Oecologia (2003) 134:332–342
DOI 10.1007/s00442-002-1124-0
ECOPHYSIOLOGY
Hans Schekkerman · Ingrid Tulp · Theunis Piersma ·
G. Henk Visser
Mechanisms promoting higher growth rate in arctic than
in temperate shorebirds
Received: 4 June 2002 / Accepted: 29 October 2002 / Published online: 18 December 2002
Springer-Verlag 2002
Abstract We compared prefledging growth, energy expenditure, and time budgets in the arctic-breeding red
knot (Calidris canutus) to those in temperate shorebirds,
to investigate how arctic chicks achieve a high growth
rate despite energetic difficulties associated with precocial development in a cold climate. Growth rate of knot
chicks was very high compared to other, mainly temperate, shorebirds of their size, but strongly correlated with
weather-induced and seasonal variation in availability of
invertebrate prey. Red knot chicks sought less parental
brooding and foraged more at the same mass and
temperature than chicks of three temperate shorebird
species studied in The Netherlands. Fast growth and high
muscular activity in the cold tundra environment led to
high energy expenditure, as measured using doubly
labelled water: total metabolised energy over the 18-day
prefledging period was 89% above an allometric prediction, and among the highest values reported for birds. A
comparative simulation model based on our observations
and data for temperate shorebird chicks showed that
several factors combine to enable red knots to meet these
high energy requirements: (1) the greater cold-hardiness
of red knot chicks increases time available for foraging;
(2) their fast growth further shortens the period in which
chicks depend on brooding; and (3) the 24-h daylight
H. Schekkerman ()) · I. Tulp
Alterra, P.O.Box 47, 6700 AA Wageningen, The Netherlands
Tel.: +31-317-478759
Fax: +31-317-419000
e-mail: h.schekkerman@alterra.wag-ur.nl
H. Schekkerman · I. Tulp · T. Piersma
Working Group International Waterbird and Wetland Research,
P.O. Box 925, 3700 AX Zeist, The Netherlands
T. Piersma
Netherlands Institute for Sea Research,
P.O.Box 59, 1790 AB Den Burg, The Netherlands
G. H. Visser
Centre for Isotope Research,
Nijenborgh 4, 9747 AG Groningen, The Netherlands
H. Schekkerman · T. Piersma · G. H. Visser
Centre for Ecological and Evolutionary Studies,
University of Groningen,
P.O.Box 14, 9750 AA Haren, The Netherlands
increases potential foraging time, though knots apparently
did not make full use of this. These mechanisms buffer
the loss of foraging time due to increased need for
brooding at arctic temperatures, but not enough to satisfy
the high energy requirements without invoking (4) a
higher foraging intake rate as an explanation. Since
surface-active arthropods were not more abundant in our
arctic study site than in a temperate grassland, this may be
due to easier detection or capture of prey in the tundra.
The model also suggested that the cold-hardiness of red
knot chicks is critical in allowing them sufficient feeding
time during the first week of life. Chicks hatched just after
the peak of prey abundance in mid-July, but their food
requirements were maximal at older ages, when arthropods were already declining. Snow cover early in the
season prevented a better temporal match between chick
energy requirements and food availability, and this may
enforce selection for rapid growth.
Keywords Calidris canutus · Energy expenditure ·
Precocial chicks · Time budget · Tundra arthropods
Introduction
Compared to temperate and tropical environments, arctic
regions present two main problems to warm-blooded
animals: the cold climate imposes high thermoregulatory
costs, which must be matched by food intake, and a short
period of increased food availability sets a narrow
window for reproduction in many species (e.g. Chernov
1985; Carey 1986). The selective force thus exerted on
arctic animals includes morphological, physiological and
behavioural characteristics. With respect to reproduction,
developmental mode and growth rate of offspring are
traits likely to be affected by this selection, as they affect
both time and amount of energy required.
Many species of shorebirds (Charadrii), especially
within the Scolopacidae (sandpipers, snipes and allies),
breed in the boreal and arctic climate zones (Piersma et al.
1996). They have precocial young that forage for
themselves from hatching onwards, leading to high
muscular activity and prolonged exposure to outdoor
333
conditions. This ontogenetic mode should lead to a high
energy expenditure (Schekkerman and Visser 2001),
especially in the cold and shelter-poor arctic tundra
(Norton 1973). Thus, arctic shorebird chicks may need
more food to achieve growth than young birds at
temperate latitudes and also more than parent-fed chicks
in the Arctic. At the same time, small shorebird chicks are
not yet homeothermic at low ambient temperatures
(Chappell 1980; Beintema and Visser 1989a; Visser and
Ricklefs 1993; Visser 1998), hence a cold climate
increases their need for parental brooding, and shortens
potential feeding time. At first sight therefore, selffeeding precociality seems to be a mode of development
not agreeing well with the arctic environment. Nevertheless, shorebirds constitute a large proportion of arctic
tundra bird communities (Chernov 1985; Boertmann et al.
1991; Troy 1996), and arctic species show the highest
growth rates among shorebirds (Beintema and Visser
1989a; Schekkerman et al. 1998a, 1998b), so the thermal
difficulties must be offset in some way. It has been
suggested that compared to lower latitudes, insect food is
more abundant in the arctic summer (e.g. Lack 1968;
Salomonsen 1972; Andreev 1999), while the continuous
summer daylight provides extra feeding time (Karplus
1952; Lack 1954). To make full use of this, chicks could
have developed thermal adaptations to reduce the need for
brooding at low temperatures (e.g. Koskimies and Lahti
1964; Chappell 1980). To date, no study has evaluated
these hypotheses in an integrated way.
We studied prefledging energy expenditure and time
budgets of red knot Calidris canutus chicks in the
Siberian Arctic, to test whether they are indeed energetically expensive. The red knot is one of the most northerly
breeding shorebirds, confined to arctic tundra and polar
desert (Piersma and Davidson 1992; Tomkovich and
Soloviev 1996), yet shows one of the fastest growth rates
found in this group. We compare energy expenditure and
time budgets of knot chicks and the abundance of their
invertebrate prey with those of temperate shorebirds in
grasslands in The Netherlands (Schekkerman 1997;
Schekkerman and Visser 2001), and use a simulation
model based on the comparative data to evaluate the three
hypothetical mechanisms for enabling red knots to grow
so fast despite the energetic challenge posed by their
environment.
Materials and methods
Study area
We studied breeding red knots at Cape Sterlegov on the Taimyr
Peninsula, Siberia (7525'N, 8908'E) from 10 June to 12 August
1994 (Tulp et al. 1998). The study area consisted of 12 km2 of arctic
tundra (sensu Chernov 1985) bordering the Kara Sea, between 0 and
50 m a.s.l. Vegetation was dominated by mosses and lichens with a
considerable proportion of bare ground in the form of clay
medallions or ‘frost boils’, and with a denser cover of grasses and
sedges in moister parts. Some scattered stone ridges and rocky
outcrops were present. Several small marshes and streams drained
the area.
Red knot growth and behaviour
Fourteen Red knot nests and 25 broods were found by flushing
incubating birds from underfoot or by rope-dragging, and by
traversing the study area intensively after hatching started. Any
chicks encountered were ringed, and most accompanying adults
(males) were trapped and individually colour-ringed. Two adult
males, one captured on the nest and the other on 1-day-old chicks,
were fitted with a radio transmitter (Holohil, Canada, type BD-2,
1.8 g) glued to feather bases on the lower back (Warnock and
Warnock 1993). The transmitters were used to relocate broods for
doubly labelled water experiments (see below) and behavioural
observations. One tagged male lost its chicks to predators after a
week, but the other fledged two young.
Throughout the prefledging period, chicks were recaptured
whenever possible to record their growth (103 recaptures of 37
chicks from 13 broods). Weights were determined with spring
balances, accurate to 0.1–1 g. Body mass growth was described by
a logistic curve. Because the exact age of many chicks was
unknown as they had already left the nest when first encountered,
the logistic growth rate parameter was estimated from mass
increments of chicks captured at least twice (Schoener and
Schoener 1978; Ricklefs 1983), using non-linear regression.
Hatchling mass was measured in the field, and the asymptote was
fixed at 120 g, the mean mass of first-year red knots wintering in
West Africa (Wymenga et al. 1992).
To analyse environmental effects on growth rate, mass increments were used of chicks at least a day old and captured twice at
intervals of 15 days (mean 1.7 days, SD=1.23, n=87). To make
growth rates at different ages comparable, observed mass increments were divided by those predicted from the logistic equation at
the given starting mass and recapture interval. These indices were
regressed on average temperature and food availability during the
interval. By treating chick and brood as random variables in linear
mixed models (Byrk and Raudenbusch 1992), we took into account
that the data represent three nested error levels (multiple observations on several chicks from the same brood). The program MLN
(Institute of Education 1995) was used for model fitting. To avoid
bias due to possible effects of doubly labelled water trials on growth
rate, mass increments during such measurements were excluded.
Time budget observations were made on three different broods
for a total of 62.6 h, covering all hours of the day and chick ages 0–
13 days. Observations were made from 100–300 m distance, using
a telescope. Behaviour of the male and chicks was recorded every
minute, distinguishing between brooding, foraging, and other
behaviours (including rest, preening, walking, and alarm). Broods
formed the recording unit, as the alternation between brooding and
foraging was highly synchronised among broodmates. The dependence of the proportion of time that chicks were brooded on chick
age and temperature was analysed by logistic regression. Observations lasting longer than 3 h were divided into sampling units of
1.5–3 (mean 2.3) h, to standardise lengths and get an appropriate
mean value for temperature, which often changed significantly over
a few hours.
Energy expenditure
Measurements of daily energy expenditure (DEE, kJ/day) of freeliving chicks were made using the doubly labelled water (DLW)
method (Lifson and McClintock 1966; Speakman 1997). Captured
chicks were injected subcutaneously in the ventral region with
0.15–0.50 ml of DLW consisting of 32% D2O and 68% H2 18O.
They were kept warm in a bag or box for an equilibration period of
0.75–1 h and structural measurements and weight were recorded.
Four to six 10–15 ml blood samples were then collected from veins
in the leg or wing, into glass capillary tubes, which were flamesealed within minutes. Chicks were released into the field and
recaptured after 19.0–25.6 h (mean 23.3 h, SD=1.5, n=15) when a
second set of blood samples and measurements was taken. In three
chicks, additional blood samples were collected before injection
with DLW to measure background isotope levels. Since broods
roamed widely over the tundra and were often difficult to relocate,
most DLW measurements were taken on chicks of the radio-tagged
males. A few measurements were made on chicks of non-tagged
334
males. At most three measurements were taken on (2) individual
chicks, separated by 3- to 6-day intervals.
2 1
H/ H and 18O/16O ratios in the blood samples were analysed
with a SIRA 9 isotope ratio mass spectrometer at the Center for
Isotope Research, Groningen, following procedures described in
Visser and Schekkerman (1999). Analyses were done in duplicate,
and a third capillary was analysed if the two measurements differed
by more than 2%. Background concentrations were 0.0143 atom-%
for 2H and 0.1989 atom-% for 18O (n=3). We calculated CO2production according to Eq. 34 in Lifson and McClintock (1966),
with fractionation factors for 18O and 2H taken from Speakman
(1997), and a value of 0.13 for the fraction of water loss occurring
by evaporation:
rCO2 ðL=dÞ ¼ ½N=2:078 ðko kd Þ
0:13 0:0249Nkd 22:4
where N is the size of the body water pool (mol), and ko and kd the
fractional turnover rates of 18O and 2H, respectively, as calculated
from the isotope measurements. In a validation study on chicks of
two related shorebirds, black-tailed godwit Limosa limosa and
northern lapwing Vanellus vanellus, this method gave an average
error of 0% (Visser and Schekkerman 1999). The errors (range 13%
to +16%) were unrelated to growth rate, indicating that the method is
accurate in chicks growing as fast as 20%/day. Because some DLW
was occasionally lost by leakage during injection, N was not
estimated from isotope dilution but from the relation between
percentage water content and the fraction of adult mass attained,
based on analysis of carcasses of lapwing and godwit chicks
(Schekkerman and Visser 2001). DEE was calculated from rCO2
using an energy equivalent of 27.33 kJ/l CO2 (Gessaman and Nagy
1988).
Total daily metabolised energy (ME) was calculated by adding
energy deposited into new tissue (Etis) to DEE in case the animal
gained weight over the measurement period, and set equal to DEE
if no weight gain occurred. Etis was estimated as the increment of
the product of body mass and energy density. The latter was taken
as ED (kJ/g)=4.38+3.21 M/Mad (M=chick body mass, g, Mad=adult
mass, 120 g), based on carcass analysis of chicks of northern
lapwing and black-tailed godwit (Schekkerman and Visser 2001).
Dependence of DEE and ME on body mass, growth rate and
weather was analysed by fitting linear mixed models, containing
chick and brood as random variables, to the log-transformed data.
Weather and arthropod abundance
Three-hourly observations of air temperature (Ta,C), wind speed
and cloud cover were obtained from a weather station 7 km from
our study site. From 3 July onwards, operative temperature (Te,C)
was automatically recorded every 5 minutes, using a blackened
copper sphere (Ø 4 cm) placed 10 cm above the ground. Te
integrates air temperature and solar radiation (but not the cooling
effect of wind) and provides a better description of the thermal
environment than air temperature alone (Walsberg and Weathers
1986). Daily means of Te were linearly related to mean Ta at the
weather station: Te=1.23Ta+1.96 (R 2=0.82, F1,34=156.6, P<0.001).
Occurrence of rain and snowfall was recorded daily.
Abundance of surface-active arthropods which constitute the
food of red knot chicks was measured in five modified pitfall traps
placed at 20 m intervals in moderately dry nanopolygonal tundra
(i.e. the habitat where most of the broods were encountered). Traps
consisted of white plastic jars (Ø 10 cm, 13.5 cm deep), filled with
1–2 cm of water and a drop of detergent to break the surface
tension. Two crossed mesh screens of 4050 cm, topped with a
plastic funnel opening into a transparent jar, were placed over the
pitfalls. In addition to surface-active animals, this structure caught
low-flying invertebrates which hit the screens and crawled either
downwards into the pitfall or upwards into the jar. Compared to
ordinary pitfalls, the modified traps caught more small Chironomid
midges and Linyphiid spiders but similar numbers of other groups
(Tulp et al. 1998). Arthropods were collected daily between
2200 hours and 2400 hours, and preserved in 4% formalin. They
were later identified to family or (sub)order (Hymenoptera,
Collembola) and body length was measured (to nearest 0.5 mm if
£5 mm; to 1 mm if larger). Dry weights were estimated from groupspecific length-weight relationships (Rogers et al. 1977; Schekkerman, unpublished). Arthropod abundance data were log-transformed before analysis. Because mites (Acari) and springtails
(Collembola) are too small to be important prey for chicks, they
were not taken into account in most analyses.
Comparison with temperate shorebird chicks
Data on red knots (growing from 13.7 g at hatching to 108 g at
fledging in 18 days) were compared with those for three temperatebreeding wader species, northern lapwing (growing from 17.5 to
142 g in 23 days), black-tailed godwit (28.6 to 201 g in 25 days)
and common redshank Tringa totanus (15.6 to 109 g in 23 days),
studied in grassland reserves in The Netherlands using similar
methods. DLW measurements of energy expenditure of lapwing
and godwit chicks were made at Baarn (5212'N, 0519'E) in 1993–
1995 (Schekkerman and Visser 2001). Time budget observations
were made from hides in 0.4–0.8 ha enclosures surrounded by a low
fence which allowed the free-living adults, but not their chicks, to
freely leave and enter. Observations were made in Flevoland
(5224'N, 540'E) in 1981 and 1984 (Beintema and Visser 1989a)
and at Baarn in 1992–1995 (Schekkerman 1997), and totalled 992 h
for godwits, 644 h for lapwing and 44 h for redshank (10, 10 and 2
broods respectively). Dependence of brooding percentages on chick
mass or age and weather variables was analysed using logistic
regression, in the same way as in red knots. Te was measured with
the same equipment at Baarn as in Siberia; temperatures measured
in Flevoland were converted to Te using regression models
incorporating air temperature, time of day and solar radiation,
based on data from Baarn.
Abundance of surface-active arthropods was measured in a
grassland reserve at Baarn between 3 May and 7 June 1994 (i.e. the
period in which most chicks are present), using the same type and
number of modified pitfall traps as in Taimyr, and identical
methods of collection, identification and analysis.
Results
Weather and arthropod availability
Upon our arrival on 11 June, the tundra was still 98%
snow-covered. Average air temperature remained below
0C until 18 June. After 19 June (90%), snow cover
declined rapidly to 50% on 21 June and 10% on 26 June.
Mean daily air temperature (Ta€SD) was 0.7€3.1C
(range 4.9–4.4) in the arrival period of red knots (10–22
June), 4.5€4.4C (range 0.9–14.2) during incubation (23
June13 July) and 0.9€1.8C (range 0.9–7.1) during
chick-rearing (14 July10 Aug). Mean operative temperature (Te) in the latter period was 2.8€2.8C (range 0.2–
10.1), and mist, drizzle or rain occurred on many days.
Daily average wind speed was mostly between 3 and 7 m/
s, with peaks up to 8–10 m/s.
Diptera were the most abundant arthropod group
caught in the modified pitfall traps at Cape Sterlegov
(60% of total number), followed by Araneae (23%),
Hymenoptera (12%) and Coleoptera (5%). Daily total
number and dry mass were strongly correlated (logtransformed data, 3 July10 August, r34=0.95, P<0.001),
and biomass was further used as an index of arthropod
availability.
Regression analysis showed a strong non-linear dependence of trapped biomass (excluding mites and
springtails) on operative temperature (Te: F1,34=62.2,
P<0.001; Te2: F1,33=41.6, P<0.001; R2 =0.65), with a
steep decline at Te<45C (Fig. 1). The occurrence of rain
335
or (wet) snowfall reduced arthropod activity (if the only
explanatory variable: F1,34=60.1, P<0.001, R2 =0.38),
even when entered into the model after temperature
(F1,32=13.3, P=0.001; R2=0.74). A negative effect of wind
speed (in isolation: F1,34=32.3, P<0.001, R2 =0.20) was no
longer significant after temperature and rain were
included (F1,31=0.37, P=0.55). Inclusion of date and
date2 after Te and precipitation further improved the
model (F2,30=5.80, P=0.007; final R2 =0.81), indicating
that independently of weather there was a unimodal
seasonal trend in arthropod activity. Predicted arthropod
availability peaked on 11 July when weather effects were
not taken into account (Fig. 1a), but on 16 July when
these were included in the regression model.
The average size-density distributions of trapped arthropods were similar between Cape Sterlegov and a Dutch
grassland managed as a meadowbird reserve (Fig. 2).
Because arthropods ‡8 mm were more abundant in The
Netherlands, mean daily trapped biomass (mean€SD:
19.0€12.0 mg.day1. trap1, n=29 days) was higher here
than at Cape Sterlegov (11.7€13.0 mg.day1.trap1,
n=31 days; t-test on ln-transformed data, t58 =3.03,
P=0.002). With mites and springtails included, this
difference was even larger (Cape Sterlegov 11.7€
13.0 mg.day1. trap1, Netherlands 31.7€18.2 mg. day1.trap1; Fig. 2).
Red knot breeding phenology and growth
Red knots were present in the study area upon our arrival
(11 June), but new migrants arrived until at least 19 June.
Most of the 14 nests (12 4-egg, two 3-egg clutches) found
in the intensive study area were depredated by an Arctic
Fox Alopex lagopus, but 11 additional broods were later
found within its borders (estimated density £2 breeding
pairs/km2), and 14 outside it. Based on direct observations, flotation of eggs and biometrics of young, eggs
hatched between 14 and 28 July. The median hatching
date was 17 July, corresponding to a first-egg date of 22
June (4 days laying, 20–21 days incubation). Incubation
was shared between sexes but females deserted at
hatching, and joined into small flocks, which disappeared
1 or 2 weeks later. Males attended the chicks alone, until a
few days after fledging. Westward migration occurred in
late July and early August, and most red knots, including
juveniles, had left the area by 10 August.
The mean mass of hatchlings still in the nest was
13.7€0.5 g (n=8). Chicks fledged when 17–20 days old,
weighing 87–114 g at last capture. Body mass growth in
relation to age (t, days) was best described as M(g)=120/
(1+8.23 e0.24 t) (SE of rate parameter KL=0.03, R 2 =0.93,
n=103 intervals from 37 chicks in 13 broods, mass range
13107 g). Conversion of KL to the Gompertz’ growth
rate parameter (Ricklefs 1983) yields KG=0.163, which is
1.9 times the value predicted for a 120 g shorebird by
Beintema and Visser (1989b). Hence, red knots are very
fast growing shorebirds.
The index of chick growth rate (growth observed /
expected at the observed mass) was positively related to
mean operative temperature during the recapture interval
Fig. 1A, B Daily arthropod dry biomass caught in pitfall traps in
relation to date. A Open dots show biomass before 3 July when no
measurements of Te were made; ln(mg)=0.082 date 0.0037
date2+3.58, F2,33=8.07, P=0.0014, R2 =0.33) and operative temperature Te. B Residuals from parabolic relationship in A
Fig. 2 Size-abundance distributions of arthropods caught in modified pitfall traps at Cape Sterlegov and in a grassland reserve in
The Netherlands. Large graph: mites (Acari) and springtails
(Collembola) excluded; inset: all groups included
(likelihood ratio test, C21=16.4, P<0.001, n=87 intervals
for 33 chicks in 12 broods). The relationship seemed nonlinear and ln(Te) gave a slightly better fit than Te (C21
=19.7, P<0.001). Adding the (negative) effect of precipitation to that of temperature further improved the model
(C21=5.23, P=0.02). However, the best fit was obtained
with the logarithm of mean daily arthropod biomass
trapped in the pitfalls as the independent variable (C21
336
Table 1 Logistic regression
analysis of the proportion of
time that red knot Calidris canutus chicks were brooded by a
parent (B), in relation to body
mass, temperature, time of day
and wind speed. Results are
given for forward stepwise inclusion of significant variables.
Two-way interactions were also
tested, but not significant (all
P>0.13). ‘Night’ was defined as
the period 2200–0400 hours.
Coefficients are for logit(B)=ln(B/(1B))
Variables in model
Constant
Chick mass (g)
Te (C)
If ‘night’
Wind speed (m/s)
Residual
Total
Change
in df
Change
in deviance
P
1
1
1
1
22
25
6.83
4.92
5.54
0.03
5.17
19.0
0.009
0.027
0.019
0.86
Coefficient
Logit(B)
(SE)
5.22
0.160
0.281
2.67
n.s.
(3.43)
(0.085)
(0.176)
(1.26)
=49.7, P<0.001; Fig. 3). This model was not improved by
the inclusion of T e (C21=1.36, P=0.24) or precipitation
(C21=0.44, P=0.51), whereas adding arthropod availability to a model including both ln(Te) and precipitation
resulted in a highly significant improvement (C21=27.7,
P<0.001). This indicates that not only weather-induced
variation in arthropod availability affected growth, but
also seasonal variation. One chick lost an exceptional 8 g
in a day (growth index 3.2; Fig. 3); because this
occurred on a cold day with very low arthropod activity,
omitting this data point did not change the results.
Time budgets
Of 62.6 observation hours, red knot chicks were brooded
by the parent during 39%. In chicks older than 8–9 days,
brooding was observed only rarely. Of the remaining time,
chicks spent 98% foraging (other behaviours slightly
underestimated as preening, resting and alarm events
lasting <1 min were not recorded). Brooding was thus the
key determinant of feeding time for young chicks.
The time that chicks were brooded declined strongly
with increasing body mass and Te (Table 1). In addition to
these effects, brooding occurred most often between 2200
and 0400 hours. Wind speed had no discernible effect on
brooding, nor were any interaction effects significant.
Results were very similar when age was used as
independent variable instead of body mass.
At the same mass (or age) and temperature, red knot
chicks were brooded less than temperate shorebird chicks
observed in The Netherlands (Fig. 4, Table 2). The
difference between knot and redshank (smallest samples),
was close to significance (‘species’ added to logistic
model with mass, Te and ‘night’: X21=3.62, P=0.057); it
was significant when age was used instead of mass (X21
=4.47, P=0.035), due to the knots’ faster growth.
Differences with black-tailed godwit (X21=11.0,
P<0.001) and northern lapwing (X21=29.9, P<0.001)
were highly significant, despite the knots’ smaller size.
Energy expenditure
Fifteen DLW experiments were completed on 10 chicks
from 5 broods. During 12 of these the chicks gained mass
at an average rate of 5.3 g/day (SE=0.3), or a growth
index of 0.82 (SE=0.05) compared to the average growth
Fig. 3 Relationship between the growth index of red knot chicks
(growth observed / predicted at observed mass) and mean daily
arthropod biomass trapped during the interval between successive
captures. The lowest observed growth index was 3.2; this point
was shifted to 0.95 to fit into the frame. Regression equation: y =
0.311 (SE=0.194)+0.306ln(x) (SE=0.036); further statistics in text
curve. The slower growth of DLW-injected chicks is
explained by measurements being made on days with
relatively low food availability: the average growth index
predicted from arthropod abundance on trial days was
0.81. Three chicks lost 3.0–4.1 g/day during DLW trials
(average growth index =0.63, SE=0.13); this was more
than predicted from arthropod availability (0.06).
The power function describing daily energy expenditure (DEE, kJ/day) in relation to body mass (M, g) was:
log(DEE)=0.492+1.078 log(M) (SEB0=0.163, SEB1=0.091,
likelihood ratio test, C21=34,9, P<0.001; Fig. 5). Including average Te (C) during the DLW trial improved this
model:
DEE
decreased
with
increasing
Te
(log(DEE) = 0.442+1.129 log(M) 0.023 Te; SEB0=0.145,
SEB1=0.083, SEB2=0.010, C21=4.16, P=0.041). Wind
speed (P=0.75), rainfall (P=0.31), arthropod availability
(P=0.92) and growth rate over the measurement interval
(P=0.12) had no significant effect on DEE in addition to
that of body mass.
Daily metabolised energy (ME, kJ/day; DEE plus energy
deposited into tissues (Etis) if the chick gained mass) was
related to body mass as log(ME)=0.837+ 0.916 log(M)
(SEB0=0.130, SEB1=0.073, C21=36.7, P<0.001; Fig. 5). In
contrast to DEE, there was no significant effect of
337
Table 2 Logistic regression parameters for proportion of time
being brooded (B) in chicks of three shorebird species studied in
temperate grasslands (The Netherlands). All observations were
made in daylight as chicks were inactive at night (c. 2200–
0600 hours). Rainfall was set to 1 if rain fell during ‡10% of the
Variable
Constant
Mass
Te
Rain
Residual deviance
Total deviance
Total df
Black-tailed godwit
time (too few wet observations were made to include this variable
for red knots). Coefficients are given for logit(B)=ln(B/(1B)). All
coefficients were significant at P<0.05, except that for rain in
common redshank (X21=3.5, P=0.06)
Northern lapwing
Common redshank
Coefficient
(SE)
Coefficient
(SE)
Coefficient
(SE)
5.512
0.094
0.199
0.661
181.4
561.4
991
(0.548)
(0.011)
(0.022)
(0.252)
4.373
0.0556
0.202
1.122
145.1
375.5
643
(0.430)
(0.0071)
(0.021)
(0.275)
8.02
0.160
0.401
2.41
3.5
24.1
43
(3.70)
(0.093)
(0.197)
(1.34)
Fig. 5 Daily energy expenditure (DEE, kJ/day) and metabolised
energy (ME, kJ/day) of red knot chicks in relation to body mass (M,
g). Allometric regression equations: DEE=3.105 M1.078;
ME=6.871 M0.916 (further statistics in text). For comparison, an
allometric relationship between ME and M in birds and mammals
under energy-demanding conditions (Kirkwood 1983; MEmax) is
also shown
Fig. 4 Comparison of proportional brooding time in relation to
body mass at the same temperature (A) and to operative temperature at the same age (B) for chicks of red knot (Kn), common
redshank (Re), black-tailed godwit (Go), and northern lapwing (La).
Lines show predictions from logistic regression models (Tables 1,
2) during dry weather in daytime
to 494 kJ/day at fledging (108 g). Total ME over this
period amounted to 5,285 kJ, of which 14% was made up
by E tis and the remaining 86% by DEE, including basal
metabolism and costs of thermoregulation, activity, and
biochemical synthesis.
Discussion
temperature on ME in addition to that of mass (C21=0.01,
P=0.92); apparently the increase in DEE at low Te was
compensated by reduced growth (lower Etis). Wind speed
(P=0.14), rainfall (P=0.69), arthropod activity (P=0.75)
or growth rate (P=0.76) did not affect ME either.
Total energy requirements of a red knot chick fledging
at Cape Sterlegov were estimated by summing daily
estimates of ME over the 18-day fledging period. At each
age, mass predicted from the average growth curve and
mean Te over the period of chicks’ presence (2.8C) were
inserted into the regression equation relating DEE to mass
and Te. Predicted mass and growth rate were also used to
estimate E tis, which was added to DEE to obtain ME. ME
increased at a decelerating rate from 65 kJ/day at hatching
High energy requirements in arctic-breeding shorebirds
ME of red knot chicks exceeded an allometric prediction
of ‘maximum’ ME based on various birds and mammals
under energy-demanding conditions (Kirkwood 1983), in
14 out of 15 cases (Fig. 5). Weathers (1992) reviewed
prefledging energy requirements in 30 bird species, and
derived a predictive equation for total metabolised energy
(TME) over the prefledging period. The largest (absolute)
difference between observed and predicted values in
Weathers’s (1992) sample was 40%, while our value for
knots is 89% above the prediction.
Two factors likely to contribute to these high energy
requirements are the red knots’ precocial lifestyle and the
338
cold climate. The studies reviewed by Weathers (1992)
included mostly temperate-breeding birds with parent-fed
young. Self-feeding chicks exhibit high muscular activity,
which should increase energy expenditure compared to
parent-fed nestlings in any climate. In temperate-breeding
black-tailed godwits and northern lapwings, TME was
28% and 45% higher than Weathers’ (1992) prediction
(Schekkerman and Visser 2001). That mass-corrected
DEE was yet c. 80% higher in knots is most probably
accounted for by the much lower temperature in the
Arctic. The largest differences between observed and
expected TME found by Weathers (1992) occurred in the
arctic-breeding dunlin (+40%, Norton 1970) and arctic
tern Sterna paradisaea (+35%, Klaassen et al. 1989).
Subsequent measurements on American golden plover
Pluvialis dominica (+52%, Visser et al., unpublished
data), black-legged kittiwake Rissa tridactyla (+35%,
Gabrielsen et al. 1992), little auk Alle alle (+35%,
Konarzewski et al. 1993) and Wilson’s storm-petrel
(+148%, Obst and Nagy 1993), also revealed high TME
in polar environments.
Fast growth in the Arctic, why and how?
In addition to elevating energy requirements, low temperatures increase a shorebird chick’s need for parental
brooding, thereby reducing time available for foraging
(Chappell 1980; Beintema and Visser 1989a; Visser and
Ricklefs 1993). In response, arctic-breeding shorebirds
might have evolved a lower growth rate which reduces the
chicks’ daily energy requirements (Lack 1968; Ricklefs
1984; Klaassen et al. 1992), but in fact they show the
opposite: arctic-breeding shorebirds tend to have higher
growth rates than temperate species (Beintema and Visser
1989a; Schekkerman et al. 1998a; this study). An ultimate
explanation for this is that the length of the season suitable
for growth is short in the Arctic, constrained at the start by
snow melt and at the end by declining temperature or food
availability (e.g. Holmes 1966a, 1966b, 1972; Carey 1986;
see below). In addition, fast growth itself may help chicks
to overcome the energetic difficulties, because size is an
important thermal characteristic of animals (Visser 1998).
At the proximate level, the fast growth shows that there
must be factors compensating for the thermal difficulties
faced by arctic chicks. Below, we explore the applicability
to the red knot’s case of three (not mutually exclusive)
mechanisms that have been proposed.
Day length
The continuous arctic summer daylight does not impose
an inactive period on visual foragers, and this would
allow chicks to increase their daily energy intake and
hence growth rate compared to lower latitudes (Karplus
1952; Lack 1954; Kvist and Lindstrm 2000). Red knots,
however, did not take full advantage of this: chicks were
brooded more between 2200 hours and 0400 hours than
during other times, irrespective of temperature. Although
the sun never set until early August, light levels were
noticeably lower ’at night’, and activity and harvestability
of arthropods may have been reduced. Alternatively,
young knots may need more sleep than can be accommodated into daytime brooding bouts, and may have
taken extra resting time ’at night’. Adult birds of 12
species observed in arctic summer conditions slept 3.7 h
per day on average (Amlaner and Ball 1983). Compared
to a 8-h dark period in spring in The Netherlands, this
would still allow for a 27% increase in feeding time.
Growing animals like young knots may need more sleep,
but how much is unclear.
Cold-hardiness
Arctic chicks may have evolved structural or metabolic
adaptations that reduce the need for parental brooding and
thus increase foraging time (Chappell 1980). Indeed, red
knots were brooded less than chicks of three temperate
shorebird species at the same mass and temperature, and
they became thermally independent earlier. This agrees
with the finding that hatchlings of ducks with a northern
breeding distribution are cold-hardier than those of more
southern species (Koskimies and Lahti 1964). Increased
cold-hardiness may be achieved in three ways: (1) arctic
chicks may be better isolated, e.g. have thicker down; (2)
they may tolerate lower body temperatures than temperate
chicks (Norton 1973; West and Norton 1975; Chappell
1980); and (3) they may be able to elevate metabolic rate
higher above basal level under cold stress. The latter two
mechanisms might be facilitated by a reduced risk of
infection and disease in arctic compared to temperate
environments, allowing arctic chicks to compromise
immunodefence for increased metabolic performance
(Piersma 1997).
We cannot distinguish between these mechanisms on
the basis of our data. The few literature data on
operational body temperatures in shorebirds do not
support hypothesis 2. Chicks of three arctic Calidris
sandpipers gave distress calls and became sluggish at a
core temperature of c. 30C (Norton 1973), while chicks
of the temperate common redshank voluntarily tolerated
27C, and common snipe Gallinago gallinago cooled
down to 2426C without signs of distress (Myhre and
Steen 1979). Subtropical crowned plover Vanellus coronatus chicks also voluntarily operated at body temperatures down to 30C (Brown and Downs 2002). Evidence
for mechanisms 1 and 3 was found in young eiders
Somateria mollissima (Koskimies and Lahti 1964; Steen
et al. 1989). Mechanism 3 would contribute to the chicks’
high energy expenditure, so that the gain in feeding time
will be partly offset by a concomitant increase in energy
requirements.
Food availability
Alternative to increased foraging time, energy intake rate
during foraging might be higher in the summer tundra
than in temperate environments (Lack 1968; MacLean
and Pitelka 1971; Salomonsen 1972; Andreev 1999). Our
pitfall samples revealed a lower rather than a higher mean
daily biomass of surface-active arthropods at Cape
339
Fig. 6 Simulated potential foraging time (FT) in relation to age
(bottom panel) of red knot and common redshank chicks, and of
imaginary chicks with mixed species/environment characters (see
Appendix for model details). Starting with a redshank in a
temperate environment (1), Te was changed from 15C to 3C
(2), then day length from 16 to 24 h/day (3), and then growth rate
(4) and finally cold-hardiness (5) to a red knot’s. Horizontal broken
line indicates maximum potential foraging time under the assumption of 6 h needed for sleep. Upper panel shows the resulting total
foraging time over 18 days (area under curves), indexed to 100 for
a temperate redshank (black: with 6 h/day sleep; grey: extra if no
sleep required). Kn red knot, Re common redshank, Re* redshank
with knot growth rate
Sterlegov than in a temperate meadow. Because arthropod
abundance and activity may vary between years as well as
between sites, this finding cannot be generalised, but red
knots at Cape Sterlegov did not experience a higher
abundance of food than Dutch shorebird chicks in 1994.
However, they might still have achieved a higher intake
rate, if prey were more easily detected or captured. This
could be a result of the simpler structure of the tundra
vegetation, compared to a temperate grassland sward, or
of a larger proportion of slow-moving or wingless
arthropods at high latitudes (cf. Chernov 1985).
Comparative simulation model
To explore the relative importance of the explanations
discussed above, we constructed a comparative model in
which the (metabolisable) energy intake rate during
foraging, required to meet the daily demands for maintenance and growth, was simulated on the basis of our
measurements of ME and foraging time, for red knots at
Cape Sterlegov and for common redshank in The Netherlands. Redshank are similar in adult mass (109 g) to knot
(120 g), but grow more slowly. If the simulated intake rate
of knots exceeds that of redshank, better feeding conditions must be invoked to explain the fast growth of arctic
knot chicks; if not the higher metabolism can be met
solely by an increase in foraging time. By changing values
for temperature, daylength, growth rate and cold-hardiness, we also explored which factors are most important in
Fig. 7 Simulated required (metabolisable) intake rate in relation to
age for red knot and common redshank chicks, and of imaginary
chicks with mixed species/environment characters. Lines ad: red
knots need a higher intake rate than redshank, but the difference is
strongly dependent on time needed for sleep. Lines ef: without a
knot’s greater cold-hardiness, young (£5 days) chicks would need
extremely high intake rates. Kn Red knot, Re common redshank,
Re* redshank with knot growth rate, with allowance for coupling of
growth rate and RMR (see Appendix)
maximising feeding time in the Arctic. We considered that
without a dark period of forced inactivity, sleep requirements may reduce foraging time unless they can be fitted
within brooding bouts. Equations and assumptions of the
model are detailed in the Appendix.
The model predicts potential foraging time (FT),
energy requirements (ME) and required intake rate (RI)
for each day during an 18-day prefledging period. Total
FT over this period for a common redshank in The
Netherlands was indexed at 100%. Allowing for 6 h of
sleep, predicted total FT for red knots in Taimyr is very
similar (102%; without sleep 128%; Fig. 6). Despite their
greater cold-hardiness 0- to 4-day-old knots have less
foraging time than redshank due to the low temperature;
later this is reversed but the knots’ advantage depends
strongly on their need for sleep.
If a redshank chick were to live at 3C under a
temperate daylength of 16 h, its total FT over 18 days
would be reduced to 46% of that at 15C (Fig. 6). With
continuous daylight and 6 h/day of sleep at 3C (i.e. after
an imaginary translocation to the arctic), the redshank’s
FT would be 61% of that in The Netherlands. Assigning a
knot’s growth rate to this chick increases FT (to 82%),
because it is larger than a redshank at each age and thus
requires less brooding. Finally, the larger cold-hardiness
of a knot increases FT to 102%. The effects of growth rate
and cold-hardiness partly substitute each other: when a
redshank chick at 3C and an 18-h day is given knot coldhardiness, FT increases from 61% to 95%, and increasing
growth rate only adds a further 7%.
340
Total ME over 18 days is 160% higher in red knots
than in common redshank, causing a large difference in
required foraging intake rate (RI, Fig. 7). Because ME
strongly depends on body mass, much of this difference is
caused by the knots’ higher growth rate. Assuming knot
growth rate for redshank, and allowing for a coupling
between growth rate and RMR elevating ME by a further
9% (see Appendix), the difference in TME reduces to
46%. This would bring RI of redshank very close to that
of knots if these need no time for sleep (Fig. 7), but it is
more likely that knots need a higher intake rate.
We conclude from this simulation that red knot chicks
can grow up successfully in the arctic because of a
combination of factors. Cold-hardiness and growth rate
are important factors compensating for feeding time lost
due to low temperatures. Continuous daylight also
contributes, but how much depends strongly on the
unknown time needed for sleep. The resulting total
feeding time differs little between red knots and common
redshanks in their natural environment. However, because
knots expend more energy, a higher foraging intake rate
must still be invoked to fully explain their fast growth.
Since we trapped fewer rather than more surface-active
invertebrates in our arctic study area than in a temperate
grassland, this seems more likely due to a greater
harvestability (easier detection or capture) of invertebrates in the tundra than to a difference in abundance.
Fast growth and increased cold-hardiness, if achieved
by a higher peak metabolism, contribute to the high energy
requirements of red knots. Although these traits therefore
have costs as well as benefits, the cold-hardiness of knots
seems essential for survival during early life, when feeding
time is constrained by the need for parental brooding. If
translocated to the Arctic, redshank chicks up to 5–6 days
old would need an excessively high intake rate, unlikely to
be achieved in the field (Fig. 7). Assigning knot growth
rate to such a chick shortens this critical period by a few
days, but does not eliminate it. Lipid stores of neonate
shorebird chicks allow for no more than c. 1 day of
survival at peak metabolic rate (Visser and Ricklefs 1995).
Only introducing the greater cold-hardiness of young red
knots reduces RI to feasible levels throughout.
Effects of weather, food availability and breeding
phenology on growth rate
Despite their high overall growth rate, red knot chicks did
at times run into energetic problems, indicated by the
strong relationship between growth rate and weather.
Three non-exclusive mechanisms may underlie this. (1)
At low temperatures young chicks were brooded more,
and thus had less time available for foraging. However,
weather also affected growth rate of older, thermally
independent chicks. (2) DEE but not ME increased with
falling temperature, indicating that on cold days energy is
allocated to thermoregulation at the expense of tissue
formation. (3) Low temperature and precipitation strongly
reduced the activity of surface-dwelling invertebrates.
Though we did not measure intake rate directly, it is
likely that this represents a reduction in prey availability
for chicks: on cold days invertebrates were hardly visible
on the tundra surface (cf. Holmes 1966a). Our finding that
trapped arthropod biomass predicted chick growth rate
better than weather variables suggests that food availability was the most important factor, and was adequately
described by the pitfall samples.
The strong relationship between chick growth rate and
arthropod availability points to the importance of timing
reproduction so that the chicks can make full use of the
summer peak in insect abundance (e.g. Hurd and Pitelka
1954; Holmes 1966a, 1966b; Nettleship 1974). The
median hatching date of red knots in our study fell 6
days after the observed peak date of arthropod availability, though only 1 day after the predicted seasonal
maximum corrected for temperature effects. However, the
simulation model showed that required intake rate is
higher for chicks older than 10 days than for newly
hatched young (Fig. 7), hence peaked at a time when food
availability was already declining. The seasonal curve for
arthropod availability dropped below 5 mg.day1.trap1, a
level below which growth rate declined seriously, on 28
July (Fig. 1), a week before chicks born on the median
hatching date fledged. Near the median fledging date, the
predicted growth rate index dropped below 50%. Unless
older chicks exploit additional food sources unavailable to
young ones (but we did not see them, for example, probe
for buried larvae), red knots might therefore increase their
offspring’s growth rate and survival by laying earlier. In
1994, however, they could hardly have done so, because
only 10% and 50% of the tundra had become snow-free
on the earliest and median laying dates respectively.
Clutches can only be initiated after suitable nest sites have
become exposed, and shorebird nests in small snow-free
patches incur high predation risk (Byrkjedal 1980).
Similar constraints on fitting laying date to the seasonal
peak in food availability for the young were reported for
arctic-breeding geese (Sedinger and Raveling 1986;
Lepage et al. 1998; Madsen et al. 1998). Such a mismatch
will contribute to selection for a strategy of maximising
growth rate at the expense of high energy requirements.
While this strategy may be common in arctic birds
(Klaassen and Drent 1991; see Fortin et al. 2000 for
another precocial example), in the small and extremely
northerly breeding red knot the energetic consequences
show up particularly clearly.
Acknowledgements Petra de Goeij, Jan van de Kam and Joop
Jukema provided indispensable help during fieldwork, with further
assistance from Hans Dekkers and Valeri Bozun. Berthe Verstappen (CIO) skilfully performed the isotope analyses. The project was
financed by the Dutch Ministry of Agriculture, Nature Management
and Fisheries, Netherlands Institute for Sea Research (NIOZ),
Netherlands Organisation for Scientific Research (NWO), Stichting
Plancius, Lund University, and c. 80 individual private benefactors.
Logistic help was provided by the Institute of Evolutionary
Morphology and Animal Ecology, Russian Academy of Sciences,
staff of the Great Arctic Reserve, and by Gerard Boere, Bernard
Spaans, Bart Ebbinge and Gerard Mskens. The manuscript
benefited from comments by Bruno Ens, Rudi Drent, Arie Spaans,
and Eric Stienen. This is NIOZ-publication 3599.
341
Appendix
Simulation model
The simulation model predicts body mass, foraging time, energy
requirements and required metabolisable energy intake of red knot
and common redshank chicks during an 18-day fledging period, on
the basis of growth, time budget and metabolism data reported in
this paper or from the literature. We distinguished two environments differing in daylength (D, h/day) and operative temperature
(Te, C): arctic (D=24 h/day, Te=3C, data from Cape Sterlegov)
and temperate (D=16 h/day, Te=15C, data from The Netherlands,
May–June 1992–1995).
At each age t, body mass (M, g) of chicks was predicted from a
logistic growth curve:
– knot:
M¼ 120=½1 þ 8:23e0:240t
ðthis studyÞ
ð1Þ
– redshank:
M¼ 109=½1 þ 6:17e0:137t
ðfrom Beintema and Visser 1989bÞ
(2)
The proportion of daylight time that chicks were brooded by a
parent (B) was calculated by inserting mass and Te into logistic
regression equations derived from our time budget observations
(Tables 1, 2). As too few observations with rain were made for
knots to estimate its effect on brooding time, we used the equations
for dry weather in both species:
– knot:
logitðBÞ ¼ 5:22 0:160Mþ0:027Te
ð3Þ
– redshank:
logitðBÞ ¼ 8:02 0:160Mþ0:401Te
ð4Þ
Potential foraging time (FT, h/day) was calculated as day length
minus brooding time. Redshank chicks do not forage during
darkness (personal observation). We made calculations including
and excluding the condition that chicks need 6 h of sleep each day,
to show the effect of this requirement. We assumed that temperate
chicks fit this into the 8-h night, while arctic chicks sleep whenever
brooded and reduce foraging time only if daily brooding time is less
than time required for sleep (i.e., if B<0.25):
– arctic:
FT ¼ 24 ð24BÞ ifB 0:25; F¼DS ifB< 0:25
ð5Þ
– temperate:
FT ¼ 16 ð16BÞ
ð6Þ
In a balanced budget, total metabolisable energy intake over the
hours spent foraging equals energy metabolised over the entire 24-h
period (ME, kJ/day). Hence, required metabolisable energy intake
rate while foraging (RI, J/s) at each age was calculated as:
RI ¼ ME=ð3:6FTÞ
ð7Þ
ME is the sum of daily energy expenditure as measured with DLW
(DEE, kJ/day) and energy incorporated into tissue (Etis, kJ/day):
ME ¼ DEEþEtis if Etis > 0; ME ¼ DEE if Etis 0
ð8Þ
E tis was calculated as the daily increment of the product of body
mass and energy density, the latter estimated from the fraction of
adult mass attained (see Materials and methods):
– knot:
Etis ¼Mtþ1 ½4:38 þ 3:21Mtþ1 =120Mt ½4:38 þ 3:21Mt =120
ð9Þ
– redshank:
Etis ¼Mtþ1 ½4:38 þ 3:21 Mtþ1 =109Mt ½4:38 þ 3:21Mt =109
ð10Þ
For DEE of knot chicks, we used the equation derived in Results,
inserting Te=3C. Because DEE was not measured in common
redshank, we used the mass-DEE relationship for black-tailed
godwit chicks (Schekkerman and Visser 2001). This relation did
not differ significantly from that for northern lapwings, despite
considerable differences in age at the same mass, hence we
assumed that it applies to redshank as well. The equation is based
on DLW measurements made at a mean Te of 15C.
– knot:
DEE ¼ 2:630M 1:129
ð11Þ
– redshank:
DEE ¼ 1:549M 1:092
ð12Þ
No predictions of ME and RI were made at ages 02 days, because
regression equations overestimate energy requirements during this
period (there is a rapid increase in metabolism over the first 3 days,
Visser and Ricklefs 1993), and because the contribution of energy
stores present in the hatchling (yolk) was not taken into account.
The effect of environmental and physiological variables on FT
and RI was explored by exchanging environment and species
parameters. For instance, a redshank chick was virtually transposed
into the Arctic by changing daylength from 16 to 24 h/day and Te
from 15C to 3C. Subsequently exchanging Eq. 4 for Eq. 3 shows
the effect on foraging time of a knot’s greater cold-hardiness than
that of a redshank.
When comparing ME and RI between the species, the difference
in growth rate must be taken into account, as ME depends strongly
on body mass. We did so by inserting the red knot growth equation,
(Eq. 1) into the model for common redshank. Klaassen and Drent
(1991) proposed that Resting Metabolic Rate in hatchling birds is
coupled to growth rate, which implies that redshank could only
grow at a knot’s rate at the expense of an increase in RMR. A rough
estimate of this additional effect would be a 9% increase of ME
(based on Fig. 4 in Klaassen and Drent 1991, a 75% higher growth
rate would lead to a 29% increase in RMR which is c. 33% of ME
in temperate shorebird chicks, Schekkerman and Visser 2001).
References
Amlaner CJ, Ball NJ (1983) A synthesis of sleep in wild birds.
Behaviour 87:85–119
Andreev AV (1999) Energetics and survival of birds in extreme
environments. Ostrich 70:13–22
Beintema AJ, Visser GH (1989a) The effect of weather on time
budgets and development of chicks of meadow birds. Ardea
77:181–192
Beintema AJ, Visser GH (1989b) Growth parameters of charadriiform chicks. Ardea 77:169–180
Boertmann D, Meltofte H, Forchhammer M (1991) Population
densities of birds in central northeast Greenland. Dan Ornithol
Foren Tidsskr 85:151–160
Brown M, Downs CT (2002) Development of homeothermy in
hatchling crowned plovers Vanellus coronatus. J Therm Biol
27:95–101
Byrk AS, Raudenbush SW (1992) Hierarchical linear models,
application and data analysis. Sage, London.
Byrkjedal, I (1980) Nest predation in relation to snow cover a
possible factor influencing the start of breeding in shorebirds.
Ornis Scand 11:249–252
Carey C (1986) Avian reproduction in cold climates. Proc Int
Ornithol Congr 19:2708–2715
Chappell MA (1980) Thermal energetics of chicks of arcticbreeding shorebirds. Comp Biochem Physiol 65A:311–317
Chernov YI (1985) The living tundra. Cambridge University Press,
Cambridge
Fortin D, Gauthier G, Larochelle J (2000) Body temperature and
resting behaviour of Greater Snow Goose goslings in the High
Arctic. Condor 102:163–171
Gabrielsen GW, Klaassen M, Mehlum F (1992) Energetics of
Black-legged Kittwake chicks. Ardea 80:29–40
Gessaman, Nagy KA (1988) Energy metabolism: errors in gas
excange conversion factors. Physiol Zool 61:507–513
342
Holmes RT (1966a) Feeding ecology of the Red-backed Sandpiper
(Calidris alpina) in Arctic Alaska. Ecology 47:32–45
Holmes RT (1966b) Breeding ecology and annual cycle adaptations
of the red-backed sandpiper (Calidris alpina) in Northern
Alaska. Condor 68:3–46
Holmes RT (1972) Ecological factors influencing the breeding
season schedule of Western Sandpipers (Calidris mauri) in
subarctic Alaska. Am Midl Nat 87:472–491
Hurd PD, Pitelka FA (1954) The role of insects in the economy of
certain Arctic Alaskan birds. Proc 3rd Alaskan Sci Conf:136–
137
Institute of Education (1995) MLN. Institute of Education, London
Karplus, M (1952) Bird activity in the continuous daylight of arctic
summer. Ecology 33:129–134
Kirkwood JK (1983) A limit to metabolisable energy intake in
mammals and birds. Comp Biochem Physiol 75A:1–3
Klaassen M, Drent RH (1991) An analysis of hatchling resting
metabolism: in search of ecological correlates that explain
deviations from allometric relations. Condor 93:612–629
Klaassen M, Bech C, Masman D, Slagsvold G (1989) Growth and
energetics of Arctic Tern chicks (Sterna paradisaea). Auk
106:240–248
Klaassen M, Zwaan B, Heslenfeld P, Lucas P, Luijckx B (1992)
Growth rate associated changes in the energy requirements of
tern chicks. Ardea 80:19–28
Konarzewski M, Taylor JRE, Gabrielsen GW (1993) Chick energy
requirements and adult energy expenditures of Dovekies (Alle
alle). Auk 110:343–353
Koskimies,J, Lahti L (1964) Cold-hardiness of the newly hatched
young in relation to ecology and distribution of ten species of
European ducks. Physiol Zool 65:803–814
Kvist A, Lindstrm (2000) Maximum daily energy intake: it
takes time to lift the metabolic ceiling. Physiol Biochem Zool
73:30–36
Lack D (1954) The natural regulation of animal numbers. Oxford
University Press, London
Lack D (1968) Ecological adaptations for breeding in birds.
Methuen, London
Lepage D, Gauthier G, Reed A. (1998) Seasonal variation in growth
of Greater Snow goose goslings: the role of food supply.
Oecologia 114:226–235
Lifson N, McClintock R (1966) Theory of use of the turnover rates
of body water for measuring energy and material balance. J
Theor Biol 12:46–74
MacLean SF, Pitelka FA (1971) Seasonal patterns of abundance of
tundra arthropods near Barrow. Arctic 24:19–40
Madsen J, Bregneballe T, Frikke J, Kristensen J-B (1998)
Correlates of predator abundance with snow and ice conditions
and their role in determining timing of nesting and breeding
success in Svalbard Light-bellied Brent Geese Branta bernicla
hrota. Nor Polarinst Skr 200:221–234
Myhre K, Steen JB (1979) Body temperature and aspects of
behavioural temperature regulation in some neonate subarctic
and arctic birds. Ornis Scand 10:1–9
Nettleship DN (1974) The breeding of the knot Calidris canutus at
Hazen Camp, Ellesmere Island, N.W.T. Polarforschung 44:8–
26
Norton DW (1970) Thermal regimes of nests and bioenergetics of
chick growth in the Dunlin (Calidris alpina) at Barrow, Alaska.
MSc thesis, University of Alaska, Fairbanks
Norton DW (1973) Ecological energetics of calidridine sandpipers
breeding in northern Alaska. PhD, thesis, University of Alaska,
Fairbanks
Obst BS, Nagy KA (1993) Stomach oil and the energy budget of
Wilson’s Storm-petrel nestlings. Condor 95:792–805
Piersma T (1997) Do global patterns of habitat use and migration
strategies co-evolve with relative investments in immunocompetence due to spatial variation in parasite pressure? Oikos
80:623–631
Piersma T, Davidson NC (eds) (1992) The migration of knots.
Wader Study Group Bull 64 [Suppl]:1–209
Piersma T, van Gils J, Wiersma P (1996) Family Scolopacidae
(sandpipers, snipes and phalaropes). In: del Hoyo J, Elliot A,
Sargatal J (eds). Handbook of the birds of the world, vol 3.
Lynx, Barcelona, pp 444–553
Ricklefs RE (1983) Avian postnatal development. In Farner DS,
King JR, Parkes KC (eds). Avian biology, vol VII. Academic
Press, New York, pp 1–83
Ricklefs RE (1984) The optimization of growth rate in altricial
birds. Ecology 65:1602–1616
Rogers LE, Buschbom LR, Watson CR (1977) Length-weight
relationships for shrubsteppe invertebrates. Ann Entomol Soc
Am 70:51–53
Salomonsen F (1972) Zoogeographical and ecological problems in
arctic birds. Proc Int Ornithol Congr 15:25–77
Schekkerman H (1997) Grassland managements and growth
opportunities for meadowbird chicks (in Dutch). IBN-report
292, Institute of Forestry and Nature Research, Wageningen
Schekkerman H, Visser GH (2001) Prefledging energy requirements in shorebirds: energetic implications of self-feeding
precocial development. Auk 118:944–957
Schekkerman H, Nehls G, Htker H, Tomkovich PS, Kania W,
Chylarecki P, Soloviev M, van Roomen M (1998a). Growth of
Little Stint Calidris minuta chicks on the Taimyr Peninsula,
Siberia. Bird Study 45:77–84
Schekkerman H, van Roomen M, Underhill LG (1998b) Growth,
behaviour of broods and weather-related variation in breeding
productivity of Curlew Sandpipers Calidris ferruginea. Ardea
86:153–186
Schoener TW, Schoener A (1978) Estimating and interpreting body
mass growth in Anolis lizards. Copeia 1978:390–405
Sedinger JS, Raveling DG (1986) Timing of nesting in Canada
Geese in relation to the phenology and availability of their food
plants. J Anim Ecol 55:1083–1102
Speakman JR (1997) Doubly labelled water. Theory and practice.
Chapman and Hall, London.
Steen JB, Grav H, Borch-Iohnsen B, Gabrielsen GW (1989)
Strategies of homeothermy in Eider ducklings (Somateria
mollissima). In: Bech C, Reinertsen W (eds) Physiology of cold
adaptation in birds. NATO ASI Ser A, vol 173. Plenum Press,
New York, pp 361–370
Tomkovich PS, Soloviev MY (1996) Distribution, migration and
biometrics of knots Calidris canutus canutus on Taimyr,
Siberia. Ardea 84:85–98
Troy D (1996) Population dynamics of breeding shorebirds in
Arctic Alaska. Int Wader Stud 8:15–27
Tulp I, Schekkerman H, Piersma T, Jukema J, de Goeij P, van de
Kam J (1998) Breeding waders at Cape Sterlegova, northern
Taimyr, in 1994. WIWO-report 61. Working Group International Wetland and Waterbird Research, Zeist, The Netherlands
Visser GH (1998) Development of temperature regulation. In
Starck JM, Ricklefs RE (eds). Avian growth and development.
Oxford University Press, New York, pp 117–156
Visser GH, Ricklefs RE (1993) Development of temperature
regulation in shorebirds. Physiol Zool 66:771–792
Visser GH, Ricklefs RE (1995) Relationship between body
composition and homeothermy in neonates of precocial and
semiprecocial birds. Auk 112:192–200
Visser GH, Schekkerman H (1999) Validation of the doubly
labelled water method in precocial birds: the importance of
assumptions concerning evaporative water loss. Physiol
Biochem Zool 72:740–749
Walsberg GE, Weathers WW (1986) A simple technique for
estimating operative environmental temperature. J Therm Biol
11:67–72
Warnock N, Warnock SE (1993) Attachment of radio-transmitters
to sandpipers: review and methods. Wader Study Group Bull
70:28–30
Weathers WW (1992) Scaling nestling energy requirements. Ibis
134:142–153
West GC, Norton DW (1975). Metabolic adaptations of tundra
birds. In: Vernberg FJ (ed) Physiological adaptation to the
environment. Intext, New York pp 301–329
Wymenga E, Engelmoer E, Smit E, van Spanje TM (1992)
Geographical origin and migration of waders wintering in West
Africa. In: Altenburg W, Wymenga E, Zwarts L (eds.)
Ornithological importance of the coastal wetlands of GuineaBissau. WIWO-report 26. Working Group International Wetland and Waterbird Research, Zeist, The Netherlands, pp 23–52