture±recapture and AUC estimates, ham et al. (2001) attributed variability in redd coho salmon and steelhead females appear to make counts to differences among individual surveyors more than one redd. Coho salmon females released and redd and habitat characteristics, yet did not above the ECS averaged 1.25 (SE, 0.15) redds per examine the effect of stream¯ow or turbidity. In female (range ϭ 1.02±1.54) over 3 years. Based this study, water visibility and stream¯ow had a on capture±recapture estimates of coho salmon strong effect on redd detection, and we were able carcasses the average number of redds per female to use these variables to predict observer ef®ciency over 3 years in all streams was 4.61 (range ϭ 1.80± for years it was not ®eld estimated. Although we 7.04). The average number of redds per coho salm- did not account for overcounting redds (false iden- on female based on AUC estimates over 3 years ti®cations), several factors suggest this was not a in all streams was 1.70 and ranged from 0.50 to concern for this study. The survey protocol had a 3.19. The average number of steelhead redds per redd classi®cation category called ``test,'' and sur- female over 3 years based on capture±recapture veyors were instructed to use this for redds or estimates was 1.93 (SE ϭ 0.47) and ranged from channel features that looked like redds but uncer- 1.02 to 2.43. The average number of steelhead tainty existed as to whether these features actually redds per female based on AUC estimates over 3 were redds. Redds classi®ed as test were reex- years in all streams was 3.46 and ranged from 1.80 amined on subsequent surveys and if they had not ESTIMATING SALMON AND STEELHEAD REDD ESCAPEMENT 295

FIGURE 8.ÐRelationships between redd counts and salmonid population estimates in several Mendocino County streams, 2000±2001 and 2002±2003. Individual panels are as follows: (A) redd counts relative to the number of coho salmon released above the Noyo River egg collecting station; (B) redd counts relative to capture±recapture estimates for coho salmon for ®ve streams; (C) redd counts relative to area-under-the-curve (AUC) estimates for steelhead for ®ve streams; and (D) redd counts relative to capture±recapture estimates for Chinook salmon.

changed were left in this category; these redds redd counts were not different from AUC or cap- were not included in further analysis. Field crews ture±recapture estimates among years, suggesting worked in pairs and were instructed to confer on that biweekly surveys encountered redds as well redd species identi®cation. All redds, including as weekly surveys. Since redds disappeared and a those ®eld classi®ed as test, were measured, and, large percentage were not measurable after as little as part of the measuring process, surveyors ex- as 2 weeks, we recommend that surveys be con- amined redds in some detail and were less likely ducted less than 13 d apart or as soon after large to include channel features which were not actu- ¯ow events as possible throughout the spawning ally redds. season. Surveying weekly rather than biweekly The length of time redds remain visible and will increase the cost of these surveys. Survey measurable can cause counting errors and may af- periodicity should be within the residence time of fect the use of redd counts for population moni- the species of interest so that AUC can also be toring. Dunham et al. (2001) found redd age was estimated. Surveying once at the end of the spawn- signi®cantly associated with counting errors, and ing season for all species (over 4 months) would some redds in their study were over 4 weeks old. not produce realistic results. Even if surveys were They and other researchers (Beland 1996; Rieman conducted once after Chinook and coho salmon and Myers 1997; Isaak et al. 2003) counted redds spawning occurred and again at the end of steel- once or twice at the assumed end of the spawning head spawning, the results would be of little use. season. In this study we surveyed weekly or bi- A larger percentage of steelhead redds remained weekly throughout the season such that the oldest measurable longer than Chinook and coho salmon redds encountered would have been aged less than redds because most steelhead spawn later than 13 d. Observer ef®ciency was not different be- coho and Chinook salmon, after the usual time of tween years, and escapement estimates based on large stream¯ow events. 296 GALLAGHER AND GALLAGHER

Classi®cation of Redd Species cause Chinook salmon are larger than coho salm- The discrimination function from logistic re- on. Although we found that steelhead and coho gression reduced species uncertainty by an average salmon fork lengths and redd sizes were not re- of 15% and thus decreased this source of error in lated, we were unable to examine this relationship the use of redd counts for population monitoring. for Chinook salmon because so few ®sh were ob- The apparent error rate from logistic regression of served on redds. The difference in pot substrate 3.9% was lower than that reported by other re- size between these species may be because Chi- searchers using multivariate techniques to classify nook salmon excavate their nests deeper than coho salmonid redds. Fukushima and Smoker (1998) salmon (DeVries 1997) or because they prefer dif- found water depth and velocity and stream gradient ferent substrate sizes (Hampton and Aceituno signi®cant in discriminating sockeye and pink 1988). However, pot depths were not different be- salmon redds, but report an error rate of 33%. Zim- tween the two species in this study (Table 2). Redd merman and Reeves (2000) found water depth and size and substrate used to differentiate Chinook substrate signi®cant in separating anadromous and and coho salmon redds were not different from resident steelhead redds using stepwise discrimi- that reported in other areas (Burner 1951), sug- nation and report an error rate greater than 28%. gesting that equation (2) may be useful in other The model based on steelhead and coho salmon areas where these species overlap. This model will redd area and date of spawning appears spatially need further evaluation and more data to validate and temporally robust for distinguishing between its applicability over multiple years or in other the two species and may be applicable to other systems. streams where these species co-occur. All known steelhead and coho salmon redds observed during Escapement Estimates 2002±2003 were correctly classi®ed by equation Redd area.ÐAlthough we did not quantitatively (1), and only 6.8% of known steelhead redds in evaluate the assumption that redd size is related the American River were misclassi®ed. Year and to the number of redds a female salmonid makes river were not signi®cant in predicting redd spe- (e.g., the redd area method), several of our results cies. The physical features of redds which con- suggest that this was valid. Redd area escapement tribute to species identi®cation (i.e., size and date estimates were not different from known numbers of spawning) appear to be consistent over a large of coho salmon released above the ECS. The redd geographic area, suggesting they are driven by area and strati®ed redd area escapement estimates some biologically inherent characteristics of the were not signi®cantly different from other meth- species and not by stream geomorphic or water- ods, except assuming one redd per female which shed features. Steelhead redds may be smaller than overestimated escapement. The number of redds coho and Chinook salmon redds because steelhead per female was greater than 1.0 for all methods are iteroparous. Female steelhead and coho salmon and were within the range used in the redd area fork lengths were not signi®cantly different and method. Redd size was not related to female size. redd sizes were not related to ®sh size. Female Fork lengths were not normally distributed and steelhead may not expend all their energy making were skewed towards larger ®sh, whereas redd siz- redds because they survive to spawn again in later es were skewed towards smaller redds (Figure 4), years, whereas coho and Chinook salmon die after suggesting redd size is related to female effort. spawning. While Burner (1951) observed that The redd area method accounts for multiple redds salmon continue to dig above the nest pockets of per female and smaller redds have lower impor- redds after spawning activity ceased, Briggs tance in escapement estimates. (1953) states that both male and female steelhead The redd area method is sensitive to the female: drift downstream after spawning is complete. male ratio, the size and range of redds, and errors The logistic regression equation developed to in counting and measuring redds. We used female distinguish between Chinook and coho salmon to male ratios based on live ®sh observations in redds was encouraging and, although more known each stream, or when too few ®sh were observed, redd data will probably improve this relationship, we assumed it was one to one. Average coho salm- it appears that these species redds can be identi®ed on and steelhead redd sizes were very similar each based on physical characteristics. Chinook and year, and we only used known redd areas for es- coho salmon redds differed in pot substrate and timating the female effort ranges. Training of sur- redd size. The difference in redd size may be be- veyors and efforts to reduce redd counting errors ESTIMATING SALMON AND STEELHEAD REDD ESCAPEMENT 297 described above helped reduce these potential ments in redd counts and redd identi®cation and sources of error. realistic con®dence bounds from the strati®ed in- Strati®ed index.ÐOf the methods examined in dex approach, suggests it may be useful for mon- this study, Chinook and coho salmon and steelhead itoring and detecting long term trends (Maxell escapement was most precisely, cost effectively, 1999). and reliably estimated using redd areas in a strat- Capture±recapture estimates.ÐThe capture±re- i®ed index approach. Irvine et al. (1992) found capture estimates had large con®dence bounds ow- that strati®ed index estimates were always similar ing to low numbers of marked and recaptured ®sh, to capture±recapture estimates. Strati®ed index es- and carcass-based estimates appeared to under- capement estimates were not signi®cantly different estimate populations (Figures 5±7). Carcass pop- from redd area, capture±recapture, or AUC esti- ulation estimates require unique individual marks, mates, but were signi®cantly different from esti- a short duration between surveys, and survey of mates assuming one redd per female for steelhead. the entire river to increase the chance of recap- When tested in the third year of the study, strati®ed turing marked ®sh. Increasing the periodicity of index estimates were not different from AUC, cap- surveys during 2002±2003 allowed coho salmon ture±recapture, or redd area escapement estimates. carcass-based estimates above the ECS, yet this Although the power of these tests was low and the drastically underestimated escapement and did not uncertainty associated with the point estimates greatly decrease uncertainty in the escapement es- high, they overlapped for all escapement estimates timates for other streams (Figure 5). To observe, except for the steelhead estimates that assumed tag, and recover enough carcasses to reduce the one redd per female (Figures 5±6). Uncertainty uncertainty with these estimates might require sur- associated with the strati®ed index estimates was veys on a daily basis because high ¯ows between lower than that of AUC and capture±recapture es- surveys can bury, wash away, or otherwise de- timates. The one redd per female and redd area crease the chance of ®nding carcasses (Cederholm estimates were total counts, and their uncertainty et al. 1989). Too few steelhead carcasses were ob- was that associated with redd identi®cation such served to estimate escapement using the capture± that these methods did not provide statistical de- recapture method. Live ®sh capture±recapture pro- scriptions of uncertainty. Krebs (1989) states that grams require active capture techniques which are total counts are often of dubious reliability and susceptible to mechanical failure in moderate-to- recommends sample counts for population esti- high water years, and that ®sh are tagged, handled, mation. The strati®ed index estimates can be and their movements impeded. Permanent or tem- viewed as a specialized form of block sampling porary counting structures are expensive to build, where the stream segments are blocks and the en- maintain, and operate; are susceptible to mechan- tire length of spawning habitat in a stream is the ical failure; and, coupled with extensive permitting census zone. The mean and variance is calculated and access requirements, limit their use over a from the blocks and multiplied by the census zone. large geographic area. Shapovalov and Taft (1954) The use of performance curves reduced cost by could not operate traps on Waddell Creek, Cali- reducing the amount of the census zone (i.e., fornia, during high ¯ows, and seining to capture spawning habitat in each stream) by about 60%, steelhead in the Rouge River, Oregon, was limited allowing more coverage with the same effort while by high ¯ows (Everest 1973). reducing variance in escapement estimates. This Area-under-the-curve estimates.ÐThe AUC es- method was shown to work for a variety of water timates were not different from total counts of years and streams, is not susceptible to mechanical coho salmon above the ECS or from capture± failure, and ®sh are not handled, tagged, or their recapture estimates of Chinook salmon, coho movements impeded. This approach may be useful salmon, and steelhead. This suggests that the use and applicable to examine and monitor metapop- of residence time from the literature for Chinook ulation dynamics (Rieman and McIntyre 1996) im- and coho salmon and estimated for steelhead in portant for the recovery of these threatened species the Noyo River and applied to other streams in (Isaak et al. 2003). Redd counts and escapement this study was not unrealistic. However, observer from strati®ed redd areas was signi®cantly cor- ef®ciency and residence time should be estimated related with ®sh released above the ECS (coho) annually for each stream and estimated throughout and capture±recapture estimates, thus these esti- each season (English et al. 1992; Manske and mates track population trends (Figure 8). This, Schwarz 2000) because the AUC method is very combined with reduced uncertainty from improve- sensitive to these variables (Hilborn et al. 1999). 298 GALLAGHER AND GALLAGHER

English et al. (1992) found the AUC method is Acknowledgments also sensitive to variability in survey time. The The Mendocino Redwood Company allowed ac- AUC con®dence bounds in this study were esti- cess to the rivers and the use of their roads. Per- mated from observer ef®ciencies which were tied sonnel from the California State Department of to the capture±recapture estimates. One of the ma- Fish and Game's Central Coast Salmon and Steel- jor shortcomings of the AUC is that it lacks a head Resource Assessment Program, North Coast rigorous statistical method for calculating con®- Watershed Assessment Program, and the Steelhead dence bounds and when estimated requires inten- Research and Monitoring Program; the Campbell sive bootstrap computer simulation and indepen- Timberland Management Company; and the Na- dent capture±recapture estimates for their calcu- tional Marine Fisheries Service's Santa Cruz Sci- lation (Korman et al. 2002; Parkin et al. 2003). ence Center helped collect data for this study. Mor- Where the AUC has been used to estimate sal- gan Knechtle helped with ECS data analysis. We monid escapement, residence time and observer thank Mark Gard, Glen Szerlong, John Hannon, ef®ciency have been estimated using independent and two anonymous reviewers for their critical ex- capture±recapture programs (Shardlow et al. 1987; amination of this manuscript. Jones et al. 1998, Korman et al. 2002; Parken et al. 2003) which are capable of estimating escape- References ment without the use of the AUC. Because of the Beidler, W. M., and T. E. Nickelson. 1980. An evaluation need to better de®ne estimates of residence time of the Oregon Department of Fish and Wildlife stan- and observer ef®ciency (Manske and Schwarz dard spawning ®sh survey system for coho salmon. 2000) and the need for intensive simulation to es- Oregon Department of Fish and Wildlife, Infor- timate statistical descriptors of uncertainty, the mation Report Series, Fisheries 80-9, Portland. AUC may prove too cumbersome for long-term Beland, K. F. 1996. The relationship between redd counts and Atlantic salmon (Salmo salar) parr pop- monitoring of salmonids in coastal northern Cal- ulations in the Dennys River, Maine. Canadian Jour- ifornia. nal of Fisheries and Aquatic Sciences 53:513±519. Reduction of counting errors and uncertainty in Briggs, J. C. 1953. The behavior and reproduction of redd identi®cation, combined with biweekly sur- salmonid ®shes in a small coastal stream. California veys throughout the spawning period of Chinook Department of Fish and Game, Fish Bulletin 94. Burner, C. J. 1951. Characteristics of spawning nests of and coho salmon and steelhead, allowed us to es- Columbia River salmon. U.S. Fish and Wildlife Ser- timate escapement in a strati®ed index sampling vice Fishery Bulletin 61:97±110. design using redd areas. This resulted in precise, Busby, P., T. Wainwright, G. Bryant, L. Lierheimer, R. reliable, and cost-effective escapement estimates Waples, W. Waknitz, and I. Lagomarsino. 1996. compared with more conventional approaches. We Status review of West Coast steelhead from Wash- recommend that surveys be conducted 7±13 d ington, Idaho, Oregon, and California. NOAA Tech- nical Memorandum NMFS-NWFSC-27. apart, that observer ef®ciency in redd counts be Cederholm, C. J., D. B. Houston, D. L. Cole, and W. J. estimated for each survey and averaged for the Scarlett. 1989. Fate of coho (Oncorhynchus kisutch) season, that redd identi®cation be based on the carcasses in spawning streams. Canadian Journal of logistic regression models presented here (with Fisheries and Aquatic Sciences 46:1347±1355. continued development and testing of the Crisp, D. T., and P. A. Carling. 1989. Observations on sitting, dimensions, and structure of salmonid redds. Chinook±coho salmon model as data become Journal of Fish Biology 34:119±134. available), and that escapement be estimated using DeVries, P. 1997. Riverine salmonid egg burial depths: redd areas in a strati®ed index approach. The re- review of published data and implications for scour lationship between redd size and the number of studies. Canadian Journal of Fisheries and Aquatic redds a female builds needs further evaluation. Sciences 54:1685±1698. Dunham, J., B. Rieman, and K. Davis. 2001. Sources This approach appears promising for long term and magnitude of sampling error in redd counts for monitoring of individual populations and meta- bull trout. North American Journal of Fisheries populations (Isaak et al. 2003) in a randomized Management 21:343±352. block design similar to that applied to salmonids English, K. K., R. C. Bocking, and J. Irvine. 1992. A in Oregon (Jacobs et al. 2001). Evaluations of the robust procedure for estimating salmonid escapement based on the area-under-the-curve method. power of the data from strati®ed index redd area Canadian Journal of Fisheries and Aquatic Sciences escapement estimates for long-term trend detec- 49:1982±1989. tion should be conducted. Everest, F. H. 1973. Ecology and management of sum- ESTIMATING SALMON AND STEELHEAD REDD ESCAPEMENT 299

mer steelhead in the Rogue River, Oregon. State and E. Bjorkst edt. 2000. Viable salmonid popu- Game Commission, Corvallis, Oregon. lations and the recovery of evolutionarily signi®cant Fukushima, M., and W. M. Smoker. 1998. Spawning units. NOAA Technical Memorandum NMFS- habitat segregation of sympatric sockeye and pink NWFSC-42. salmon. Transactions of the American Fisheries So- Meffe, G. K. 1986. Conservation genetics and the man- ciety 127:253±260. agement of endangered ®shes. Fisheries 11(1):14± Gallagher, S. P., and M. F. Gard, 1999. Relationship 23. between Chinook salmon (Oncorhynchus tshawyts- Myers, J. M., R. G. Kope, G. J. Bryant, D. Teel, L. J. cha) redd densities and PHABSIM-predicted habitat Lierheimer, T. C. Wainwright, W. S. Grand, F. W. in the Merced and Lower American rivers, Cali- Waknitz, K. Neely, S. T. Lindley, and R. S. Waples. fornia. Canadian Journal of Fisheries and Aquatic 1998. Status review of Chinook salmon from Wash- Sciences 56:570±577. ington, Idaho, Oregon, and California. NOAA Tech- Hampton, M. and M. Aceituno. 1988. Direct observa- nical Memorandum NMFS-NWFSC-35. tion techniques for habitat use criteria development Neilson, J. D., and G. H. Geen. 1981. Enumeration of on the Trinity River, Trinity County, California. spawning salmon from spawner residence time and Pages 159±180 in K. Bovee and J. R. Zuboy, edi- aerial counts. Transactions of the American Fish- tors. Proceedings of a workshop on the development eries Society 110:554±556. and evaluation of habitat suitability criteria. U.S. Orcutt, D. R., B. R. Pulliam, and A. Arp. 1968. Char- Fish and Wildlife Service Biological Report 88. acteristics of steelhead trout redds in Idaho streams. Hilborn, R., B. Bue, and S. Sharr. 1999. Estimating Transactions of the American Fisheries Society 97: spawning escapements from periodic counts: a com- 42±45. parison of methods. Canadian Journal of Fisheries Parken, C. K., R. E. Bailey, and J. R. Irvine. 2003. and Aquatic Sciences 56:888±896. Incorporating uncertainty into area-under-the-curve Irvine, J. R., R. C. Bocking, K. K. English, and M. and peak count salmon escapement estimation. Labelle. 1992. Estimating coho (Oncorhynchus kis- North American Journal of Fisheries Management utch) spawning escapements by conducting visual 23:78±90. surveys in areas selected using strati®ed random and Platts, W. S., W. F. Meghan, and G. W. Minshall. 1983. strati®ed index sampling designs. Canadian Journal Methods for evaluating stream, riparian, and biotic of Fisheries and Aquatic Sciences 49:1972±1981. conditions. U.S. Forest Service, Intermountain For- Isaak, D. J., F. R. F. Thurow, B. E. Rieman, and J. B. est and Range Experiment Station, General Tech- Dunham. 2003. Temporal variation in synchrony nical Report INT-138, Ogden, Utah. among Chinook salmon (Oncorhynchus tshawyts- Reingold, M. 1965. A steelhead spawning study. Idaho cha) redd counts from a wilderness area in central Wildlife Review 17:8±10. Idaho. Canadian Journal of Fisheries and Aquatic Rieman, B. E., and J. D. McIntyre. 1996. Spatial and Sciences 60:840±848. temporal variability in bull trout redd counts. North Jacobs, S., J. Firman, and G. Susac. 2001. Status of American Journal of Fisheries Management 16: Oregon coastal stocks of anadromous salmonids, 132±141. 1999±2000. Oregon Department of Fish and Wild- Rieman, B. E., and D. L. Myers. 1997. Use of redd life, Monitoring program report number OPSW- counts to detect trends in bull trout (Salvelinus con- ODFW-2001- 3, Portland. ¯uentus) populations. Conservation Biology 11: Jones, E. L., T. J. Quinn, and B. W. Van Allen. 1998. Observer accuracy and precision in aerial and foot 1015±1018. survey counts of pink salmon in a southeast Alaska Shardlow, T., R. Hilborn, and D. Lightly. 1987. Com- stream. North American Journal of Fisheries Man- ponents analysis of instream escapement methods agement 18:832±846. for Paci®c salmon (Oncorhynchus spp.). Canadian Korman, J., R. M. N. Ahrens, P. S. Higgins, and C. J. Journal of Fisheries and Aquatic Sciences 44:1031± Walters. 2002. Effects of observer ef®ciency, ar- 1037. rival timing, and survey life on estimates of es- Shapovalov, L. and A. C. Taft. 1954. The life histories capement for steelhead trout (Oncorhynchus mykiss) of the steelhead rainbow trout (Salmo gairdneri) and derived from repeat markϪrecapture experiments. silver salmon (Oncorhynchus kisutch) with special Canadian Journal of Fisheries and Aquatic Sciences reference to Waddell Creek, California, and rec- 59:1116±1131. ommendations regarding their management. Cali- Krebs, C. J. 1989. Ecological methodology. Harper & fornia Department of Fish and Game, Fish Bulletin Row, New York. 98. Manske, M., and C. J. Schwarz. 2000. Estimates of Susac, G. L., and S. E. Jacobs. 1999. Evaluation of stream residence time and escapement based on cap- spawning ground surveys for indexing the abun- ture±recapture data. Canadian Journal of Fisheries dance of winter steelhead in Oregon coastal basins: and Aquatic Sciences 57:241±246. annual progress report, 1 July 1997 to 30 June 1998. Maxell, B. A. 1999. A power analysis on the monitoring Oregon Department of Fish and Wildlife, Corvallis. of bull trout stocks using redd counts. North Amer- U.S. Of®ce of the Federal Register. 1997. Endangered ican Journal of Fisheries Management 19:860±866. and threatened species: threatened status for coho McElhany, P., M. Ruckelshaus, M. Ford, T. Wainwright, salmon in the southern Oregon/northern California 300 GALLAGHER AND GALLAGHER

coast evolutionarily signi®cant unit in California. Weitkamp, L. A., T. C. Wainwright, G. J. Bryant, G. B. Federal Register 62:87(6 May 1997):24588±24609. Milner, D. J. Teel, R. G. Kope, and R. S. Waples. U.S. Of®ce of the Federal Register. 1999. Endangered 1995. Status review of coho salmon from Wash- and threatened species: threatened status for two ington, Oregon, and California. NOAA Technical Chinook salmon evolutionarily signi®cant units Memorandum NMFS-NWFSC-24. (ESUs) in California: ®nal rule. Federal Register Zimmerman, C. E., and G. H. Reeves. 2000. Population 64:179(16 September 1999):50393±50415. structure of sympatric anadromous and nonanad- U.S. Of®ce of the Federal Register. 2000. Endangered and threatened species: threatened status for one romous Oncorhynchus mykiss: evidence from steelhead evolutionarily signi®cant unit in Califor- spawning surveys and otolith microchemistry. Ca- nia. Federal Register 65:110(7 June 2000):36074± nadian Journal of Fisheries and Aquatic Sciences 36094. 57:2152±2162.