Wetland use by brood-rearing female ducks in aboreal forest landscape: the importance of food and

habitatPETRI NUMMI,1* ANTTI PAASIVAARA,2 SARI SUHONEN1 & HANNU PÖYSÄ3

1Department of Forest Sciences, University of Helsinki, PO Box 27, Helsinki, FI-00014, Finland2Oulu Game and Fisheries Research, Finnish Game and Fisheries Research Institute, Tutkijatie 2 E, Oulu,

FI-90570, Finland3Joensuu Game and Fisheries Research, Finnish Game and Fisheries Research Institute, Yliopistokatu 6, Joensuu,

FI-80100, Finland

Habitat use by birds may be related to single or interacting effects of habitat characteris-tics, food resources and predators, but little is known about factors affecting habitat useby wetland species in boreal ecosystems. We surveyed brood-rearing females and duck-lings of four common boreal duck species to assess the effects of habitat structure andfood resources on the use of wetlands by brood-rearing ducks. Although wetland use byduck broods was related to habitat structure and food abundance, their relative impor-tance varied among duck species. For the Common Goldeneye Bucephala clangula, a div-ing duck, aquatic invertebrates and large emerging insects were the most importantfactors associated with wetland use. Common Teal Anas crecca broods were observedmore often on wetlands with greater Dipteran emergence, whereas in Mallard Anasplatyrhynchos both habitat structure and large emerging insects were important. Theoccurrence of Eurasian Wigeon Anas penelope broods was related to emerging Dipteraand habitat structure but the associations were not strong. The varying habitat and foodrequirements of common duck species could influence the success of wetland manage-ment programmes, and consideration of these factors may be particularly important forinitiatives aimed at harvested species or species of conservation concern.

Keywords: Anas crecca, Anas penelope, Anas platyrhynchos, aquatic invertebrates, Bucephalaclangula, emerging insects, habitat structure.

Understanding factors that affect the distribution ofspecies and individuals among habitats is crucial foreffective management and conservation. However,associations between habitat structure and habitatuse may be difficult to interpret because differenthabitat characteristics often act at the same time,confounding the effects of individual factors (Petit& Petit 1996, Chalfoun & Martin 2007). Therelative importance of food and habitat structure isfrequently addressed in studies of habitat selectionby birds (Wiens 1989, Preston 1990, Butler & Gil-lings 2004) and some researchers have argued thatthe importance of structure per se has been

overemphasized (Cody 1981, Terborgh 1985). Ter-borgh (1985) pointed out that the ‘seductive corre-lations’ found between birds and the structuralcomplexity of their habitat may be mere reflectionsof some critical habitat features which are not read-ily measured and which closely correlate with habi-tat structure – of which food resources are a goodexample (Halaj et al. 2000). Temporal variation incritical resources may pose difficulties for birds thatmust attempt to predict future habitat quality.General habitat structure, for example, may bedetectable early in the breeding season, but not thevariation in insect food abundance and availability(Hilden 1965, Orians & Wittenberger 1991).

Waterbirds live in environments where habitatsand resources are patchily distributed. In boreal

*Corresponding author.Email: petri.nummi@helsinki.fi

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Ibis (2013), 155, 68–79

forest regions, for example, resource landscapes ofwaterbirds comprise suitable patches (lakes, ponds,etc.) within a terrestrial matrix that is mostlyunsuitable for foraging. In boreal landscapes, thelocation of wetlands is predictable, but food abun-dance and availability may vary substantially bothbetween and within wetlands. For example, theavailability of emerging insects, a critical resourcefor newly hatched ducklings, may vary from weekto week (Dessborn et al. 2009).

We investigated wetland use by brood-rearingfemales of four common duck species that breedregularly in this region: Common Goldeneye Bu-cephala clangula (hereafter Goldeneye), EurasianWigeon Anas penelope (hereafter Wigeon), Com-mon Teal Anas crecca (hereafter Teal) and MallardAnas platyrhynchos. We focused on the brood stagebecause evidence suggests this is the most criticalperiod of the breeding season: duck pairs occupymany kinds of wetlands, whereas broods appear tooccur regularly only on a few types of wetlands inboreal lake–forest landscapes (Nummi et al. 2000,Sjöberg et al. 2000, Gunnarsson et al. 2004).Moreover, duckling survival is among the mostimportant vital rates in duck population dynamics(Hoekman et al. 2002). In an earlier study address-ing the distribution of duck pairs, broods and juve-niles in relation to habitat structure and food, wefocused on comparisons between different stages ofthe breeding season (Nummi & Pöysä 1993). Thatstudy revealed some general patterns of duck broodhabitat associations, such as the overall preferencefor vegetation-rich habitats.

In the present study we focused on habitatstructure (e.g. width and height of emergent vege-tation, shore depth) and two aspects relating tofood resources (two size classes of emerginginsects, aquatic invertebrates) which have beencorrelated with brood abundance in previous stud-ies (Godin & Joyner 1981, Elmberg et al. 1993,Nummi & Pöysä 1993, Robinson et al. 2003). Alllakes in our study system were sufficiently large tosupport some individuals (broods) of several spe-cies (Danell & Sjöberg 1978, Nummi & Pöysä1995). Most lakes were linked by streams orcreeks. Broods may thus potentially respond toresource changes within a few hours or 1–2 days(Rotella & Ratti 1992, Dzus & Clark 1997, Pöysä& Paasivaara 2006, Paasivaara & Pöysä 2008). Ouraim was to identify the relative importance ofthese factors to duck broods, and assess how suchrequirements differ among species.

We predicted that of females with broods,Goldeneyes would be more closely associated withhigh numbers of aquatic invertebrates and, to les-ser extent, habitat structure because food availabil-ity and not vegetation reportedly influenceswetland use (Eriksson 1976, Paasivaara & Pöysä2004). During the early breeding season, Wigeonspecializes in feeding on emerging chironomids(Sugden 1973, Jacobsen 1991) and its wetland usehas been related to emerging insects (Nummi &Pöysä 1993), so we predicted that Wigeon wouldbe associated with high numbers of emerginginsects. We surmised that Teal and Mallard wouldbe associated with emerging insects and well-vegetated habitats because these factors have beenshown to be important in wetland use by bothspecies (Monda & Ratti 1988, Nummi & Pöysä1993, Robinson et al. 2003).

METHODS

Study area

Data were gathered in 1989–96 in an oligotrophicwatershed (area 39 km2) at Evo in southern Fin-land (61°12′N, 25°07′E). We used data from 12lakes selected as typical of the study area as wellas of boreal forest areas throughout the Holarctic;lakes represented a wide gradient of vegetationgrowth and water depth (see below and Nummi &Pöysä 1993; Table 2). Nummi and Pöysä (1993)used data from 3 years (1989–91); now we analysedata from five more years, which is importantgiven the low density of broods in boreal areas(Nummi & Pöysä 1995). The lakes are located in a5 9 5 km area, range in size from 0.6 to 37.1 ha,and the distance between them ranges between0.3 and 6 km (for further information on the habi-tat configuration around lakes in the watershed,see Pöysä & Paasivaara 2006). Boreal evergreenforest covers most of the watershed, interspersedwith lakes and mires. Agriculture and human set-tlement is very limited and local, and thereforealso lake eutrophication and vegetation change arelimited. Habitat structure of the lakes at the land-scape level has on average been stable for the last20 years (Suhonen et al. 2011). Lake shores aregenerally steep, with little emergent vegetation(mainly sedges Carex spp.), although some lakesare more mesotrophic, with stands of WaterHorsetail Equisetum fluviatile, Cattail Typha spp.and Common Reed Phragmites australis. Emergent

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vegetation is usually lined with narrow belts ofYellow Water Lilies Nuphar lutea, which in moremesotrophic lakes are accompanied by Water Lil-ies Nymphaea candida; submerged vegetation isvery sparse. Located in a cool continental climate,all wetlands freeze over from November to lateApril. They are thus colonized anew each springby migrating ducks.

Habitat structure

To obtain a habitat structure index, shoreline veg-etation was described at the end of the brood per-iod in late July in 1989 when the vegetation wasfully developed. The vegetation was classified visu-ally into six categories based on predominantemergent vegetation types: (1) forest and bog; (2)Phragmites on dry land; (3) Carex on dry land; andemergent (4) Phragmites; (5) Carex and (6) Equise-tum/Typha. Equisetum and Typha shores werecombined because they often occur together andin limited shore sections. The width of the emer-gent vegetation in the water was classified as: 0–1,1–5, 5–10 and > 10 m; average height of a vegeta-tion stand was also classified into four categories,0–25, 25–50, 50–100 and > 100 cm. These weremarked on a field map consisting of enlargementsof lake outlines (1 : 5000) drawn from maps. Thepercentages of each type of vegetation of theshoreline, of each width class and each height classwere measured from the maps. Floating-leavedvegetation, which mostly consisted of Nuphar luteaand Nymphaea candida, was classified as absent, 1–5%, 5–15% or > 15%. Water depth at a distanceof 0.5 m from the shoreline was taken from five toten random points around the lakes with a measur-ing rod. The mean of the depths assigned to thelakes fell into three classes: 0–50, 50–100and > 100 cm.

The 16 habitat variables (i.e. percentage lengthof six vegetation types, four width classes, fourheight classes, coverage of floating-leaved vegeta-tion and water depth) were reduced with principalcomponents analysis (PCA, Pimental 1979) as inNummi and Pöysä (1993). PCA was performedupon the correlation matrix. The first componentexplained 27% of the total variation in the habitatdata. Based on the component weights (Support-ing Information Table S1) the first component wasrecognized as a biologically meaningful gradient:lakes at the positive end of the habitat gradienthad luxuriant vegetation (i.e. a wide band of tall

emergent plants; Table S1); those at the negativeend of the gradient had sparse vegetation (i.e. nar-row band of short emergent plants) and deepwater (Table S1). Hence, we used the first compo-nent as a habitat structure gradient. A similar habi-tat gradient was derived in another study area with35 lakes (the same 16 variables plus lake size;Pöysä 2001), suggesting that the habitat structuregradient used here is generally applicable to north-ern boreal lakes.

Brood surveys

Five brood surveys were carried out at each lakefrom early June to early August every second weekof each year between 1989 and 1996. The meanhatching dates were: Goldeneye 5 June, Wigeon19 June, Teal 18 June and Mallard 8 June. Hence,our surveys covered the brood period well; in 6 of8 years we added an extra survey 1 week beforethe proper survey and observed no Teal or Wigeonbroods, one Mallard brood and five Goldeneyebroods. The five Goldeneye broods were seen inthe lakes that were the most used in the main sur-veys, so missing those data did not bias our results.Shoreline vegetation in the study lakes was gener-ally sparse, but to observe as many broods as possi-ble, we used combined point and round counts(Nummi & Pöysä 1995). We summed all observa-tions of the five brood surveys and used the spe-cies-specific total number of brood observationsfor each year (Supporting Information Fig. S1) asan index of lake use in each year in the statisticalanalyses (except for Wigeon, see below). Onlybroods with ducklings, rather than flying juveniles,were included.

Food resources

Invertebrate trapping was continuous in each Julybetween 1989 and 1996 and consisted of fourtrapping periods of 1 week, except in 1989 (7, 6,7, 9 days) and 1990 (6, 11, 8, 7 days). For eachtrap, a new trapping period began immediatelyafter the trap was emptied from the catch of theprevious trapping period. Free-swimming aquaticinvertebrates were trapped with the activity trapdescribed in Murkin et al. (1983). We used 4-Lglass jars and white plastic funnels with 140-mmopenings at the large end and 20-mm openings atthe narrow end. Activity traps were suspended inthe middle of the water column within the reach

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of the ducks (20–40 cm from the water surface) ata water depth of 50–100 cm as close to the shore-line as possible. Because fish affect the activity trapcatch, traps with fish were omitted from the analy-ses (Elmberg et al. 1992). Emerging insects werecaptured with emergence traps similar to thosedescribed by Danell and Sjöberg (1977). We used5-L plastic buckets and plastic funnels with 200-mm openings at the large end and 40-mm open-ings at the narrow end. Our emergence trapsfloated at fixed sites on two styrofoam panels(c. 30 9 6 9 4 cm) attached to the bucket withmetal rods so that about 5 cm of the trap restedbelow the water surface. Differing from the traptype used by Danell and Sjöberg (1977), our trapshad no hole on the wall of the bucket or the fixedfloating system with metal rods and floats.

Four traps of each type were used per lake. Thetraps were placed at two fixed sites (two traps ofeach type per site) of the shore so that seeminglythe best shore section with wide and high vegeta-tion and the poorest (usually the typical one of agiven lake) shore section with a narrow or non-existent vegetation belt was sampled in each lake.Animals from activity traps were identified andtheir size assigned according to the taxon list andlength categories provided by Nudds and Bowlby(1984); the index is expressed as millimetres ofswimming invertebrates. In some cases, however,our prey animals within a given taxon did not fitthose length categories, and an appropriate lengthcategory was used instead. Because the size of thespecies caught in activity traps varied considerablyand different-sized species dominated in differentlakes, we multiplied the number of individualswithin each taxon by the mean size of the appro-priate length category (size ranges given in Nudds& Bowlby 1984). To correct for trapping periodsof different length, the food abundance is esti-mated per 100 days. The overall food abundancein a given lake was thus measured in two ways:the index of free-swimming invertebrates per 100trap days and the total number of emerging insectsper 100 trap days. In the analyses, the emerginginsects were divided into two groups: one contain-ing only Diptera (small), and the other composedof three categories of large-sized emerging insects(Ephemeroptera, Odonata, Trichoptera). In theactivity trap catch, no such grouping was used, aswithin many taxons, different species are morewidely dispersed in different size classes. Measuresof food abundance varied considerably between

lakes and between years (Supporting InformationFig. S2).

Statistical analyses

We used generalized linear mixed models (Bolkeret al. 2009) and model inference within an infor-mation-theoretical framework (Burnham & Ander-son 2002) to assess simultaneously the role ofhabitat structure and food in habitat selection. Wemodelled the index of brood abundance as a func-tion of the abundance of emerging large and smallinvertebrates, the abundance of free-swimminginvertebrates and the habitat structure index. Lakesize (in hectares) was included in all models as afixed scale covariate. In general, the explanatoryvariables were not strongly intercorrelated (Sup-porting Information Table S2), although correla-tions were found between habitat structure andemerging dipterans and large-sized emerginginsects, and between the two size classes of emerg-ing insects. Emerging insects usually correlatedpositively with the habitat structure index,whereas the correlations between habitat structureand free-swimming invertebrates were mostly neg-ative. There were also clear yearly differences inthe strength and direction of correlations betweenthe explanatory variables (Table S2).

Our data may reflect species-specific randomdynamics in the number and occurrence of broods.So, before final model fitting, we fitted differentrandom effect scenarios for each species: (1) a cat-egorical random factor for the effects of lake oryear, separately; (2) the additive effect of the twocategorical random factors for lake and year (lake+ year); (3) the random slope and the interceptfor the interaction of year (as a continuous covari-ate; coded as 0–7) and lake (i.e. random changefor the number of brood observations over thestudy period in a given lake; year*lake); and (4)the additive effects of the random slope and inter-cept for the interaction of year (covariate) andlake, and the categorical random factor for theeffect of year (year*lake + year). The fit for therandom effects was estimated from the full modelthat included all fixed effects (Bolker et al. 2009).We used the best-fitting random effects scenariofor each species throughout the model selection.

For the dependent summed brood count vari-able we assumed a Poisson distribution and canoni-cal log-link function. However, a preliminaryexamination of the variances, means and estimated

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scale factors of the quasipoisson distribution (phi;Bolker et al. 2009) and dispersion analyses (ĉ;Burnham & Anderson 2002) suggested that resid-ual variation was less than expected according to apure Poisson distribution in the models of all spe-cies, and especially in the full model for Wigeon(phi and ĉ � 1). Therefore, for Wigeon we used abinary presence–absence variable (i.e. broodseither observed or not in a given lake in a givenyear) instead of the total number of brood obser-vations, and assumed a binomial error and canoni-cal logit-link function. For the other species, weheld pure Poisson errors with scale factor ĉ = 1,because scale factor ĉ < 1 may lead to a biasedand overly optimistic group of models with toomany parameters.

We used the Laplace approximation to estimateparameters (Bolker et al. 2009) and an informa-tion-theoretic model selection approach for statisti-cal inference (Burnham & Anderson 2002).Second-order Akaike’s information criterion(AICc) corrected for small sample size served toevaluate the relative support for the differentmodels (Burnham & Anderson 2002). There is nostraightforward way to assign the sample size forAICc for mixed-effects models. Therefore, we usedthe number of independent clusters (12 lakes and8 years; sample size was n = 20 in all) instead ofthe total number of observations (n = 96) for thesample size of AICc, providing a more conservativesample size for AICc-based model selection (Burn-ham & Anderson 2002).

We also calculated Akaike weights (wi, addingto 1), evidence ratios (wbest/wi, where wbest is theAkaike weight of the best-fitting model) for allmodels, where models with a larger wi betterapproximate the data (Burnham & Anderson2002); in multi-model inference, we focus onmodels within the 95% confidence set (sum of wi

from largest to smallest � 0.95) and present onlythe 95% confidence set of models in the results.Given model selection uncertainty (see Results),we used the method of Burnham and Anderson(2002) to quantify the evidence for the impor-tance of each variable. We summed the Akaikeweights for each variable across all the modelswhere it occurred as a measure of variable impor-tance. We also calculated the model-averagedparameters (b-values) of the variables, weightingby the wi, as well as their unconditional standarderrors and 95% unconditional confidence intervals;all models in the candidate set were used

(Burnham & Anderson 2002). We carried out theanalyses using the glmer function (in the lme4library; Bates & Maechler 2009) in R 2.12.1. (RDevelopment Core Team 2010).

RESULTS

Broods of Goldeneye were the most abundant andoccupied nine lakes during the study period(Fig. S1). The yearly average number of Golden-eye brood observations was 1.48 (sd = 2.58,n = 144 observations) per lake. The second mostabundant species was Wigeon, which occupied fivelakes and in which the yearly average number ofobservations was 0.54 (sd = 1.65, n = 52 observa-tions). Teal occupied ten of the lakes, and theaverage number of yearly brood observations was0.46 (sd = 1.12, n = 44 observations). Mallardbroods occupied only four of the lakes, and theyearly average number of brood observations perlake was 0.17 (sd = 0.65, n = 16 observations).

For the Goldeneye, five models fell into the 95%confidence set (Table 1), thus reflecting somemodel selection uncertainty. The best supportedmodel suggested that the habitat use of Goldeneyebroods increased with increasing abundance offree-swimming invertebrates and large-sized emerg-ing insects (Table 2). The abundance of free-swim-ming invertebrates was included in all the modelsin the 95% confidence set, and its relative impor-tance was high (0.999; Table 2). Similarly, the pre-cision of the estimate and the high sum of AICweights for the abundance of large-sized emerginginsects indicates that this variable was also impor-tant. The models in the 95% confidence set alsoincluded the index of habitat structure and theabundance of emerging Diptera, but the relativeimportance of these variables was low (Table 2).

In Wigeon, the 95% confidence set included 11models, but only two models had a better rankthan the null model that included only the effectof lake size (Table 1). The best supported modelincluded the abundance of emerging Diptera(Table 2). The second best supported modelincluded the habitat structure index. Occurrenceof Wigeon broods was positively but weakly asso-ciated with lake size, abundance of Diptera andhabitat structure, but high unconditional errorrates (se in relation to parameter estimates) andlarge confidence intervals include zero and indicateimprecise parameter estimation for all of them(Table 2).

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In Teal, seven plausible models fell within the95% confidence set of candidate models (Table 1)and four models fell within ΔAICc < 2, indicatingconsiderable model selection uncertainty. How-ever, the model that included the abundance ofemerging Diptera received most support and thesum of AIC weights for the abundance of emerg-ing Diptera was high (Table 2). The abundanceof emerging dipterans was included in all modelsof the 95% confidence set. In contrast, the sums of

the AIC weights of habitat structure, the abun-dance of large-sized emerging insects and theabundance of free-swimming invertebrates weremuch lower (see Table 2). Model-averaged param-eter estimates revealed that the lake-specific num-ber of Teal broods increased with the abundanceof emerging Diptera; for the other explanatoryvariables the unconditional error rates (se inrelation to parameter estimates) and unconditionalconfidence intervals were large (Table 2).

Table 1. The 95% confidence sets of generalized linear mixed models developed a priori to explain variation in habitat use bybrood-rearing female ducks. For Goldeneye, Wigeon and Mallard, models included lake as a random effect. For Teal, modelsincluded year as a random effect. For all species, models included intercept and lake size as fixed effects (null model). The modelsare ranked by AICc values.

Models Ka AICcb ΔAICc

c wd C-We E-ratiof

GoldeneyeEph/Trich+Freesw 5 142.199 0.000 0.624 0.624 1.000Freesw 4 145.665 3.467 0.110 0.734 5.660Dipt+Eph/Trich+Freesw 6 145.922 3.723 0.097 0.831 6.431Habit+Eph/Trich+Freesw 6 145.962 3.763 0.095 0.926 6.566Dipt+Freesw 5 148.076 5.878 0.033 0.959 18.903Lake size 3 165.178 22.980 0.000 1.000 NA

WigeonDipt 4 54.849 0.000 0.211 0.211 1.000Habit 4 55.181 0.332 0.179 0.389 1.180Lake size 3 55.507 0.658 0.152 0.541 1.390Eph/Trich 4 56.440 1.591 0.095 0.636 2.216Habit+Dipt 5 56.745 1.896 0.082 0.718 2.579Habit+Eph/Trich 5 57.207 2.358 0.065 0.783 3.252Dipt+Eph/Tric 5 57.613 2.764 0.053 0.835 3.983Freesw 4 58.443 3.594 0.035 0.870 6.037Dipt+Freesw 5 58.462 3.612 0.035 0.905 6.090Habit+Freesw 5 58.466 3.617 0.035 0.940 6.107Eph/Trich+Freesw 5 59.741 4.892 0.018 0.958 11.514

TealDipt 4 101.747 0.000 0.261 0.261 1.000Dipt+Eph/Trich 5 102.016 0.270 0.228 0.488 1.145Habit+Dipt 5 102.311 0.564 0.197 0.685 1.326Habit+Dipt+Eph/Trich 6 103.495 1.748 0.109 0.794 2.397Dipt+Freesw 5 104.293 2.546 0.073 0.867 3.575Habit+Dipt+Freesw 6 104.463 2.716 0.067 0.934 3.890Dipt+Eph/Trich+Freesw 6 105.656 3.910 0.037 0.970 7.062Lake size 3 135.683 33.936 0.000 1.000 NA

MallardHabit+Eph/Trich 5 55.331 0.000 0.554 0.554 1.000Habit 4 57.696 2.365 0.170 0.724 3.262Habit+Dipt+Eph/Trich 6 59.371 4.040 0.074 0.797 7.536Habit+Eph/Trich+Freesw 6 59.443 4.112 0.071 0.868 7.812Habit+Dipt 5 60.505 5.174 0.042 0.910 13.283Habit+Freesw 5 61.172 5.841 0.030 0.940 18.525Eph/Trich 4 61.372 6.041 0.027 0.967 20.515Lake size 3 65.644 10.312 0.003 0.998 173.094

Habit = habitat structure index; Dipt = abundance of emerging Diptera; Eph/Trich = abundance of emerging large invertebrates;Freesw = abundance of free-swimming invertebrates. aNumber of parameters. bSecond-order Akaike’s information criterion. cDiffer-ence between the current model and the minimum AICc value. dModel weight. eCumulative weight. fEvidence ratio (seeMethods).

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In Mallard, the 95% confidence set includedseven plausible models (Table 1). The highest-ranked model included the effects of habitat struc-ture and the abundance of large-sized emerginginsects (Table 2) which were included eitheralone or together in the 95% confidence set ofmodels. The sums of the AIC weights of habitatstructure and large-sized emerging insects were0.952 and 0.745, respectively, whereas the sumsof the AIC weights of free-swimming invertebratesand Diptera were 0.120 and 0.140, respectively.The sums of the AIC weights and model averagedparameter values and their error rates (Table 2)indicate that habitat structure and the abundanceof large-sized emerging insects are the mostimportant variables in explaining the Mallardbrood lake use in the present data; the number ofMallard brood observations increased with habitatstructure index and large-sized emerging insects(Table 2).

DISCUSSION

Habitat use by brood-rearing female ducks wasassociated with habitat structure and food abun-dance but the relative importance of these twofactors varied among species, and in ways thatwere not always consistent with our initial predic-tions. As predicted, Goldeneye, the only divingduck among the species studied, differed fromdabbling duck broods in that it was strongly associ-ated with invertebrates in the water column andwith large emerging insects, but not with smallemerging insects or habitat structure. Several pre-vious studies have found that Goldeneye broodsare strongly associated with aquatic invertebrates(Eriksson 1978, Nummi & Pöysä 1993, Paasivaara& Pöysä 2004). Similarly, Haszard and Clark(2007) demonstrated that the occurrence ofWhite-winged Scoter Melanitta fusca broods wasassociated with the abundance of amphipods in

Table 2. Model averaged parameter estimates, their unconditional standard errors and unconditional 95% confidence intervalsderived from generalized linear mixed models explaining habitat use by brood-rearing female ducks. Estimates of parameters, theirstandard errors and confidence intervals are based on all models in the candidate model set using Akaike weights as weighting fac-tors (see Methods).

Variable b-value Unconditional seUnconditional 95% confidence interval

Upper, Lower Importancea

GoldeneyeLake size 0.031 0.034 �0.036, 0.097 –Dipt 0.041 0.054 �0.064, 0.146 0.145Habit 0.236 0.348 �0.445, 0.917 0.136Eph/Trich 1.550 0.541 0.490, 2.610 0.826Freesw 0.623 0.128 0.374, 0.874 0.999

WigeonLake size 0.115 0.077 �0.037, 0.266 –Dipt 0.383 0.237 �0.081, 0.846 0.413Habit 1.205 0.756 �0.276, 2.686 0.395Eph/Trich 2.815 2.364 �1.818, 7.449 0.263Freesw 0.246 0.648 �1.024, 1.515 0.150

TealLake size �0.004 0.018 �0.052, 0.031 –Dipt 0.209 0.056 0.100, 0.318 0.988Habit 0.344 0.203 �0.053, 0.741 0.402Eph/Trich 1.392 0.800 �0.299, 2.927 0.403Freesw �0.369 0.243 �0.175, 2.960 0.196

MallardLake size 0.011 0.030 �0.048, 0.070 –Dipt 0.020 0.135 �0.245, 0.285 0.140Habit 1.441 0.523 0.416, 2.465 0.952Eph/Trich 2.231 0.840 0.585, 3.876 0.745Freesw 0.111 0.383 �0.641, 0.862 0.120

Dipt = abundance of emerging Diptera; Habit = habitat structure index; Eph/Trich = abundance of emerging large-sized insects;Freesw = abundance of free-swimming invertebrates. aImportance = sum of the Akaike weights for each variable across all themodels where it occurred (see Methods).

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the boreal wetlands of northwest Canada. BecauseGoldeneyes can use the invertebrates in ratherunstructured habitats, they benefit from theabsence of competing fish in acidified boreal lakesthat usually have little emergent vegetation (Eriks-son 1979, Pöysä et al. 1994, Nummi et al. 2012).The association of ducklings with large emerginginsects most probably reflects the presence of Tri-choptera and Odonata larvae in those very habi-tats; Goldeneye ducklings frequently prey on theselarvae (Eriksson 1976).

Among the dabbling duck species, Wigeonbroods were associated with emerging Diptera andhabitat structure, but the strength of these associa-tions was weaker than we had initially expected.The pattern may be due to the low number ofinhabited lakes; most of the Wigeon broods werefound in the most eutrophic lake of the study area(lake 4 in Figs S1 and S2). Wigeons may prefer awell-vegetated habitat, as they become largely her-bivorous relatively early in their development, atthe age of 3 weeks (Bartonek 1972, Sugden1973). However, Wigeon also glean emerginginsects, especially among Equisetum (Jacobsen1991). As Equisetum stands were particularlyextensive in the most eutrophic lake of the studyarea, we suggest that the association betweenbrood occurrence and habitat structure reflectsWigeon ducklings’ preference for a suitable forag-ing substrate.

Teal broods behaved partly as predicted, beingstrongly associated with emerging dipterans. Num-mi and Pöysä (1993) found that Teal broods wereassociated both with emerging insects and withhabitat structure. The food of young Teal duck-lings consists mainly of emerging Diptera, whichthe ducklings catch from the water surface or fromthe vegetation (Danell & Sjöberg 1980). Althoughthe foraging behaviour of Teal ducklings remainslargely unstudied, adult Teals are known to searchfor food near the water surface with the bill sub-merged, and use different parts of feeding patchesmore evenly than do Mallards (Pöysä 1986). Thisis reflected in the diet: Teal feeds on many kindsof small-sized invertebrates living in the watercolumn, whereas the Mallard concentrates onfewer types of larger animals living on the bottomor on submerged plants (Nummi 1993).

For Mallards, our predictions held, as both habi-tat structure and the number of large-sized emerg-ing insects were important. Mallard broods areknown to feed in shallow water within stands of

emergent vegetation (Monda & Ratti 1988). Theassociation of Mallard broods with large emergentinsects corroborates the observation that trichopt-erans and odonates are relatively common in thediet of Mallard ducklings (Perret 1962). Theimportance of both habitat and food has rarelybeen considered, but Godin and Joyner (1981)found both to be important. That said, they mea-sured only the amount of aquatic invertebrates,which may not strongly correlate with the abun-dance of emerging insects; at the least, there maybe clear yearly variation in these correlations(Table S2). Moreover, older ducklings consume alot of aquatic invertebrates below the water sur-face (Chura 1961). In semi-natural gravel pits, theimportance of emerging insects was greater thanthat of habitat structure (Robinson et al. 2003). Inan ecologically similar species, the Black DuckAnas rubripes, Staicer et al. (1994) found thatbrood density in the lakes of western Nova Scotia,Canada, was positively associated with the abun-dance of pelagic and benthic invertebrates andmacrophyte cover.

The present analyses, based on larger samplesand new statistical methods, confirmed some previ-ous findings from the same study system (Nummi& Pöysä 1993). However, they also provided newinformation on factors affecting the habitat use ofduck broods. First, the association of Wigeonbroods with habitat structure, although not strong,indicates that the species may be a habitat special-ist, at least at the brood stage; food abundancealone may not suffice if a suitable foraging substrateis unavailable. Secondly, although prey abundanceappeared less important in the habitat use of Mal-lard broods in our previous study (Nummi & Pöysä1993), the present analyses revealed that both habi-tat structure and prey abundance are important.Moreover, for the first time, we demonstrated thedifference between the Teal and the Mallard withregard to the importance of different-sized emerg-ing insects: Diptera were very important to Tealbroods, whereas Mallards were associated with lar-ger emerging insects, of which the Trichopterawere presumably the most abundant. When creat-ing new wetlands, dipterans appear to colonizethem more rapidly than do trichopterans (Danell &Sjöberg 1982), which, in turn, is reflected in therapid colonization by Teal and a slower one byMallard (Nummi & Pöysä 1997, Nummi & Haht-ola 2008). Because emergence patterns of aquaticinsects vary seasonally and annually, as well as

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Wetland use by duck broods 75

among lakes, more detailed study than the presentone would be useful. Also, possible differences inthe scale of habitat selection between duck pairsand broods need more attention. In particular, con-tinuous measurement of emerging insects and habi-tat use by duck pairs and broods could reveal hownon-flying duck broods and highly mobile pairs dif-fer in their responses to changing lake conditions,especially if the habitat selected turns out to bepoorer than anticipated (Orians & Wittenberger1991).

We could not separate the role of predationfrom that of food or habitat structure in affectingpatterns of habitat use by brood-rearing females.In particular, total brood loss due to predationmight result in incorrectly assigning some wetlandsas not being used by duck broods. We cannotexclude this possibility; however, we made fivebrood surveys at each lake during each summerand therefore expect low bias in this respect. Onthe other hand, females might actively avoid usingbrood-rearing habitats in which there is high pre-dation risk.

However, in our study area, radio-markedfemale Goldeneyes consistently moved their broodsfrom invertebrate-poor wetlands to ones with moreinvertebrates (Paasivaara & Pöysä 2004). Becauseinvertebrate-rich lakes often support Northern PikeEsox lucius populations (A. Paasivaara & H. Pöysäunpubl. data), predation risk may not be the mainforce affecting habitat selection patterns, at least inGoldeneye.

Moreover, when foraging in lakes with lowphosphorus and low wild brood use, human-imprinted Mallard ducklings gained little or evenlost weight, whereas in more productive lakes usedby wild broods, ducklings grew much faster (Sjö-berg et al. 2000). Furthermore, the weight gain ofthe ducklings was positively associated with above-surface feeding, which most likely reflects theavailability of emerging insects (Nummi et al.2000). Experimental work has demonstrated thataquatic invertebrate abundance has a positiveeffect on duckling growth and subsequent survival(Cox et al. 1998). It would be informative experi-mentally to manipulate habitat, for example byremoving vegetation at different intensities, and tocombine this with studies on invertebrates andbrood habitat use and duckling foraging behaviour(Wiens et al. 1986, Batzer & Resh 1992).

In general, the role of habitat structure in thehabitat use of all dabbling duck broods may

reflect the role of vegetation as shelter for inverte-brates against fish predation (Diehl 1992, Hor-nung & Foote 2006) as well against inclementweather and predation (Sayler & Willms 1997,Bloom et al. 2012). It has been shown that theabundance of competing fish, e.g. the EuropeanPerch Perca fluviatilis, may affect Teals which for-age in more open areas (Pöysä 1986), but notMallards, which especially forage among shelteredshore vegetation (Elmberg et al. 2010, Väänänenet al. 2012). Similarly, in other bird groups and inother types of habitats the role of food and habi-tat structure may vary (Preston 1990, Whitting-ham & Markland 2002). For example, in farmlandhabitat there was a negative relationship betweenprey detectability and vegetation height in Lap-wings Vanellus vanellus, whereas in ChaffinchesFringilla coelebs the prey capturing was notaffected but mobility was (Butler & Gillings2004). In forest passerines, the microhabitat usedfor foraging was constrained by habitat structureand characteristics of the available prey (Robinson& Holmes 1982).

The four species studied here constitute thecore species of boreal waterfowl communities inEurope (Danell & Sjöberg 1978, Kauppinen1993). When the management of all duck speciesis considered, we conclude that both food andhabitat structure are important. The food situationis also affected by other consumers of the foodweb, namely fish (Hill et al. 1987, Haas et al.2007, Nummi et al. 2012). In the creation of newwetlands it is important to avoid the introductionof fish which may cause not only competition butalso predation (Paasivaara & Pöysä 2004, Hornung& Foote 2006). The requirements of many speciescan often be taken into account at the same time,but some species may require special attention.For example, the creation of flooded habitats maybenefit Teal and Goldeneye, which are stronglyassociated with different kinds of aquatic inverte-brates. On the other hand, the Wigeon and tosome extent the Mallard may benefit only fromwetlands if they contain suitable vegetation.

We wish to thank all the field workers for their assis-tance in duck surveys and invertebrate collection. Thegrant from the Jenny and Antti Wihuri Foundation toS.S., and from the Foundation for Research of NaturalResources in Finland to P.N. are much appreciated. BobClark and two anonymous referees made valuable com-ments on the manuscript.

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76 P. Nummi et al.

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Received 21 April 2011;revision accepted 10 October 2012.

Associate Editor: Robert Clark.

SUPPORTING INFORMATION

Additional Supporting Information may be foundin the online version of this article:

Table S1. Summary statistics for the habitatvariables used in the PCA and component weightsof the first component.

Table S2. Pearson correlation coefficientsamong lake size, habitat structure, emerging

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dipterans, large-size emerging insects and free-swimming invertebrates for each year.

Figure S1. The total number of brood observa-tions (i.e. the index of lake use of broods) forGoldeneye, Wigeon, Teal and Mallard broods inthe lakes (see Methods).

Figure S2. The abundance of emerging Diptera,the abundance of free-swimming invertebrates(log-scaled), the abundance of emerging large-sizedinvertebrates and the index of habitat structure inthe lakes (see Methods).

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Wetland use by duck broods 79