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Food constraints explain the restricted distribution ofwintering Lesser White-fronted Geese Anser

erythropus in ChinaXIN WANG,1 ANTHONY D. FOX,2 PEIHAO CONG1 & LEI CAO1*

1School of Life Sciences, University of Science and Technology of China, Hefei, China2Department of Bioscience, Aarhus University, Rønde, Denmark

More than 90% of the Lesser White-fronted Geese Anser erythropus in the EasternPalearctic flyway population winter at East Dongting Lake, China. To explain thisrestricted distribution and to understand better the winter feeding ecology and habitatrequirements of this poorly known species, we assessed their food availability, diet andenergy budgets at this site through two winters. Lesser White-fronted Geese maintaineda positive energy budget when feeding on above-ground green production of Eleocharisand Alopecurus in recessional grasslands in autumn and spring to accumulate fat stores.Such food was severely depleted by late November and showed no growth in mid-win-ter. Geese fed on more extensive old-growth Carex sedge meadows in mid-winter wherethey were in energy deficit and depleted endogenous fat stores. Geese failed to accumu-late autumn fat stores in one year when high water levels prevented the Geese fromusing recessional grassland feeding areas. Fat stores remained lower throughout that win-ter and Geese left for breeding areas later in spring than in the previous year, perhapsreflecting the need to gain threshold fat stores for migration. Sedge meadows are wide-spread at other Yangtze River floodplain wetlands, but recessional grasslands are rare andperhaps restricted to parts of East Dongting Lake, which would explain the highly local-ized distribution of Lesser White-fronted Geese in China and their heavy use of thesehabitats at this site. Sympathetic management of water tables is essential to maintain therecessional grasslands in the best condition for Geese. Regular depletion of fat storeswhilst grazing sedge meadows in mid-winter also underlines the need to protect the spe-cies from unnecessary anthropogenic disturbances that enhance energy expenditure. Thespecialized diet of the Lesser White-fronted Goose may explain its highly restricted win-ter distribution and global rarity.

Keywords: conservation management, East Dongting Lake, energy budget, Goose foraging,recessional grasslands.

Understanding the factors that shape distributionand abundance of organisms is crucial to effectiveconservation and historically is a cornerstone ofecology (de Humboldt & Bonpland 1807, Andre-wartha 1961, Caughley & Sinclair 1994, Krebs1994). Among many factors affecting species dis-tribution and abundance (e.g. Dunson & Travis1991, Polis & Strong 1996, Ricklefs & Jenkins2011), food availability is frequently considered

one of the most critical (Wiens 1989, Newton1998, Strong & Sherry 2000). For migratory birds,food availability on the wintering areas influencespopulation distribution and abundance by affectingthe body condition, migration dates and subse-quent breeding success of migrants (Holmes &Sherry 2001, Newton 2004). Successful wintersurvival and spring departure dates and conditionultimately rely on obtaining positive feedingenergy budgets for self-maintenance and fat stor-age (Price 1981, Moore & Yong 1991, Owen et al.1992, Marra & Holberton 1998).

*Corresponding author.Email: [email protected]

© 2013 British Ornithologists’ Union

Ibis (2013), 155, 576–592

Most northern hemisphere herbivorous Goosepopulations are increasing (Fox et al. 2010), partlybecause of the fitness consequences of feeding onextensive agricultural monocultures that have pro-vided unlimited winter food subsidies in recentyears (Abraham et al. 2005, Fox et al. 2005). Incontrast, the globally threatened Lesser White-fronted Goose Anser erythropus is designated asglobally ‘Vulnerable’ because of long-term declinesin abundance and contractions in range (BirdLifeInternational 2010). Unlike most other winteringAnatidae, the Lesser White-fronted Goose ishighly restricted in winter within the YangtzeRiver floodplain (Cao et al. 2010), with EastDongting Lake supporting more than 90% of thetotal Eastern Palaearctic wintering population of25 000–28 000 birds (Wang et al. 2012). Thehighly concentrated nature of its distributionmakes the Lesser White-fronted Goose particularlyvulnerable to winter habitat loss and change,underlining the need to understand the reasons fortheir biogeographical reliance on East DongtingLake. Lack of research relating to the habitat andfood requirements of the Lesser White-frontedGoose hinders our understanding of the factorsaffecting the unique distribution pattern of thisspecies and ability to offer management recom-mendations for its effective conservation (BirdLifeInternational 2010, Wang et al. 2012).

We predicted that the impact of food availabil-ity on the energy budget of wintering LesserWhite-fronted Geese would play a key role inexplaining their unique distribution for three rea-sons. First, many studies indicate that shifts infeeding distribution between habitats of winteringherbivorous Geese may reflect differences in avail-ability and energetic profitability of dietary items(e.g. Ely & Raveling 2011, Fox et al. 2011, Conget al. 2012). Secondly, although a few studies ofAnatidae in captivity show endogenous patterns ofwinter mass loss (e.g. Mallard Anas platyrhynchosLoesch et al. 1992, Barnacle Geese Branta leucopsisPortugal et al. 2007), studies of herbivorous Geesein the wild show that they generally accumulateenergy stores in autumn, which are then depletedin mid-winter and reconstructed in spring (Owenet al. 1992, Tinkler et al. 2009). Thirdly, at EastDongting Lake, Lesser White-fronted Geese havebeen observed grazing on widespread recessionalsingle-species Carex sedge meadows (Markkolaet al. 1999, Fox et al. 2008), as well as on moregeographically restricted recessional grasslands,

where Geese aggregated in greater concentrationson short single-species swards of the grass Alopecu-rus aequalis and the spikerush Eleocharis migoana,especially in autumn and spring (Cong et al.2012). Sedge meadows are a feature of severallakes throughout the Yangtze River floodplain (Liet al. 2010, Yu et al. 2011, Zhao et al. 2012) andare commonly exploited by other herbivorousGeese, e.g. Greater White-fronted Goose Anseralbifrons albifrons and Bean Goose Anser fabalisserrirostris (Lu & Zhang 1996, Cheng et al. 2009,Zhao et al. 2010). Greater White-fronted Geese inparticular are largely restricted to such sedgemeadows throughout the Yangtze River floodplain(Cao et al. 2010, Zhao et al. 2012). If the LesserWhite-fronted Goose can maintain a positiveenergy budget on Carex, we would expect it to bemore widely distributed in eastern China. How-ever, if it is reliant on the heterogeneous reces-sional grasslands of East Dongting Lake, this couldexplain their concentration of Lesser White-fronted Geese at this site and render them extre-mely vulnerable to habitat loss and changes. Thisis because such recessional grassland communitiesare extremely rare in the Yangtze River floodplain,where highly dynamic annual flooding stronglyinfluences their composition and productivity,whereas perennial Carex sedge meadows are lessdisturbed by these influences (e.g. Deil 2005,Barzen 2008).

We estimated energy budgets of Lesser White-fronted Geese throughout the entire winter inareas with differing vegetation types in order tocompare the energetic consequences of feedingon Carex sedge meadows with those exploitingheterogeneous recessional grasslands during 2008/2009 and 2009/2010 in this study. We antici-pated that long-leaved Carex constitutes relativelyinefficient forage for the short-billed LesserWhite-fronted Goose (Durant et al. 2003), incontrast to the larger-billed Greater White-frontedand Bean Geese, which are known to achieve apositive energy budget while feeding on Carex(Lu & Zhang 1996). As the above-ground pri-mary production in recessional grasslands peaks inautumn and spring, and ceases during the coldestand driest period in winter (Cong et al. 2012),we expected that Lesser White-fronted Geeseaccumulate energy stores from feeding on hetero-geneous grasslands in relation to seasonal andbetween-year variation in food availability in theseplant communities.


Food constrains Lesser White-fronted Goose distribution 577

METHODS

Study site

East Dongting Lake National Nature Reserve(Hunan Province, China, 29.32°N, 112.98°E)comprises 190 000 ha of sedge Carex spp. mead-ows, marshes and shallow freshwater lakes (Tayloret al. 2005). The northwestern parts, Caisang andDaxi Lakes, were selected for study because oftheir importance for Lesser White-fronted Geeseand their accessibility (Fig. 1; see also Cong et al.2012, Wang et al. 2012). Both basins retain waterafter water levels recede in surrounding areas.Daxi Lake has a direct connection with the Yan-gtze River and supports c. 800 ha of exclusivelyCarex sedge meadows and virtually no recessionalgrassland. Caisang Lake lies to the north of DaxiLake, is separated by a dyke and its water levelsare controlled by a sluice. Water levels started to

recede 2 weeks earlier in 2008 (9 October 2008)than in 2009 (22 October 2009) and because ofearlier recession of water levels supported c.350 ha of recessional grasslands, dominated by thespike rush Eleocharis sp. and grasses of the genusAlopecurus in winter 2008/2009. In winter 2009/2010, late high water levels delayed exposure andgrowth in recessional grasslands, which resulted inretained water, bare mud flats and only limitedAlopecurus and small Carex patches that year. Theseconditions created two contrasting foraging environ-ments at Caisang Lake in the two study years. Cai-sang and Daxi Lakes constitute two major foragingareas for Lesser White-fronted Geese in East Dong-ting Lake, and together support up to 84% of thetotal numbers for the entire lake (Cong et al. 2012,Wang et al. 2012). Neither lake is exposed to severehuman disturbance. The Geese using these twosites also utilize Chunfeng Lake (39 km to thesoutheast; Fig. 1), a much larger area nearby, which

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Figure 1. Maps showing the location of the study sites within China and within East Dongting Lake National Nature Reserve, withthe position of Chunfeng Lake (inset right) and the two observation sites, Caisang and Daxi Lakes (lower inset).


578 X. Wang et al.

supports very similar recessional grassland vegeta-tion to that of Caisang Lake. Chunfeng Lake isextremely large, difficult to access and the opennessof the habitat precludes close study of Goosebehaviour. Faecal analysis showed that Geese fedbroadly on the same plants there as at Caisang andlimited data gathered on Goose abdominal profilessuggest no major differences between birds at bothsites (P. Cong unpubl. data). For this reason, datacollection was restricted to Daxi and Caisang Lakesfor the purposes of comparing the energetic profit-ability of recessional Carex beds vs. recessionalgrassland communities to the Geese.

Food supply and Goose utilization

To measure food supply, we marked 20 contigu-ous 100 9 100 m plots with bamboo posts acrossthe main Goose feeding areas at Caisang Lake andfive such plots at Daxi Lake. Random turf samplesof 10 9 10 cm at Caisang Lake and 20 9 20 cmat Daxi Lake were dug up and removed fromwithin each plot, above-ground plant parts clippedto soil level, identified and sorted into live anddead biomass for each species before being oven-dried at 50 °C for 24 h. Because it was not alwayspossible to determine the epidermal tissue of grassspecies in Goose faeces (see below), we aggregatedplant species into four classes throughout theanalysis: ‘Eleocharis’; ‘Grass’, which included com-mon Poaceae food species, which was predomi-nantly Alopecurus, but including some Poa andCynodon species; ‘Carex’; and ‘Dicots’, comprisingall dicotyledonous species. Eleocharis, Alopecurusand Carex were the dominant species consumedby the Geese based on visual observations, andalthough dicotyledonous species formed a largeelement of the sward, they were of limited impor-tance in the diet of the Geese (see below). Weconducted regular Goose counts throughout bothlakes (47 counts at Caisang Lake in 2008/2009, 92at Daxi Lake in 2009/2010 and 45 at CaisangLake in 2009/2010). Counts were performed at1.5-h intervals throughout the day but we presentdaily maximum Goose number as a surrogate forGoose use of the feeding sites.

Goose diet composition

The diet composition of Lesser White-frontedGeese was determined by faecal analysis. Fortyfresh and complete droppings were collected

weekly at each lake, cleaned of mud and sand,oven-dried at 50 °C for 24 h, weighed for drymass, pooled and ground. Ground samples wererandomly selected and diluted with water to dis-perse fragments evenly and mounted on micro-scope slides. For each sample, 200 randomlyencountered epidermal fragments in the micro-scope field were identified (at 9100 magnification)to the four species groups defined above (followingthe methods of Owen 1975) and their size esti-mated. The proportion (based on total leaf frag-ment area) of plant species group i in the diet(PAi) can be represented as:

PAi ¼AiPiAi

where Ai is the total area of species group i in theanalysis.

For quantitative analysis of food intake, the areaproportion was further transformed to propor-tional mass (PMi) by:

PMi ¼PAi � LSWiPiPAi � LSWi

where LSWi is the leaf weight ratio for species i.The leaf weight ratio (dry mass/mm) was calcu-lated for each species from the area of fresh leafsamples, scanned using a scanner (Canon�

LIDE25) and calculated using the software IMAGEJ

(Abr�amoff et al. 2004), and the dry mass of thesamples. We assumed that the leaf area to massrelationships for faecal fragments were identical tothose for fresh leaves. We grouped food items intothe four classes described above.

Estimating energy budgets

We calculated energy expenditure by compilingtime budgets and combining these with the ener-getic costs of different behaviours, adjusted forthermoregulation. Then we estimated daily metab-olizable energy intake based on the difference inenergetic content between the food and faecesusing the indigestible marker system. We esti-mated the energy budgets from the differencebetween these two measures (see SupportingInformation Table S1 for estimated values), andcompared this with field observations of changesin Goose fat stores as described below.



Estimating daily energy expenditureDaily energy expenditure was estimated by com-bining the energy cost of different behavioursbased on basal metabolic rate (BMR, kJ/h), calcu-lated after Reynolds and Lee (1996) as:

BMR = 0.176 9 W0.635

We assumed that the average body mass (W) ofLesser White-fronted Geese was constant at1600 g (Zhao 2001) and that the energy expendi-ture for flying, feeding, alert, resting (standing, sit-ting, sleeping and loafing combined) and otheractivities (walking, preening, drinking, swimmingand social behaviour) were 14 9 BMR, 2 9 BMR,2.1 9 BMR, 1.3 9 BMR and 2.3 9 BMR, respec-tively (Hart & Berger 1970, King 1974). Thesevalues do not differ greatly from those used inother Goose studies derived from different meth-ods (e.g. Madsen 1985, Mooij 1992, Clausen et al.2013).

We recorded Goose behaviour from full-dayobservations, carried out weekly at both sites. At15-min intervals (this being the maximum timenecessary to determine the behaviours of theentire flock), scan samples were taken of all visiblebirds. At the point of first encounter, each individ-ual was assigned to a behavioural state, defined asflying, feeding, alert, standing, sitting, sleeping,walking, preening, social behaviour, drinking, loaf-ing and swimming (Altmann 1974). Activity scansof Geese started at first light and ceased when itbecame too dark to determine individual behav-iour. When Geese continued feeding after it wastoo dark to recognize behaviours, observers stayedand recorded the time at which all Geese flew tothe roost (generally less than 15 min) and assumedthat observed behaviours continued until that time(as confirmed using infra-red imagery of dusk feed-ing Greenland White-fronted Geese Anser albifronsflavirostris, A.D. Fox pers. obs.).

Geese can forage at night (Owen & Black1990), contributing to the energy budget calcu-lated by day, but we found no evidence of this inour study. Lesser White-fronted Geese alwaysflew from the roost sites to feed in the morning,and ceased feeding and flew back in the evening.There was no feeding potential at the roost site,where large roost dropping piles were left on baresubstrates and shallow water after the birds leftto feed in the morning. No defecation wasobserved during the first hour after arrival at thefeeding sites and Geese rested for less than 10%

of the day. Geese were never heard calling or fly-ing at night, even during the full moon (Ydenberget al. 1984), so we inferred that nocturnal feedingwas rare or absent, and presume that the Geeseslept throughout the night for our energy expen-diture calculation.

Low temperatures increase energy expenditure.Below the ‘lower critical temperature’ (LCT, °C)Geese must increase their heat production to main-tain body temperature. The LCT was calculatedusing the formula of Calder and King (1974):

LCT = T0 � 4.73 9 W0.274

Here, body temperature (T0) was assumed tobe 40 °C. The daily heat loss below LCT (HLCT,kJ/day) was calculated following the method ofLefebvre and Raveling (1967):

HLCT = a 9 (Tb � LCT) 9 Hb

The coefficient ‘a’ (1.33) was estimated by aquadratic regression of heat loss coefficientsagainst body mass, based on data provided in Le-febvre and Raveling (1967). Tb and Hb are averagetemperature and hours below LCT, respectively.By assuming a uniform distribution of the ambienttemperature ranging from minimum to maximumtemperature throughout the course of a day, wecalculated daily Tb and Hb. Average daily HLCT

was then factored into daily energy expenditure.We used daily ambient maximum and minimumtemperatures from Yueyang City (TuTiempo2011), about 35 km from the study area. This isthe most accessible, local source of meteorologicaldata, and we assumed that urban effects on tem-peratures were negligible.

Estimating daily metabolizable energy intakeTo estimate daily metabolizable energy intake(MEI) we needed to estimate the digestive effi-ciency and the energy contents of food plants anddroppings. Digestive efficiency was adjusted for bytaking into account the relative concentrations of anon-digestible marker, acid detergent fibre (ADF),in the food items and faeces (Durant 2003, Durantet al. 2003, van Gils et al. 2008). Chemical com-position of plants and therefore their digestibilitymay vary with date (Prop & Vulink 1992) andplant parts (Ely & Raveling 2011). For this reason,we took plant samples by simulating Goosegrazing, removing the top 4 cm from leaf tipsfrom Carex, Eleocharis, Alopecurus, Poa, Cynodonand dicotyledonous species at monthly intervals.


580 X. Wang et al.

Plant and dropping samples were oven-dried at50 °C for 24 h. Ground dropping and plant sam-ples were then analysed for ADF using a FOSS�

Fibertec 2010 fibre analyser following the methodsof Goering and van Soest (1970). Dry mass intakeof each food plant species i (mFi) per unit drop-ping mass was calculated as:

mFi ¼ PMi �ADFdP

iðPMi �ADFiÞ

where ADFd is the ADF percentage in droppingsand ADFi is the ADF percentage in plant species i(see Supporting Information Tables S2 and S3 forvalues). Mass determinations reported here allrelate to ash-free values.

Total energy contents of plants and droppingswere measured by a Parr� 1281 calorimeter. Wecould then estimate the metabolizable energyintake (MEI) as:

MEI ¼X

i

MFi �Qi �mT �Qd �mT

where Qi and Qd represent the total energy con-tent (kJ/g) of food species i and droppings (seeTables S2 and S3 for values), respectively, mT isthe daily total defecation mass calculated from themean dropping interval (td), average droppingmass (md) and total time spent active (tA):

mT ¼ tAtd

�md

based on values presented in Suppoprting Informa-tion Table S4. We directly observed dropping inter-vals of Geese by recording the time length betweentwo consecutive droppings of a randomly selectedindividual. We obtained at least 30 records perweek in each site, and averaged them as td.

According to sample availability, weekly or fort-nightly energy budgets were calculated and statisti-cally analysed. The weekly or fortnightly valueswere combined into monthly averages in figures andtables in order to fit the time scale of other figures.

Field assessments of the energy storesof Geese

Abdominal profile indices (APIs; Owen 1981) arewidely used in Goose research as a visual non-invasive means of assessing body condition in the

field (Boyd et al. 1998, Drent et al. 2003, Propet al. 2003). Ordinal API scores show a positivecorrelation with body mass and abdominal fatstores of Geese across species (F�eret et al. 2005,Madsen & Klaassen 2006). Field-sampled APIscores were used to assess changes in lipid energystores of Geese within the population as a whole.Regular samples of more than 60 randomly selectedindividuals were taken on each observation date atCaisang and Daxi Lakes, assigning individuals toreference API states (Supporting Information Fig.S1). To avoid systematic between-observer bias, allAPI observations were recorded by the same obser-ver (P.C.).

Data analysis and statistics

Collections of dropping samples, time budget anddropping interval observations were conducted fort-nightly in 2008/2009 and weekly in 2009/2010,and food plant samples were collected monthly.Fortnightly (in 2008/2009) or weekly (in 2009/2010) energy budgets for Lesser White-frontedGeese were compiled to monthly averages at eachsite from 15 October to 31 March. In 2008/2009,above-ground green biomass samples were collectedmonthly from October to January and fortnightlyfrom February to March to detect the rapid growthof plants. In 2009/2010, above-ground green bio-mass samples were collected fortnightly with addi-tional samplings during the plant growing seasons.

All statistical analyses were performed using the R

2.12.2 statistical program (R Development CoreTeam 2011). We considered Caisang Lake in 2008/2009 and 2009/2010 as different ‘sites’ for the pur-poses of analysis because of the differences in vegeta-tion composition we expected between thetwo years. To examine the effects of month and siteon Goose diet, we analysed the variation in foodcomponents using a multivariate analysis of variance(MANOVA). In this analysis, we used the proportion ofEleocharis, Grass and Carex in the droppings asresponse variables, feeding site and month as fixedfactors, and an interaction term between feedingsites and months. Dicots and other species wereexcluded because of their low overall contributionto faecal content. We calculated Pillai’s trace statistic(V) as a multivariate tool to assess whether therewere significant differences between these catego-ries. When differences were detected, we analysedthe variation in each response variable (the food spe-cies proportion) separately using ANOVA with the



same fixed factors and Tukey’s HSD post-hoc tests.To assess differences in energy budget between thethree sites/years, we performed a two-way ANOVA

with site/year, month and the interactions as fixedeffects followed by a post-hoc pairwise Tukey’s HSDtest to determine differences in energy budgetsbetween sites/year.

To test for differences in available food, we alsoperformed a MANOVA to examine the effect of thesite, season and their interaction on the above-ground green biomass of Eleocharis, Grass and Ca-rex, which was expressed in mean g/m based on the20 quadrats in Caisang Lake and five quadrats inDaxi Lake, from the three sites/years. Because ofsmall sample sizes in certain months, we combinedabove-ground green biomass of each sampling eventinto three seasons: autumn (15 October to 14December), winter (15 December to 14 February)and spring (15 February to 31 March). We analysedindividual food plant biomass using ANOVA with thesame fixed factors and Tukey’s HSD post-hoc tests.

We tested for differences in API at CaisangLake between the two years. Although API valuesare ranked intervals data, there is a linear relation-ship between API and lipid stores of Geese (Mad-sen & Klaassen 2006) and Shapiro–Wilk testsconfirmed that the values derived in this studyconformed to a normal distribution. We thereforeconducted repeated-measures ANOVA with observa-tion year, period (defined as quarters of a month)and a year 9 period interaction as fixed factors,and used Tukey’s HSD post-hoc tests to assessdifferences in API scores between periods andyears. Following Owen et al. (1992), we predicteda linear correlation between mean daily changes inmean population API scores and the calculatedaverage net daily energy budget (kJ/day) for thesame periods in both study years at Caisang Lake,assuming the depletion of body stores to meetenergy deficits. Data collected during the first15 days after arrival in autumn were excludedfrom the regression, because migratory birds mayallocate energy to reconstruct organs rather thanfat storage immediately after autumn migration(Piersma & Lindstr€om 1997, Piersma et al. 1999).

Due to differences in sampling intervals for dif-ferent variables, we used three different time scalesin different analyses: we examined the effect of‘Month’ on Goose diet and energy budget, theeffect of ‘Season’ on food supply, and the effect of‘Period’ on API as defined above. To comparechanges over time between different variables we

always plotted monthly averages in the figures, butin the analyses we used the raw data (samplingfrequency varied between variables, see above).

RESULTS

Food supply and geese utilization

Available plant food biomass at Caisang and DaxiLakes differed greatly (Fig. 2). Available plant foodbiomass differed significantly among seasons(Pillai’s V = 0.98, F6,78 = 12.45, P < 0.001), sites(V = 1.25, F6,78 = 21.68, P < 0.001) and theirinteraction (V = 0.59, F12,120 = 2.42, P = 0.007;Table 1). At Caisang Lake the delay in water levelrecession inhibited autumn growth of food plantsin 2009/2010, in contrast to the peak in above-ground green biomass at the same site in autumn2008/2009. The overall production of food bio-mass in winter and spring was also much lower in2009/2010 than in 2008/2009 at Caisang Lake(V = 0.79, F3,19 = 24.48, P < 0.001; Fig. 2). Inparticular, there was significantly less Eleocharisand Grass biomass in 2009/2010 compared with2008/2009 (ANOVA and Tukey’s HSD test,P < 0.001, Fig. 2 and Table 1). Carex biomass atDaxi Lake in 2009/2010 greatly exceeded that atCaisang Lake in both years (ANOVA and Tukey’sHSD test, P < 0.001; Fig. 2 and Table 1). How-ever, in all sites/years, above-ground green biomassof Carex did not change during the course of thewinter (F2,40 = 0.78, P = 0.45; Table 1).

Fewer Geese used Caisang Lake in 2009/2010(mean Goose numbers 330.9 � 54.9 se, n = 45)than in 2008/2009 (1086.3 � 212.7 se, n = 36),especially in autumn and spring, when food bio-mass had been highest in 2008/2009 (Fig. 3). In2009/2010, Goose numbers at Caisang and Daxilakes were similar (330.9 � 54.9 se, n = 45 and310.4 � 62.9 se, n = 92, respectively), eventhough feeding areas at Daxi Lake were much lar-ger, and Goose densities therefore lower (Fig. 3),than at Caisang Lake. Variance in Goose numbersat Daxi Lake was much higher than at CaisangLake, with more zero counts in 2009/2010 (36 of92 at Daxi vs. 9 of 45 at Caisang Lake).

Diet composition

Diet composition varied significantly among feed-ing sites (V = 1.12, F6,60 = 12.73, P < 0.001) and‘Month’ (V = 0.96, F15,93 = 2.90, P < 0.001), and


582 X. Wang et al.

the strength of dietary differences among feedingsites changed over time (site 9 ‘Month’ interac-tion, V = 1.20, F30,93 = 2.07, P = 0.004; Table 1).The effect of ‘Month’, however, was significant

only for Eleocharis (F5,31 = 5.79, P < 0.001) andnot for Grass (F5,31 = 1.86, P = 0.13) or Carex(F5,31 = 0.32, P = 0.90). Amongst food items atCaisang Lake, only the amount of Eleocharis in the

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Figure 2. Above-ground green biomass (g/m2 � se) at (a) Caisang Lake in 2008/2009 (based on Cong et al. 2012), (b) CaisangLake in 2009/2010 and (c) Daxi Lake in 2009/2010. The mean above-ground green biomass (g/m2 � se) of each month was com-piled from the average above-ground green biomass of one or more sampling events during the non-growing or growing period,respectively. Note that the scale of the y-axis varies between panels.



diet differed significantly between 2008/2009 and2009/2010 (Table 1). At Caisang Lake, the Carexcontribution to the diet was uniform and relativelyhigh throughout 2009/2010. At Caisang Lake in2008/2009, however, Eleocharis dominated thediet during the growth periods in autumn andspring, together with grasses and Carex, and Carexmade up the majority of the diet in winter(Fig. 4). In 2009/2010, the proportion of Eleochar-is in the diet was significantly less than in 2008/2009 (t19 = 4.15, P < 0.001, Table 1), with ele-vated proportions of Carex and dicots in the diet.At Daxi Lake, Carex dominated the diet (taken insignificantly greater proportions than at CaisangLake) but significantly less grass was taken therethan at Caisang (see Fig. 4 and Table 1).

Energy budgets

We calculated daily energy budgets of the LesserWhite-fronted Goose feeding at Caisang and DaxiLake on a monthly basis (Fig. 5a) based on datapresented in Tables S1–S4. The two-way ANOVA

showed significant differences in energy budgetbetween the feeding sites (F2,23 = 8.50, P = 0.001)and ‘Month’ (F5,23 = 4.13, P = 0.008) but nointeraction was detected (F10,23 = 1.98, P = 0.09).Tukey’s HSD tests (P < 0.05) indicated that theenergy budget of Lesser White-fronted Geese wassignificantly higher at Caisang Lake in 2008/2009 (259 � 157 kJ/day; Fig. 5a) and 2009/2010 (69 � 147 kJ/day) than at Daxi Lake(�338 � 72 kJ/day) in all months. At Caisang Lake,

Table 1. Results of analyses of variance (ANOVA) separately for individual food plants examining (a) the effects of ‘Season’ and ‘Site’on the food supply (available biomass) of each major dietary plant component (Eleocharis, Grass and Carex), and (b) the effects of‘Month’ and ‘Site’ on each major diet component (Eleocharis, Grass and Carex) in the faecal material of the Lesser White-frontedGeese wintering at Caisang Lake in 2008/2009 and 2009/2010, and Daxi Lake in 2009/2010. Significant contrasts are derived frompairwise Tukey’s HSD comparisons between sites after adjusting for ‘Season’ and ‘Month’, respectively. As sampling intervals dif-fered between food biomass and faecal material collections, analyses used different timescales (see Methods).

Factor df F ratio P Significant contrasts

(a) Food supplyEleocharisSeason 2 4.97 0.012 Caisang 2008/2009 vs. Daxi 2009/2010: P < 0.001Site 2 10.85 < 0.001 Caisang 2009/2010 vs. Daxi 2009/2010: P = 0.80Season*Site 4 2.31 0.074 Caisang 2008/2009 vs. Caisang 2009/2010: P < 0.001Residual 40

GrassSeason 2 22.68 < 0.001 Caisang 2008/2009 vs. Daxi 2009/2010: P < 0.001Site 2 12.96 < 0.001 Caisang 2009/2010 vs. Daxi 2009/2010: P = 0.89Season*Site 4 2.74 0.042 Caisang 2008/2009 vs. Caisang 2009/2010: P < 0.001Residual 40

CarexSeason 2 0.78 0.47 Caisang 2008/2009 vs. Daxi 2009/2010: P < 0.001Site 2 54.10 < 0.001 Caisang 2009/2010 vs. Daxi 2009/2010: P < 0.001Season*Site 4 1.11 0.36 Caisang 2008/2009 vs. Caisang 2009/2010: P = 0.62Residual 40

(b) Goose dietEleocharisMonth 5 5.79 < 0.001 Caisang 2008/2009 vs. Daxi 2009/2010: P < 0.001Site 2 51.74 < 0.001 Caisang 2009/2010 vs. Daxi 2009/2010: P = 0.24Month*Site 10 4.76 < 0.001 Caisang 2008/2009 vs. Caisang 2009/2010: P < 0.001Residual 31

GrassMonth 5 1.86 0.13 Caisang 2008/2009 vs. Daxi 2009/2010: P = 0.024Site 2 7.59 0.002 Caisang 2009/2010 vs. Daxi 2009/2010: P = 0.002Month*Site 10 1.11 0.38 Caisang 2008/2009 vs. Caisang 2009/2010: P = 0.38Residual 31

CarexMonth 5 0.32 0.90 Caisang 2008/2009 vs. Daxi 2009/2010: P < 0.001Site 2 29.53 < 0.001 Caisang 2009/2010 vs. Daxi 2009/2010: P < 0.001Month*Site 10 0.72 0.70 Caisang 2008/2009 vs. Caisang 2009/2010: P = 0.065Residual 31


584 X. Wang et al.

energy budgets did not differ significantly betweenyears.

Field assessments of fat stores

Geese arrived at Caisang Lake with similar low fatstores following autumn migration in both years(Fig. 5b). There were no significant differencesbetween the API scores of Geese between the2 years before the second half of December(P > 0.99 for API in the third week of November

and P > 0.99 for API in the first week of Decem-ber). Due to prolonged high water levels in Cai-sang Lake, Geese were not able to maintain afavourable energy budget in 2009/2010. As aresult, energy budget surpluses were insufficientfor Geese to accumulate the same levels of fatstores by December, and API scores in 2009/2010were significantly lower in each month than in2008/2009 from late December through to thefollowing spring. In the last week of March, APIscores were still lower in 2009/2010 (3.32 � 0.04

(a)

(b)

(c)

Figure 3. Daily maximum density (Geese/ha) of Lesser White-fronted Goose counted at (a) Caisang Lake in 2008/2009 (based onCong et al. 2012), (b) Caisang Lake in 2009/2010 and (c) Daxi Lake in 2009/2010.



0%

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15 Oct –14 Nov

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15 Jan –14 Feb

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15 Mar –31 Mar


(a) Caisang Lake 2008/09

(b) Caisang Lake 2009/10

(c) Daxi Lake 2009/10

Figure 4. Diet composition of Lesser White-fronted Geese at (a) Caisang Lake in 2008/2009 (based on Cong et al. 2012), (b) Cai-sang Lake in 2009/2010 and (c) Daxi Lake in 2009/2010. The mean diet composition of each month was compiled from the dietcomposition of several within-month sampling events. Diet composition is based on faecal analysis and expressed as the percentageof total fragment area of each species.


586 X. Wang et al.

se) than in 2008/2009 (3.60 � 0.05 se, P =0.014).

There was a significant correlation between thedaily change in mean API score (y) and the calcu-lated daily energy budgets of Geese (x, in kJ/day)(y = 0.0000816 (� 0.0000127 se) x + 0.0133(� 0.00375 se), r2 = 0.82, P < 0.001), and therewas little difference between the two years in theslope of the relationship (F1,6 = 4.13, P = 0.090)and no difference in the intercept (F1,6 = 0.002,P = 0.955).

DISCUSSION

Differences in the estimates of energy budgets ofwintering Lesser White-fronted Geese foraging on

two different habitat types support the predictionthat food availability can explain between-site andbetween-season variation in body conditionamongst individuals at the largest non-breedingaggregation of this species in the world. Geese thatfed on fresh growth from recessional grasslands atCaisang Lake either balanced or maintained a posi-tive energy budget during October/November andin February/March of both years, which enabledaccumulation of fat stores during both periods.They failed to balance their energy budgets whenfeeding on sedge beds at Daxi Lake, to which theyresorted mostly in mid-winter. From late Novem-ber to early February, Lesser White-fronted Geesefeeding on Carex failed to balance their energybudget and those feeding on recessional grassland

1

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1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4Mea

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Figure 5. (a) Mean daily mean energy budget (kJ/day � se) for the 6-monthly periods of Lesser White-fronted Geese feeding atCaisang Lake in 2008/2009, Caisang Lake in 2009/2010 and Daxi Lake in 2009/2010, which was compiled by fortnightly (in 2008/2009) or weekly (in 2009/2010) energy budget estimates. (b) Mean abdominal profile index scores (� se) for each weekly interval(1–4) over the same winter monthly periods at Caisang Lake in 2008/2009 and 2009/2010. Symbols above the data points indicateno significant difference (‘–’, P > 0.05) and significant difference (‘*’, P < 0.05) between years, based on repeated-measure ANOVA

and Tukey’s HSD post-hoc tests.



could only marginally reach a positive energy bud-get, necessitating depletion of energy stores accu-mulated in autumn. This pattern was concordantwith changes in API scores, which provided a reli-able surrogate of body condition, based on thestrong correlation between changes in API and innet energy budgets. The API variation throughoutthe wintering period indicates that Lesser White-fronted Geese behaved similarly to winteringGeese elsewhere (e.g. Owen et al. 1992, Tinkleret al. 2009). It is likely that the Geese accumu-lated autumn fat stores in anticipation of mid-win-ter energy deficits which corresponded to periodsof body mass loss and stores were reconstructedprior to spring migration when day length, foodquality and quantity permitted. Although weshould be cautious about concluding too muchfrom studies undertaken in just two seasons, in theabsence of other compounding factors (such aspredator activity, disturbance or other weathereffects) to explain the low lipid reserves, we canbe reasonably confident that these recessionalgrassland communities play a key role in the acqui-sition of adequate fat stores by Lesser White-fronted Geese at East Dongting Lake.

Although we lack direct evidence, food avail-ability might affect winter survival, migration datesand, potentially, subsequent breeding success ofLesser White-fronted Geese, as in many other spe-cies (e.g. Owen & Black 1990, Ebbinge & Spaans1995, Clausen et al. 2003, Drent et al. 2003, Propet al. 2003). At Caisang Lake, the Geese depletedfat stores at similar rates in both years, but fatstores remained significantly lower throughout2009/2010 than in 2008/2009 because of reducedstores acquired in autumn 2009. Since the amountof stored endogenous fat affects the ability of anindividual to meet current and future energyneeds, especially during periods of food shortage,autumn food availability has potential fitness con-sequences for the Geese later in winter. In severeweather, with high thermoregulatory demands andpoor food supply, Geese could deplete stores tothe point of death by starvation (e.g. Beer & Boyd1964). We therefore infer that access to food fromrecessional grasslands affects the ability of LesserWhite-fronted Geese to accumulate fat stores,which could have fitness consequences. Anotherpossible consequence of poor food supply could bea delay in spring departure date; in 2009/2010when API values changed relatively rapidly on adaily basis, spring departure (3 April 2010) was

delayed compared with 2008/2009 (30 March2009, P. Cong pers. obs.). The late spring depar-ture may reduce breeding success and, in turn,influence the population abundance (Drent et al.2003, Newton 2004).

The importance of energy stores to meet cur-rent and future expenditure needs of the Geese inwinter indicates their vulnerability to anthropo-genic disturbance and water table variation, andthus highlights the conservation significance ofmanaging these factors. Where present, anthropo-genic disturbance (such as buffalo herding, fishingand gathering of plant material) will incur addi-tional energy expenditure associated with escapeflight (Hart & Berger 1970, King 1974). This maybe especially critical in mid-winter when theopportunities to compensate for such energy lossare constrained by a food supply that already failsto meet daily energy expenditure. The differencesin water table levels between years had contrastingeffects on the availability and abundance offavoured food items, which affected the Gooseenergy budget surpluses in the two years of thisstudy. The Yangtze River is characterized by itsstrong seasonal flooding cycle (Shankman & Liang2003) but since 2003 this has been regulated bythe Three Gorges Dam, causing significant changesto the vegetation in the surrounding wetlands (Yuet al. 2011) and the waterbirds that rely upon thewetlands for their nutrition (e.g. Zhang et al.2011, Zhao et al. 2012). Whilst the presence andpersistence of the perennial sedge meadows arerelatively robust to variations in water level fluctu-ations, the distribution and abundance of Eleochar-is and Alopecurus communities are highlydependent on the timing of exposure of substrates(Deil 2005, Barzen 2008). In autumn 2009/2010,when prolonged high water levels greatly reducedthe availability of the recessional food plant bio-mass, especially Eleocharis, Geese were unable tobalance energy budgets and suffered reduced fatstores for the rest of the winter. In both seasons,Geese relied upon recessional grasslands to recoupdepleted fat stores in preparation for spring migra-tion. As the temperature characteristics of the twowinters differed relatively little (Supporting Infor-mation Table S5), and the thermoregulatory costsare relatively modest in relation to energy expendi-ture, energy intake was likely to play a moreimportant role than between-year differences inexpenditure. For these reasons, we consider thatsympathetic management of the water table


588 X. Wang et al.

regime to encourage growth of food items (espe-cially Eleocharis and Alopecurus), as well as ensur-ing disturbance-free feeding sites at Caisang Lakeand elsewhere in East Dongting Lake, will benefitwintering Lesser White-fronted Geese.

Finally, these findings also suggest that foodconstraints contribute to explaining the currentrestricted distribution of wintering Lesser White-fronted Geese in China. Sedge meadows are a pre-dictable, widespread and abundant source of foodand Carex is the primary food for many winteringGeese in the Yangtze River floodplain (Lu &Zhang 1996). This study shows that Carex doesnot constitute an energetically profitable foodsource for Lesser White-fronted Geese. Carexmeadows are relatively widespread at Dongting,Poyang and Shengjin Lakes, as well as other wet-lands throughout the Yangtze River floodplain(Cheng et al. 2009, Li et al. 2010, Yu et al. 2011,Zhao et al. 2012). This might explain why so fewLesser White-fronted Geese occur at other lakescharacterized by sedge meadows, which lack Eleo-charis/Alopecurus recessional grasslands, as is thecase at Shengjin Lake (Zhao et al. 2010). Theseephemeral recessional graminoid communitiesoccur on exposed substrates at low biomass (Conget al. 2012) and are difficult to identify fromremote sensing imagery, so their presence andextent at East Dongting Lake or elsewhere in theYangtze River floodplain is hard to determine.Our limited experience is that they are largelyconfined to Chunfeng and Caisang Lakes at EastDongting Lake, which may explain the highlyrestricted winter distribution of the Lesser White-fronted Goose within China. Lesser White-frontedGeese rarely fed with other herbivorous Goosespecies (Bean Anser fabalis and Greater White-fronted Geese A. albifrons) at Daxi Lake in mid-winter, when they grazed separately on the short-est (< 60 mm) sedge swards compared with the120–200 mm swards consumed by the two largerGoose species (P. Cong unpubl. data). Only theLesser White-fronted Geese grazed the short(< 60 mm) recessional grassland swards of CaisangLake, which developed on bare mud in a similarfashion to those of Hungarian recessional wetlandsand fish ponds after autumn water level drawdown(Tar et al. 2009), ephemeral recession meadows ofLake Kerkini and Evros Delta in Greece (Øienet al. 2009), the steppes and ephemeral wetlandsof Azerbaijan and spring staging areas in Finland(Markkola et al. 2003), which are used elsewhere

in the range of this species. This suggests that Les-ser White-fronted Geese may avoid competitionwith larger-bodied, more numerous and widespreadGoose species by grazing dense swards of shortephemeral graminoid plants, especially those associ-ated with recessional wetlands that expose bare mudsubstrates. Bill size, handling times and allometricrelationships (Durant et al. 2004) may enable a spe-cialist herbivore such as the Lesser White-frontedGoose to maintain high food intake rates on suchgrasslands which larger Geese and smaller herbivo-rous ducks (e.g. Eurasian Wigeon Anas penelope)cannot achieve. This may result in Lesser White-fronted Geese avoiding competition but may con-tribute to their localized distribution and raritythroughout the northern hemisphere, in contrast tothe more numerous larger AnserGoose species.

We would like to thank Mark Barter for his inspirationand Fred de Boer for constructive comments on earlydrafts of this paper, East Dongting Lake National NatureReserve for permission to work in the nature reserve andassistance with field work, Cai Chunyan for statisticalanalyses, Meng Fanjuan, Liu Jing, Yang Xiuli, Yu Xiaoxiand Yang Wei for field observations and sample analysis,and Wang Qing for API drawings. The study was sup-ported by the National Basic Research Program of China(973 Program, Grant No. 2012CB956104), NationalNatural Science Foundation of China (Grant No.31071941), University of Science and Technology ofChina Graduate School Educational Innovation Base, plusa Chinese Academy of Sciences Visiting Professorship forSenior International Scientists (2011T1Z04), and StateAdministration of Foreign Experts Affairs, PRC. We areextremely grateful to Eileen Rees, Bob Clark, RuediNager and an anonymous referee for suggesting improve-ments to earlier drafts of this manuscript.

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Received 8 April 2012;revision accepted 8 January 2013.Associate Editor: Robert Clark.

SUPPORTING INFORMATION

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

Figure S1. Abdominal profile index (API) forthe Lesser White-fronted Goose, reference draw-ings illustrating differences in energy deposits,body shape and corresponding API scores.

Table S1. Components of the energy budgets(� se) of the Lesser White-fronted Geese feedingat Caisang Lake in 2008/09 and 2009/10 and atDaxi Lake in 2009/10; “n” represents the numberof replicates in each calculation. All values areexpressed in kJ/day; minor discrepancies arise fromrounding to nearest integer values.

Table S2. Food quality of dietary items of theLesser White-fronted Geese feeding at Caisangand Daxi Lakes in 2008/09 and 2009/10. All val-ues are shown as ash-free dry weight.

Table S3. Ash, acid detergent fibre and calorificcontent of Lesser White-fronted Goose droppingscollected from Caisang Lake in 2008/09 and 2009/10 and from Daxi Lake in 2009/10; “n” representsthe number of replicates in each calculation.

Table S4. Dropping interval � se and droppingmass � se (dry weight) of the Lesser White-frontedGeese feeding at Caisang Lake in 2008/09 and2009/10 and at Daxi Lake in 2009/10.


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