Survival of Common Goldeneye Ducklings in Interior Alaska

Research Article

Survival of Common Goldeneye Ducklings inInterior Alaska

JOSHUA H. SCHMIDT,1 Department of Biology and Wildlife, University of Alaska, Fairbanks, Fairbanks, AK 99775, USA

ERIC J. TAYLOR,2 United States Fish and Wildlife Service, National Wildlife Refuge System, Alaska, Anchorage, AK 99503, USA

ERIC A. REXSTAD,3 Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK 99775, USA

Abstract

Duckling survival is an important component of waterfowl population dynamics, and we provide the first-known estimates of duckling survival for

common goldeneyes (Bucephala clangula ) at the northern limit of their range in Interior Alaska. We color-marked common goldeneye ducklings

from 91 broods and radio-marked a subset of the females (n¼ 39) from a nest-box population in the boreal forest during the summers of 2002

and 2003. We monitored 46 broods in 2002 and 2003 combined and estimated daily survival rates (DSR) and survival to 30 days of age using

program MARK. We modeled DSR in relation to year, linear trend across season, duckling age, female age, female body condition, initial brood

size, and daily precipitation. Model-averaged duckling survival estimates from the mean yearly hatch date to 30 days of age were 0.64 (95% CI,

0.37–0.90) and 0.67 (95% CI, 0.54–0.80) for 2002 and 2003, respectively. Our best-approximating model indicated that survival differed by year

and increased in a linear manner over the course of the 2002 season. Precipitation had a consistent negative effect on duckling survival in both

years across models, whereas duckling age did not explain much of the variation in daily survival rates. In light of the decline of many

populations of sea ducks, we suggest that more effort should be expended to obtain estimates of other population parameters for common

goldeneyes, and monitoring programs should attempt to estimate populations more precisely to identify population-level changes in the future.

(JOURNAL OF WILDLIFE MANAGEMENT 70(3):792–798; 2006)

Key wordsAlaska, boreal forest, Bucephala clangula, common goldeneye, duckling survival, population dynamics, program MARK, sea ducks.

Populations of common goldeneyes occur worldwide in northernboreal forests, and in Interior Alaska they reach the northern limitof their range (Eadie et al. 1995). Conditions at this latitude arelikely quite different from those found in the southern portions oftheir range, and populations may have developed unique life-history strategies in response to shorter breeding seasons,variations in food resources, or limited nesting sites. Data fromthe North American Waterfowl Breeding Population Surveyindicate that common goldeneye populations across NorthAmerica are probably stable (U.S. Fish and Wildlife Service[USFWS] 1999), but to our knowledge, no other information isavailable for this species in Interior Alaska, where it is likelyexperiencing conditions different from those of populations atlower latitudes. Recent information indicates that many species ofAlaskan sea ducks and some diving-duck species, such as scaup(Aythya spp.), are declining or deserve special attention (USFWS1999). These declines, coupled with unknown responses to rangelimitations, suggest that an increased effort to estimate thecomponents of common goldeneye population dynamics in Alaskais warranted.

Recruitment of young into the breeding population is importantfor understanding the population dynamics of waterfowl, and animportant component of recruitment is duckling survival (Johnsonet al. 1992, Hoekman et al. 2002). Survival estimates from otherportions of the breeding range indicate that brood survival isvariable but generally low (Eadie 1989, Wayland and McNicol

1994, Eadie et al. 1995), and variable weather and a shorterbreeding season in Alaska could result in lower duckling survival.Past studies have indicated that females usually begin breeding at2–3 years of age and can reproduce for many years (Eadie et al.1995, Ludwichowski et al. 2002, Milonoff et al. 2002), althoughthe average lifetime reproductive success averages just over 2independent offspring per female (Eadie et al. 1995). This issimilar to the life-history strategies of many species of sea ducksthat postpone breeding until 2 or 3 years of age (Bellrose 1980)but breed for many years.

There are many variables that may explain variation in ducklingsurvival in addition to geographic location. Brood size at hatchmay affect duckling survival (Guyn and Clark 1999, Smith et al.2005) by increasing predator detection or decreasing the ability ofthe female to efficiently brood young during inclement weather(Dzus and Clark 1997). Females with more breeding experiencemay be better able to care for their young and secure high-qualityhabitats, and female body condition can positively influence thesurvival of young (Yerkes 2000, Gendron and Clark 2002, Walkerand Lindberg 2005). The age of ducklings is often related to dailysurvival with younger ducklings surviving at a lower rate(Ringleman and Longcore 1982, Savard et al. 1991, Sargent andRaveling 1992, Flint and Grand 1997, Guyn and Clark 1999,Hoekman et al. 2004), and inclement weather can decrease thesurvival of prefledged ducklings (Moulton and Weller 1984,Johnson et al. 1992, Eadie et al. 1995).

Our objectives were to estimate daily survival rates (DSR) ofducklings throughout the brood-rearing period, produce estimatesof survival to 30 days of age (after which mortality is likely quitelow; Savard et al. 1991), and identify factors that explainedvariation in duckling survival. Factors affecting duckling survivalduring the first month after hatch may help managers concentrate

1 E-mail: [email protected] Present address: The Wildlife Society, Bethesda, MD 20814,USA3 Present address: Centre for Research into Ecological andEnvironmental Modelling, University of St. Andrews, St. Andrews,Scotland KY16 9LZ, United Kingdom

792 The Journal of Wildlife Management � 70(3)

effort on segments of the breeding population that fledge the mostyoung, such as older females or those nesting earlier in the season.Estimates of the relative effects of environmental conditions couldalso help managers understand fluctuations in duckling survivalthat are unrelated to management activities.

Study Area

We conducted our study in central Alaska, USA, approximately48 km east of Fairbanks on the Chena River State RecreationArea during the summers of 2002–2003. The study areaencompassed an approximately 102-km2 strip along the northand middle forks of the Chena River. Nest-boxes (n¼ 150) werelocated on sloughs, oxbows, ponds, and the Chena River atheights of 3–7 m above the ground. These boxes have beenmonitored and maintained since 1997, during which time, thenumber of nesting females has steadily increased. The sites weredominated by mixed stands of white spruce (Picea glauca), paperbirch (Betula papyrifera), black spruce (Picea mariana), and balsampoplar (Populus balsamifera). We obtained daily precipitation datafrom the Two Rivers National Weather Service weather station(64853055 00N, 146824042 00W), located within the study area.

Methods

We inspected nest-boxes weekly beginning in May to determineoccupancy, and we revisited active nests every 1 to 3 days todetermine egg-laying rates and to capture adult females on thenests. We candled all eggs to determine stage of incubation(Weller 1956) and numbered them with a permanent marker toidentify new or missing eggs. Revisits occurred until we capturedthe adult female or the clutch neared completion. We limitedsubsequent visits until late in incubation to reduce the possibilityof nest abandonment (Eadie et al. 1995). We assumed abandon-ment was caused by research activities when embryo developmentwas unchanged between nest visits after disturbing the female.

We captured most females on the nest during egg-laying byblocking the nest-box entrance. Upon initial capture of eachindividual female, we recorded measurements of culmen length,head length, tarsus length, and body mass and attached a stainlesssteel USFWS leg band, if no band was present. We also recordedbody mass and verified the band number on all subsequentrecaptures. Beginning in 1997, all successfully breeding femaleswere captured and banded yearly, and most day-old ducklingswere banded yearly since 1998. Because of this effort, approx-imately 90% of the breeding females captured in this populationeach year carried leg bands from previous capture events, allowingus to assign a minimum age to most females based on the numberof years since first capture (E. Taylor, USFWS, Anchorage, Alas.,USA, unpublished data). During late incubation, we revisited allactive nests and recaptured most incubating females. For femalesthat had been captured during egg-laying, we recorded only bodymass and candled all eggs in the clutch to estimate hatch dateassuming an incubation period of 28 days (Bellrose 1980).

At hatch, we marked all ducklings from most broods withplasticine-filled metal leg bands (ARANEA, Lodz, Poland; seeBlums et al. 1994), and colored their white cheek patches usingpermanent markers (Eadie 1989). Each brood received a uniquecolor combination that lasted 4–5 weeks, which allowed us to

identify nonradio-marked broods and was necessary to detect anybrood amalgamations. We monitored broods from the range ofhatch dates (7–28 Jun 2002 and 3 Jun–9 Jul 2003) each season andincluded nests from throughout the study site. The females wemonitored using these 2 methods were from all ages present in thebreeding population from first-time breeders, 2 years of age (basedon plasticine leg-bands), to females �8 years of age (based onnumber of years since first capture).

At hatch, in 2002 and 2003, we attached radio transmitters to 19and 20 adult females, respectively. In 2002, we affixed a 13-g, tail-mounted, very high frequency (VHF) radio (model G3, AVMInstrument Company, Ltd., Colfax, California), similar to themodel used by Poysa and Virtanen (1994), to the central 2 retrices.In 2003, we used a modified prong-and-suture mount similar tothat used by Mauser and Jarvis (1991) to affix a 9-g, VHF radiotransmitter (model A4430, Advanced Telemetry Systems, Inc.,Isanti, Minnesota) between the scapulars of the female. The tail-mounted transmitters we used in 2002 had low-retention rates andpoor signal strength, and the switch to the modified prong-and-suture-mounted transmitters in 2003 virtually eliminated thisproblem.

After transmitter attachment, we either released the female tothe water or placed her back in the nest with the ducklings,depending on the ambient temperature and the apparent stresslevel of the bird. In the transmittered group, we included onlyfemales known to have bred at least once previously to avoidpotential researcher-caused abandonment because of the extrahandling time necessary for attachment, and we observed no broodabandonment related to the extra handling. We were able toinclude first-time breeders in the analysis through the use of colormarks as described above. All procedures were approved by theInstitutional Animal Care and Use Committee at the Universityof Alaska, Fairbanks, USA (IACUC 02–20).

We relocated broods with a hand-held, Yagi antenna (AVMInstrument Company, Ltd., Colfax, California) every 3–5 days, ifpossible, and visually confirmed the identity of the brood, basedon the presence of the radioed female and the color marks on theducklings. We counted the number of ducklings, and we assumedthat ducklings not observed on subsequent visits had died duringthe previous interval. Ducklings were usually gathered around thefemale, enabling accurate counting, and duckling counts did notincrease during subsequent visits. We had no way of verifying thedeath of the ducklings, so our survival estimates could be biasedlow if ducklings permanently left broods undetected but remainedalive. We consider this to be unlikely because lone ducklings werenot sighted, and brood amalgamations were rare.

When possible, we continued to locate broods until they reached30 days of age. After that time, color marks began to fade, andadult females began leaving the study area, preventing us fromcontinuing to locate them. Although common goldeneyes do notfledge until ;8 weeks of age (Bellrose 1980), further monitoringwas not feasible. We assumed complete brood loss when thefemale was observed without her brood on 2 or more separate daysand did not display normal brood-protection behavior. Normalbehavior of females with broods included calling and attemptingto swim away from the observer rather than flying. Once per

Schmidt et al. � Common Goldeneye Duckling Survival 793

season, we used a fixed-wing aircraft to aid in locating the broodsthat had moved out of range of the hand-held antenna.

We determined survival in a similar manner as Ringelman andLongcore (1982) and Savard et al. (1991) by observing markedfemales and broods to determine daily survival rates. We estimatedduckling survival from hatching until 30 days of age by modelingDSR using the nest-survival module in the program MARK,which has been suggested for use with radiotelemetry data withunequal resighting intervals (White and Burnham 1999). Thesemodels were recently used by Walker and Lindberg (2005) forsimilar data to provide 30-day survival estimates for scaupducklings. We considered year, date, initial brood size, femaleage, female body condition (body mass relative to structural size),duckling age, and daily precipitation as potential explanatoryvariables, and we ranked models using an information-theoreticapproach (Burnham and Anderson 2002). We then used Akaike’sInformation Criterion (AICc) corrected for small sample size, toselect the best-approximating model (Anderson et al. 2000) andused model averaging to produce estimates of DSR (Burnham andAnderson 2002).

To obtain an index of female body condition at the time ofhatch, we used a procedure similar to that used by Gendron andClark (2002). Using SAS V.8 (SAS Institute, Cary, NorthCarolina), we conducted a principle components analysis, usingculmen length, head length, and tarsus length to calculate an indexof female structural size (PC I PROC PRINCOMP; SASInstitute 1999). We then conducted a linear regression (PROCREG; SAS Institute 1999) between body mass and PC I scoresand used the resulting residuals as indices of body condition(Sedinger et al. 1997, Gendron and Clark 2002).

The use of nest-survival models required 2 important assump-tions. The first was that the fates of individual ducklings wereindependent, and this assumption could have been violatedbecause of the dependence of fates among ducklings within abrood. For this reason, we applied a variance-inflation factor toour output before model selection to ensure that we were notoverly confident in a model that our data could not support(Anderson et al. 1994), and we then presented model-averagedestimates of survival to further account for model-selectionuncertainty (Burnham and Anderson 2002).

A second important assumption for this type of model was thatthe fates of ducklings were known. If the loss of ducklings wentundetected, survival estimates would be biased high. We onlydetermined 2 radioed females to have experienced total brood losswithin 30 days of hatch, and in both cases, total brood loss did notoccur until near the end of the 30 day monitoring period. Thegeneral pattern of mortality for most broods was a gradual loss ofducklings over time. We did not observe a pattern of highermortality for younger ducklings as has been reported for otherspecies (Savard et al. 1991, Grand and Flint 1996, Flint andGrand 1997, Guyn and Clark 1999, Walker and Lindberg 2005),and catastrophic mortality was rare. We conducted an additionalanalysis of the 2003 data to investigate the potential for a markereffect both alone and with the other covariates, and we found nodifference in survival rates between the 2 marker types. Also,within the radioed sample, broods moved extensively during thebrood-rearing period with ;45% moving �1 km from the nest

site. We believe that this was likely the reason that only a portionof the color-marked broods were successfully monitored. For thesereasons, we suggest that bias in survival rates due to differences indetectability between marker types was likely low, and therefore,we assert that we met the assumption that the fates of ducklingswere known.

To organize the encounter histories, we followed the formatused by Dinsmore et al. (2002) and standardized the first-hatchdate (Jun 3 in this case) as day 1, numbering all relocation datessequentially thereafter to the end of the observation period. Bytreating the individual duckling as the sampling unit, the first agewas always 1 because we first observed all ducklings on the day ofhatch, and we coded our encounter histories in the same manneras Dinsmore et al. (2002).

Our candidate model set included the simplest possible modelwhere the daily survival rate was constant within season andbetween years. We then let survival vary by year and included alinear time-trend, with the assumption that DSR may changelinearly throughout the brood-rearing period. We also added thevariables initial brood size, female age, female body condition athatch, duckling age, and amount of daily precipitation singly andin combination to find the model that explained the mostvariation in the data. This resulted in an a priori model setcontaining 29 models.

After fitting all of our potential models, we then adjusted theoutput for overdispersion before selecting the best model using anestimate of c, calculated by dividing the deviance by the deviancedegrees of freedom from our most-highly parameterized model(White and Burnham 1999). This is a conservative method, butthere is currently no other way to estimate the degree ofoverdispersion in the nest-survival module (Dinsmore et al.2002). We believe that using this conservative estimate wasjustified to prevent the selection of a more highly parameterizedmodel than our data could actually support (Anderson et al. 1994).Model-averaged estimates of survival were then calculated for themean hatch date for each year by taking the product of the 30DSRs beginning on that date. We used the delta method (Seber1982) to calculate the variance and estimate the precision of all 30-day survival estimates.

Results

We marked 283 ducklings from 44 broods in 2002, and 360ducklings from 47 broods in 2003. Of these, we monitored 15 and31 broods in 2002 and 2003, respectively. The monitored groupsincluded broods that did not receive radios, but we identified themby color-code identification alone (4 of 15 in 2002, 14 of 31 in2003), allowing us to record duckling-survival information for 18additional broods. We did not monitor the remaining markedbroods because of radio loss or emigration from the immediatestudy area. We rarely observed brood amalgamations in our study(1 brood gained ducklings), and female nest-abandonment ratesduring 2002 and 2003 that could potentially be attributed toresearch activities were low, with 4 and 1 abandonments in eachyear, respectively.

After adjusting for overdispersion (c¼ 1.8), our candidate modelset contained a high degree of model selection uncertainty (Table1). All models had similar levels of support; therefore, we used


model-averaging to produce estimates of DSR for each day of the

brood-rearing season based on inference from all models in the

model set (Fig. 1; Burnham and Anderson 2002). Our model

averaged estimates were 0.64 (95% CI, 0.37–0.90) and 0.67 (95%

CI, 0.54–0.80) for ducklings that hatched on the mean yearly

hatch date, 18 June 2002 and 13 June 2003, respectively.

We present the effects of the covariates and the results from the

top model Syear*TþPPT to provide some explanation for the

variation in survival within and among seasons (Fig. 2). The top

model contained an effect of year (byear¼�2.07; SE¼ 0.82; 95%

CI, �3.68 to �0.45) on a logit scale. This model also included a

weak linear trend with date, which was only estimated differently

from zero in 2002 (bT 2002¼ 0.09; SE¼ 0.04; 95% CI, 0.01–0.17;

and bT 2003 ¼ 0.0042; SE ¼ 0.02; 95% CI, �0.04 to 0.05) on a

logit scale. These effects were common in the top 6 models as well

as others in the model set (Table 1). Daily precipitation had a

negative effect on DSR in both years (bprecip¼�2.68; SE¼ 1.10;

95% CI, �4.83 to �0.53) on a logit scale, and the size and

direction of this effect was similar across models including

precipitation. In 2002, a majority of the precipitation events

occurred in the first half of the brood-rearing season, whereas in

2003, a majority of the precipitation events occurred in the latterhalf of the season (Figs. 1 and 2).

There was an apparent weak-positive effect of initial brood sizeon DSR on a logit scale for all models containing brood size, butthe confidence intervals around the parameter estimates includedzero in all cases. The parameter estimates for an effect of femaleage, female body condition, and duckling age substantiallyoverlapped zero across all models in which they were present. Aseparate analysis of marker effect (radio transmitter vs. color-marked only) for the 2003 data provided no support for adifference in survival between marker types.

Discussion

Our estimates of common goldeneye duckling survival from ourstudy area were higher than previously reported for this species,and survival estimates to 30 days of age were some of the highestever reported for ducks. In British Columbia, survival of thisspecies to near-fledging averaged 0.37 (SE 0.038; Eadie et al.1995), and in Ontario, brood survival to near-fledging rangedfrom 0.31–0.53 (Wayland and McNicol 1994). Our survivalestimates were unexpected, considering that common goldeneyesin our study area were nesting at the northern limit of their range.It seemed likely that the shorter breeding season and potentiallymore variable weather patterns during the season would decreasethe survival of young, but that did not appear to be the case. Thiscould indicate that habitat conditions were quite favorable forducklings of this species in our study area.

Another unexpected result was that we did not observe thepattern of high mortality early in brood-rearing reported for manydifferent species of waterfowl (Savard et al. 1991, Grand and Flint1996, Flint and Grand 1997, Guyn and Clark 1999, Hoekman etal. 2004, Walker and Lindberg 2005). Models containingduckling age did not perform well and explained little of thevariation in the data. Duckling mortalities occurred at a nearlyconstant rate throughout the brood-rearing period with noevidence of catastrophic duckling loss during any period. Therewas a slight increase in DSR through the brood rearing period in2002, but in 2003, duckling survival appeared to be nearlyconstant, except for decreases in DSR on days with precipitation(Figs. 1 and 2).

Of the variables we considered, daily precipitation appeared tohave the largest effect on duckling survival during both seasons.There are several potential explanations for a negative effect ofprecipitation on duckling survival. There is some evidence thatinvertebrates may become less active during precipitation events(Sjoberg and Danell 1982), which would likely hinder the foragingefficiency of ducklings. This would likely be combined withincreased thermoregulatory costs (Dzus and Clark 1997) andcould result in increased mortality. Ducklings may also spendmore time loafing during storms, and loafing areas are likely moreaccessible to predators.

It is possible that sample size limited our ability to detect anyeffects of brood size, female age, and female body condition, evenif they were present. We found some evidence of a positive effectof initial brood size, and female age and body condition appearedin several of the top models, but none of the parameters for theseeffects were estimated very precisely. Smith et al. (2005) recently

Table 1. Model selection results based on Akaike’s Information Criterion,corrected for small sample size and overdispersion (QAICc) values for commongoldeneye duckling survival in the Chena River State Recreation Area, Alas.,USA, 2002–2003. Survival (S) models containing effects of year (year), lineartime trend across season (T), daily precipitation (PPT), initial brood size (size),female body condition index (PC), female age (henage), and duckling age(ducklingage) were considered, as were interactive (*) and additive effects (þ).The number of parameters (K ) and the model weights (x) are also shown.

Model QDeviance K QAICc DQAICc x

Syear*TþPPT 341.05 5 351.14 0.00 0.09Syear*TþsizeþPPT 339.16 6 351.29 0.15 0.09Syear*TþsizeþPCþPPT 337.80 7 351.98 0.84 0.06Syear*TþsizeþhenageþPPT 337.83 7 352.00 0.86 0.06Syear*Tþsize 342.02 5 352.11 0.97 0.06Syear*T 344.12 4 352.18 1.04 0.05Syear*TþsizeþPC 340.39 6 352.51 1.37 0.05Syearþsize 346.52 3 352.56 1.42 0.05Syear*TþsizeþhenageþPCþPPT 336.59 8 352.81 1.67 0.04Syear*Tþsizeþhenage 340.77 6 352.90 1.76 0.04S. 350.92 1 352.92 1.78 0.04Syear*TþducklingageþPPT 340.94 6 353.07 1.93 0.04SyearþsizeþPC 345.04 4 353.10 1.96 0.03Syearþsizeþhenage 345.05 4 353.11 1.97 0.03Syear 349.72 2 353.74 2.60 0.03Syear*TþsizeþPCþducklingageþPPT 337.68 8 353.90 2.76 0.02Syear*PPT 345.93 4 353.99 2.85 0.02Syear*Tþsizeþducklingage 341.86 6 353.99 2.85 0.02Syear*Tþducklingage 343.96 5 354.05 2.91 0.02SyearþPPT 348.10 3 354.14 3.00 0.02SyearþTþsize 346.19 4 354.25 3.11 0.02Syear*TþsizeþPCþducklingage 340.18 7 354.35 3.21 0.02SyearþPC 348.36 3 354.40 3.26 0.02ST 350.75 2 354.77 3.63 0.02Syear*TþsizeþPCþducklingage

þhenageþPPT 336.49 9 354.77 3.63 0.02SyearþTþsizeþPC 344.69 5 354.78 3.64 0.02Syearþhenage 348.79 3 354.83 3.69 0.01SyearþTþsizeþhenage 345.02 5 355.11 3.97 0.01SyearþT 349.32 3 355.36 4.22 0.01


found that brood size had a positive influence on duckling survivalin a similar species, the Barrow’s goldeneye (Bucephala islandica),and we suspect that this could be the case for common goldeneyesas well. If duckling survival is positively related to brood size, thismay partially explain the persistence of high rates of nestparasitism in this species.

High duckling-survival rates to 30 days could have been theresult of certain habitat features within our study site, such as anabundance of potential brood-rearing wetlands, although we wereunable to quantify habitat differences. Wayland and McNicol(1994) found that common goldeneye duckling survival washigher on clustered wetlands than on isolated wetlands, andSavard (1987) suggested that brood-mixing was largely caused byterritorial disputes in Barrow’s goldeneyes. The lack of broodamalgamation in our study may indicate that territorial inter-actions were uncommon. Nest boxes were located in only a smallportion of the habitat available to common goldeneye broodsbecause of limited accessibility, and many females led theirducklings long distances (�11km) from the nest site to brood-

rearing areas, which may have reduced territorial conflicts. The

proximity of the Chena River, generally less than 0.5 km from nest

sites, facilitated these long-distance brood movements without

requiring much overland travel. We often observed broods on the

river during radio-relocating, and they likely used the river to

move between wetlands. Because broods on our study area travel

long distances and use multiple wetlands, quantification of the

effects of habitat features on duckling survival would require a

large-scale and intensive effort.

High survival could also be related to factors such as predator

abundance or food availability. Predators have been identified as

important sources of duckling mortality in other species of

waterfowl (Talent et al. 1982, Mauser et al. 1994, Grand and Flint

1996). Other studies have indicated that common goldeneye

females select habitats with more-abundant invertebrate popula-

tions (Poysa and Virtanen 1994) and that brood survival is higher

in these habitats (Eriksson 1978, Wayland and McNicol 1994).

These factors likely influence the survival of common goldeneye

Figure 1. Model-averaged estimates of common goldeneye duckling daily survival rates (DSR; 695% CI) for A) 2002 and B) 2003 for each day of the season atChena River State Recreation Area, Alas., USA (Table 1). Dark circles on the x-axis under the downward spikes indicate days with measurable precipitation.


ducklings; however, quantification of these variables was beyond

the scope of our study.

Management Implications

To more fully understand the factors that influence duckling

survival, we recommend that future studies attempt to quantify

food availability and the spatial characteristics of brood-rearing

habitat. If these prove important and can be adequately

quantified, managers could identify and protect potentially

important areas for brood-rearing. We also advocate further

investigation of brood size, female breeding experience, and

female body condition to identify additional components that

impact duckling survival.

Based on the ability of broods to successfully travel many

kilometers between nest and brood-rearing sites and the high

overall survival of ducklings in our study, we suggest that box

placement may not be the primary concern when developing a nest-

box program. We propose that by placing boxes near more easily

accessible wetlands, providing that adequate interconnected brood-

rearing habitat is available nearby, the costs associated with these

projects can be reduced. Artificial nests are not a replacement for lost

habitat, but they can provide nesting locations for breeding birds if

suitable nest sites are the limiting factor for reproduction in a given

area. By reducing the amount of labor needed to maintain boxes,

managers may be able to support larger projects than previously

anticipated without negatively affecting duckling survival.

Although duckling survival is unusually high in our study area,

we advise that other components of the population dynamics of

this species be estimated. In general, knowledge of common

goldeneye population dynamics in Alaska is lacking, and

considering the population declines of many other species of sea

ducks, it is clear that baseline information is important for

Figure 2. Estimates of common goldeneye duckling daily survival rates (DSR; 695% CI) for A) 2002 and B) 2003 for each day of the season at Chena River StateRecreation Area, Alas., USA, based on the top model (Table 1). Dark circles on the x-axis under the downward spikes indicate days with measurableprecipitation.


identifying and beginning to understand the underlying reasons

for population level changes. Estimates of nest success, breeding

propensity, dispersal, and adult survival may reveal dramatic

differences compared with estimates from other regions, as we

have shown for duckling survival, and could be important for the

future management of this species. These estimates could be used

to identify the components most likely to affect population

change, and if combined with increased population monitoring,

could help identify and interpret population changes in the future.

Acknowledgments

A. Powell and 2 anonymous reviewers provided comments onprevious versions of this manuscript, and R. Oates aided in projectdesign. We thank S. Hoekman, M. Lindberg, and J. Walker fordiscussions concerning data analysis. B. Soiseth and B. Ottsprovided field assistance. Project funding was provided by the U.S.Fish and Wildlife Service, Migratory Bird Management, Anchor-age, Alaska (Grant G0000135). E. Mallek and D. Sowards servedas pilots during aerial relocations.

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Associate Editor: Rodewald.


Documents

Survival of Common Goldeneye Ducklings in Interior Alaska