J. Avian Biol. 38: 552
563, 2007 doi: 10.1111/j.2007.0908-8857.04014.x # 2007 The Authors. J. Compilation # 2007 J. Avian Biol. Received 30 June 2006, accepted 20 November 2006 Growth and energetics of a small shorebird species in a cold environment: the little stint Calidris minuta on the Taimyr Peninsula, Siberia Kathleen M. C. Tjørve, Hans Schekkerman, Ingrid Tulp, Leslie G. Underhill, Joep J. de Leeuw and G. Henk Visser K. M. C. Tjørve (correspondence), Avian Demography Unit, Department of Statistical Sciences, University of Cape Town, Rondebosch, 7701, South Africa. Present address: Lista Bird Observatory, Research Group, Fyrveien 6, N-4563 Borhaug, Norway. Email: kmctjorve@yahoo.co.uk.  H. Schekkerman, Alterra, P.O. Box 47, 6700 AA Wageningen, The Netherlands; Present address: Dutch Centre for Avian Migration and Demography, Netherlands Institute of Ecology, P.O. Box 40, 6666 ZG Wageningen, The Netherlands.
I. Tulp and J. J. de Leeuw, Alterra, P.O. Box 47, 6700 AA Wageningen, The Netherlands. Present address: Institute for Marine Resources and Ecosystem Studies (IMARES), P.O. Box 68, 1970 AB IJmuiden, The Netherlands.  L. G. Underhill, Avian Demography Unit, Department of Statistical Sciences, University of Cape Town, Rondebosch, 7701, South Africa.  G. H. Visser, Centre for Isotope Research, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands; and Zoological Laboratory, University of Groningen, P.O. Box 14, 9750 AA Haren, The Netherlands. The little stint Calidris minuta is one of the smallest shorebird species breeding in the Arctic (weighing 4.3 g on hatching). Their chicks are small and have a high surface area-to-volume ratio. We determined prefledging growth, energy expenditure and time budgets for little stint chicks in northwestern Taimyr, Siberia. A modified power curve was introduced to model the relationship between daily energy expenditure and body mass. Total metabolisable energy, TME, over the 15-d prefledging period was 107% greater than the allometric prediction for a bird the size of a little stint. Their growth rate coefficient was 14% greater than the prediction for a bird their size. The growth of young chicks was reduced in cool weather, possibly due to a reduction in foraging time in order to be brooded and reduced food availability which impact foraging efficiency. We did not detect weather effects on energy expenditure of chicks, but lack of temperature variation during energy expenditure measurements may have prevented this. In sum, both growth rate coefficient and energy expenditure of little stint chicks were greater than predicted and this is similar to that observed in other arctic shorebird species. Migrant shorebirds experience the low temperatures and high wind velocities of the high Arctic during the summer months, May to August (Chernov 1985). The little stint Calidris minuta is one of the smallest shorebirds that migrates from as far as southern Africa to the Arctic (ca 13,000 km) to breed, and their chicks are among the smallest self-feeding warm-blooded animals on the tundra, weighing 4.3 g upon hatching (Underhill et al. 1993, Schekkerman et al. 1998a). The highest breeding densities of little stints occur in the arctic tundra sub zone between 728N and 758N in Siberia (Rogacheva 1992). 552 Little stint chicks are self-feeding precocials (Schekkerman et al. 1998a), and in addition to energy needed for growth and development they also require energy for locomotion and thermoregulation while foraging (Starck and Ricklefs 1998). As a result of their small size, little stint chicks have a large surface area compared to their body volume and thus lose heat rapidly in the cold (Schekkerman et al. 2003). Unlike adult birds, young chicks are incapable of maintaining their body temperature by producing sufficient heat through shivering (Dawson 1975, Visser and Ricklefs 1993, Krijgsveld et al. 2001). In addition, although the down which covers young chicks provides a measure of insulation, it is far less effective than adult plumage (Visser and Ricklefs 1993). Therefore young chicks require brooding by their parents to insulate them from the cold and to enable their body temperatures to increase by a transfer of heat from the parent after a feeding period (Kendeigh 1969, Krijgsveld et al. 2001). Chicks of small shorebird species grow relatively more rapidly than larger species (Beintema and Visser 1989b, Krijgsveld et al. 2001), and Kendeigh (1969) and Krijgsveld et al. (2001) showed that small species are capable of increasing their metabolism to a relatively higher level than large species to maintain body temperature. The fast growth of chicks of smaller species may be a result of their investing energy in growth and mature function of tissue to its maximum capacity (Krijgsveld et al. 2001). Several studies of the energetics of free-living shorebird chicks have been completed in arctic and temperate zones (Schekkerman and Visser 2001, Joest 2003, Schekkerman et al. 2003) and these show that energy expenditure is greater in shorebirds growing at higher latitudes. We measured growth rate, daily energy expenditure (DEE) and time-activity budgets during the prefledging period of little stint chicks in the field. We compared growth and energy expenditure of little stints with predicted values for a species of its size and to values of other arctic and temperate-breeding shorebirds. We hypothesised that due to their small size and high surface area-to-volume ratio, little stint chicks have greater energy expenditure than predicted for their body size, and that environmental variation (e.g. weather) has a strong effect on their energy expenditure and time budgets and consequently impacts their growth. Methods Study area Measurements were performed on birds in the vicinity of the Willem Barentsz Biological Station at Medusa Bay, (738 04?N, 808 30?E), near Dikson on the northwestern Taimyr Peninsula, Siberia, Russia. All growth and energetics data were collected in June to August 2002 and time-budget data were collected in the summers of 2000 to 2002. The landscape of the 4 km2 main study area is classified as arctic tundra (Chernov 1985), with the highest of the rolling hills reaching 39 m above sea level. The vegetation of the study area is mostly well-vegetated tundra (mosses, lichens, grasses, herbs and dwarf willows Salix polaris ) with an area of large polygonal bogs to the east. Schekkerman et al. (2004) provide a more detailed description of the study area. Weather data Weather conditions for the study site, including ambient air temperature (Ta, 8C) ca 1 m above the ground and wind speed (ms 1) ca 10 m above the ground, were measured and logged every five minutes. Ambient air temperature at 1 m is strongly correlated with that at chicks’ body levels (2
10 cm; Tulp unpubl. data). Rainfall (mm) was recorded daily. Growth measurements Nests were located during laying or incubation. Hatch date was estimated using floatation tests (Schekkerman et al. 2004, Liebezeit et al. 2007), and nests were monitored intensively close to the predicted hatch date. Chicks were located through observation of adults caring for chicks. The family was observed from a short distance and the positions of chicks noted, whereafter the brood was approached quickly by one observer while another person was guided to the chicks through instructions from the observer. Chicks were ringed and weighed either in the nest cup or when broods were encountered on the tundra. Throughout the prefledging period, chicks were recaptured when encountered to record their growth. Mass (to the nearest 0.1 or 0.5 g) was measured using Pesola spring balances. Chicks were released at the site of their capture. Mean masses for hatchlings were determined in the nest and for prefledglings measured on their last capture at 14 to 15 d old. All chicks of known age with an accuracy of 24 h and for which at least two measurements were taken, were used to describe growth of body mass. Growth parameters were determined for the Gompertz (1825), M A exp(exp(K (tT))); and logistic, M A=(1exp(K (tT))); growth models and the fits of both growth curves were compared. In these growth models, the parameter M is body mass (g), A is the asymptotic body mass (g), K is the growth coefficient (d 1), t is the age of the chick (d) at the time of the observation, and T is age at the point of inflection (d). The better fitting curve was chosen to describe the data. Chicks fledge while still increasing in mass and it is not feasible to obtain a biologically meaningful estimate of the asymptote. The asymptote of body mass, A, was fixed at the mean adult body mass observed in the study area, 26.6 g (Tulp et al. 2002). The growth rate coefficient for the Gompertz curve (REFERENCE?), KG, or the logistic curve, KL, and the point of inflection were estimated for individual chicks through regression. The median values were taken as the growth rate coefficient and 553 point of inflection for the species. Parameter estimations were only obtained from chicks which were presumed to fledge successfully (data from chicks that were known not to fledge were removed from the analysis), to produce a curve for ‘‘normal successful’’ growth. Growth of chicks may be influenced both by temperature (affecting energy expenditure and the time available for foraging instead of being parentally brooded) and by food availability. As growth of shorebird chicks follows an S-shaped curve, therefore we compared the growth rate coefficients of chicks at different ages and over different intervals by means of a growth index (growth observed/growth predicted over the same time interval from the fitted growth curve for little stint chicks for the 2002 breeding season (cf. Schekkerman et al. 2003). Growth indices were determined for chicks which were captured at two to five day intervals. The growth indices were normally distributed (Kolmogorov-Smirnov test: KS 0.05, P
0.10). These growth indices were used to analyse the dependence of growth rate on mid-interval date (the date midway between the first and last measurement of the chick) and ambient temperature (Ta, 8C) during the recapture interval through linear regression. Since shorebird chicks often lose mass during the first day(s) after hatching and this is not reflected in the fitted standard growth curves (Schekkerman et al. 1998a, 1998b), growth indices for chicks first weighed when less than a day old (often still in the nest) tend to be lower than those for older chicks. Therefore, we analysed the growth of neonates up to 5 g and chicks greater than 5 g at the start of the recapture interval separately. Energetic expenditure measurements using DLW Daily energy expenditure (DEE, kJ d 1), defined as energy expenditure excluding that which is deposited into tissue, was measured using the doubly labelled water (DLW) technique (Lifson and McClintock 1966, Nagy 1980, Speakman 1997, Visser and Schekkerman 1999) on free-living chicks. Either single chicks or siblings in families with up to four chicks were captured, weighed to the nearest gram and then injected subcutaneously in the ventral region with 0.05 to 0.1 ml of DLW, depending on the mass of the chick. The DLW consisted of 36.7% D2O and 59.9% H218O. Both two-sample (Nagy 1983) and single-sample (Webster and Weathers 1989) DLW protocols were used. The little stint chicks subjected to the twosample protocol were kept warm in a well-ventilated cloth bag containing a hot water bottle after their injection for an equilibration period of approximately one hour after which four to six 10
15 ml initial blood samples were collected from the brachial vein, into glass 554 capillary tubes, which were flame-sealed with a propane torch within minutes. These chicks were then released to their parent which stayed nearby during processing. Chicks subjected to the single-sample protocol and were released directly after the DLW injection, and no initial blood samples were taken. Broods were relocated and chicks recaptured after approximately 24 h, and mass measurements and final blood samples were taken. Blood samples were collected from four chicks before injection with DLW to measure background isotope levels. The 2H/1H and 18O/16O ratios in the blood samples were analysed with a SIRA 9 isotope ratio mass spectrometer at the Centre for Isotope Research, University of Groningen, following procedures described by Visser and Schekkerman (1999) and Visser et al. (2000a). Due to difficulties injecting known quantities of DLW (especially in small chicks), the chick’s body water pool (N, moles) was estimated using the equation for shorebird chicks (modified from Schekkerman and Visser 2001) by inserting the appropriate body mass into the function: N 0:000556M(79:86(9:55(M=26:6))); where M represents the chick’s body mass (g) during the DLW measurement, taken as the average of the initial and final masses, and 26.6 is the asymptotic body mass (g). Daily rates of carbon dioxide production were determined using the methods described and validated for growing chicks by Visser and Schekkerman (1999), Visser et al. (2000b) and Schekkerman and Visser (2001). Rates of carbon dioxide production were converted to DEE using a factor of 27.3 kJ l1 of carbon dioxide produced, based on a diet rich in protein (Gessaman and Nagy 1988). Analyses were done in triplicate and averaged. Statistical analysis and a new model to establish the relationship between DEE and body mass The relationship between daily energy expenditure (DEE, kJ d 1) and body mass, M (g), in growing chicks is usually modelled using the standard power curve, DEE aMb ; where a represents a coefficient and b represents the allometric scaling exponent (e.g., Weathers and Siegel 1995, Schekkerman and Visser 2001, Visser and Schekkerman 1999). The standard power curve can be rewritten as a straight line in log-log space, log (DEE) A blog M; where A equals log a, with A (and therefore a) and b estimated by linear regression. This model assumes a single allometric scaling exponent throughout the development period. However, this model was not appropriate for the little stint data (see Results). In the past, a non-linear relationship in log-log space has been solved by applying two different power curve functions to specific phases of the postnatal period, the biphasic approach, e.g. Freeman (1967) described the resting metabolic rate of Japanese quail Coturnix coturnix japonica , using the biphasic approach and Dietz and Ricklefs (1997) used this type of analysis to determine the moment in development when metabolism changed dramatically. We modified the standard power curve by adding a third parameter so that the scaling exponent becomes (b
(c/M)) and varies with body mass, DEE aM(b(c=M)) ; where a, b and c are coefficients to be estimated. This model is more parsimonious than the biphasic approach, with three parameters in place of five, and it overcomes the mathematical artefact of the break-point between the two curves. The three parameters can be estimated by standard multiple linear regression software, because it can be written in the form: 1 log (DEE) A blog McM log M where A is log a and M is body mass (g). The parameters of this model cannot be directly compared to those of the standard power curve. To keep the results in this paper comparable to those of previous studies, analyses were completed using both the modified power curve and the standard power curve. The programme GraphPad Prism (Motulsky and Christopoulos 2004) was used for both regressions. Because the standard power curve and the modified power curve are nested models, we used the F-test to determine which better fits the DEE data for little stints (Motulsky and Christopoulos 2004). The DEE data were tested for outliers using Grubb’s test (Motulsky and Christopoulos 2004), and the pattern of the residuals of the regressions were tested using the Wald-Wolfowitz runs test (Motulsky and Christopoulos 2004). We note that the DEE data contain repeated measures for chicks and that there may be brood effects in both the DEE and the growth data. There were no clustered deviations from the fitted curve, so we used the above method to give initial insights into the data. The investigation of the effects of repeated measures and brood effects may require a larger data set and thus warrants investigation. The impact of weather on DEE was determined through forward selection linear regression using the equation: log (DEE) A blog McM1 log Md Ta ewind speedf rainfall: The additional explanatory variables were tested both untransformed, as done by Schekkerman and Visser (2001) and Schekkerman et al. (2003), and after logarithmic transformation. Energy budget estimation Prefledging energy budgets were constructed on the basis of the average body mass growth curve for freeliving chicks. Metabolisable energy (ME) is the sum of two components: DEE and energy that is converted into tissue (Etis, kJ d 1). DEE measured through the DLW method constitutes resting metabolic rate (RMR, kJ d 1), energy used for assimilation of nutrients and tissue synthesis (Esyn, kJ d 1), and the energy costs of thermoregulation and activity (Etract, kJ d 1). RMR and Etract were not determined separately for little stint chicks, but a combined value was estimated. Etis was estimated as the daily increment of the product of body mass and energy density using the equation Etis (t)Mt (4:383:21(Mt =26:6)) Mt1 (4:383:21(Mt1 =26:6)) where Mt
1 and Mt are the masses (g) estimated by the logistic growth curve for days t
1 and t, and 26.6 is the asymptotic mass (g) for the species (Schekkerman and Visser 2001). The relationship between ME and body mass was modelled using the standard power curve and the modified power curve. The impact of weather on ME was determined through forward selection linear regression using the modified power curve, as for the DEE. Peak daily metabolisable energy (peak DME, kJ d 1) is the maximal daily energy demand of chicks across the prefledging period (Weathers 1992). Precocial birds often fledge before attaining adult mass (Fjeldså 1977, Starck and Ricklefs 1998), thus their energy requirements may continue to increase after fledging. Little stint chicks fledge at 73
92% of adult mass. Total metabolisable energy (TME, kJ) was estimated as the total amount of energy metabolized during the prefledging period. Assuming a synthesis efficiency (Esyn) of 75% (Ricklefs 1974), total energy for growth (kJ) was estimated as the combination of daily Etis and Esyn values across the prefledging period (i.e. 1.33 sum of daily Etis values). The energy used for RMR and Etract was estimated by subtracting the total energy for growth from TME. Growth efficiency (%) was estimated as the sum of the daily Etis values divided by TME. To study the impact of the type of curve used on the estimates for peak DME and TME, energy budgets were calculated based on both the standard power curve and the modified power curve. 555 25 Observations were made on six different broods in 2000, 2001 and 2002. Observation periods (n 40) were scattered throughout the 24 h of daylight and at all stages of chick development, from hatching to 17 d, and totalled 60.9 h in bouts of 38
130 minutes (average 91, SD 25 min). Chick behaviour was categorised as brooding, foraging, or other behaviours (including preening, walking and hiding at the adult’s alarm). The proportion of total observation time spent brooding was modelled in relation to age, temperature and whether it was ‘day’ (04:00 to 22:00 h local time (i.e. GMT3 h), the period in which light levels were generally largest in our study area) or ‘night’ (22:00 to 04:00 h) using multiple regression on the logit-transformed values. 20 Results Environmental conditions During the period that unfledged chicks were present, average ambient temperature, Ta, was 8.68C (SD 3.6, range 4.3
15.4). Rainfall during the period when unfledged chicks were present was greater than recorded in the previous two summers at the same study site. As a possible result of cool temperatures and rainfall, the peak in arthropod abundance was narrow, about a week around 20 July (Schekkerman et al. 2004). Mass (g) Time budget 15 10 5 0 0 5 10 15 Age (d) Fig. 1. The growth of little stint chicks at Medusa Bay in 2002. The data points show individual measurements of chicks, and the curve is the logistic growth function, M 26.6/(1exp( 0.2340 (t 7.40))), based on the medians of individual fitted curve parameters; see text for method. faster than those that hatched later. Mid-interval date was negatively correlated to ambient temperature (Pearson product moment correlation: r0.565, n 89, P B0.001). The growth index was positively related to ambient temperature (Ta,8C) in young chicks up to two days of age, but not in older chicks (Fig. 2, Table 1). The results using the different growth indices indicate that little stint chicks in Medusa Bay in 2002 did not grow as rapidly as has been observed in this species previously. Energy expenditure Chick growth Throughout the prefledging period, 338 captures and recaptures were made of 98 chicks from 34 broods. Fifty-nine chicks were caught at least once after they were five days old. Median hatching mass of chicks found in the nest cup was 4.3 g (mean 4.2, range  3.2
4.9, SD 0.3, n 57). Chicks fledged when 14
16 days old (based on last capture), weighing between 19.3 and 24.4 g (mean 22.3, SD 1.9, n 5). This was 73% to 92% of body mass of adult little stints, 26.6 g (Tulp et al. 2002). Although no formal test was possible, the logistic growth model seemed to fit the body mass data of little stints as well as or slightly better than the Gompertz growth model. Body mass (M, g) in relation to age (t, d) was described as: M 26:6=(1exp(0:234(t7:40))) (SEKL 0.006, SET 0.169, n 99, Fig. 1). Significant negative relationships were found between the growth index and mid-interval date (Table 1), indicating that there was a seasonal effect on growth. Chicks that hatched early in the breeding season grew 556 Twenty-nine measurements of DEE were made on 22 free-living chicks from eight broods. Seven chicks had two measurements made on them, at intervals of at least four days. In the 21 cases when the two-sample protocol was used, the initial blood sample was taken after an equilibration period of 0.50 to 1.27 h (mean 0.81, SD 0.18). Final blood samples of these chicks were taken 24.0
24.1 h after the initial samples were taken (mean 24.0, SD 0.02, n 21). Eight DLW measurements were taken using the single sample method; three of these were for three repeated measurement chicks and five were completed on small chicks weighing less than 6 g. These chicks were sampled 24.0
24.1 h after injection (mean 24.0, SD 0.02, n 8). During all experiments, chicks gained mass at an average rate of 0.82 g d 1 (range 0.10
3.50, SD 0.74, n 29). The mean growth index over the DLW measurement interval was 0.97 (SD 0.040, range 0.39
1.39, n 29), hence the DLW chicks grew as fast as other chicks in the field. The DEE data showed a normal distribution with no outliers. The standard power curve relationship between DEE (kJ d 1) and body mass (M, g) was: Table 1. Growth index of body mass in free-living little stint chicks at Medusa Bay in 2002 and mid-interval date (middle date between first and last measurement), and ambient temperature, Ta; for more detail see text and Fig. 2. Predictor variable Mid-interval date Mid-interval date Mid-interval date Ta Ta Ta Constant Predictor r2 P 1.39290.195 1.48690.263 1.91890.408 0.73190.124 0.50390.154 1.29390.436 0.01790.007 0.04190.011 0.03290.014 0.02490.014 0.04190.015 0.04390.059 0.061 0.232 0.116 0.031 0.135 0.012 0.020 0.001 0.027 0.091 0.011 0.472 DEE 0:655M1:793 (Fig: 3a) (r2 0.937, SEa 1.256, SEb 1.227, n 29). This power curve tended to underestimate DEE in chicks of 10 to 15 g, and to overestimate DEE in chicks heavier than 20 g (Fig. 3a). The Runs test showed that the data did not follow the standard power curve (Runs test: n1 16, n2 13, u6, P B0.001). The inclusion of an additional term to form the modified power curve significantly improved the fit (F-test: F 62.0, df 1, 26, PB0.001): DEE 10 13:30 M 5:610(60:02=M) (Fig: 3b): 2 (r 0.981, SEa 51.76, SEb 7.625, SEc 0.942, n 29). The residuals of the modified power curve were evenly distributed along the fitted curve through the body mass range (Runs test: n1 15, n2 14, u12, P
0.1). According to the modified power curve daily energy requirements of little stints increased during the prefledging period, from 8.0 kJ d 1 in the first day after hatching to 128.0 kJ d 1 in a 22.4 g chick that was close to fledging (i.e. aged 15 days). The average ambient temperature at Medusa Bay during the DEE measurements was 7.88 C (range  5.1
10.3, SD 1.22, n 29), mean wind speed was B 1.5 Growth index Growth index A 1.0 0.5 c 1.5 1.0 0.5 7.1 m s 1 (range 4.9
8.9, SD 1.36, n 29) and mean rainfall was 2.7 mm (range 0.0
7.0, SD 2.66, n 29). The fit of the modified power curve was not significantly improved through the inclusion of Ta (P 0.315), wind speed (P 0.221) or rainfall (P 0.318) during the DLW measurement. Logtransforming the weather variables before inclusion in the regression did not change the results. Energy budget The relationship between ME (kJ d 1) and body mass (M, g) can be described by the standard power curve, ME 1:0859M1:651 (Fig: 3a) (r2 0.943, SEa 1.219, SEb 0.078, n 29). The inclusion of the additional term to form the modified power curve resulted in ME 2:33311 M4:585(50:564=M) (Fig: 3b) (r2 0.945, SEa 39.719, SEb 0.878, SEc 7.113, n 29). According to the F-test, the standard power curve was the better fitting model (F-test: F 2.91, A 200.0 160.0 120.0 80.0 40.0 0.0 0.0 23-Jul 2-Aug 12-Aug Mid-interval date 4 6 8 10 12 14 16 Te (° C) Fig. 2. Growth index over recapture intervals of little stint chicks at Medusa Bay in 2002, in relation to (A) mid-interval date and (B) mean ambient temperature. Filled circles and the solid line represent chicks up to two days old, and open circles and the dashed line represent chicks older than two days old. 200.0 160.0 120.0 80.0 40.0 0.0 0 5 10 15 20 25 Mass (g) 0.0 13-Jul B DEE or ME (kJ d–1) All: 0
2 d
2 d All: 0
2 d
2 d Regression coefficients9SE DEE or ME (kJ d–1) Age of chicks 0 5 10 15 20 25 Mass (g) Fig. 3. The relationship between daily energy expenditure (DEE, kJ d 1) and daily metabolisable energy (ME, kJ d 1), with body mass (g) of little stint chicks at Medusa Bay in 2002 described by (A) the standard power curve and (B) the modified power curve. The solid circles and solid line represent the DEE data and the fitted allometric relationship, and the open circles and dotted line represent the ME data and the fitted allometric relationship. 557 df 1, 26, P B0.1). The residuals of the standard power curve were, however, distributed in clumps along the fitted curve (Runs test: n1 11, n2 18, u 8, P B0.01). The residuals of the modified power curve were more evenly distributed through the body mass range (Runs test: n1 13, n2 16, u 12, P
0.05). Thus we chose to use the modified power curve for these data also. The fit of the modified power curve was not significantly improved by the inclusion of Ta (P  0.166), wind speed (P 0.576), or rainfall (P  0.274) over the ME measurement period or the logarithm of these variables. Peak DME (at 15 d) of little stint chicks was 137.1 kJ d 1 (Fig. 4, Table 2), and TME over the 15-d prefledging period was 1348.4 kJ (Table 2). Growth efficiency of little stint chicks up to 15 days old was 11%; 14% of TME was allocated to growth and 86% to RMR and Ethact. Peak DME and TME estimated using the standard power curve were greater than those estimated by the modified power curve (Table 2). This is a result of overestimations by the standard power curve in larger chicks (Fig. 3a). Average daily metabolisable energy, (ADME), which is TME divided by both fledging mass (g) and time to fledging (d, Weathers 1992), was 3.95 kJ g 1 d1 for little stint chicks. Time budget Energy (kJ d –1) Chicks up to one week old spent an average of 46% (SD 23, n 28) of their time brooding and 52% of their time foraging (SD 22, n 28). Chicks older than one week spent 21% (SD 27, n 12) of their time brooding and 76% of their time foraging (SD  27, n 12). Other activities, including preening, walking and vigilance, were observed for only 2% (SD 4) of the time during the first week and 3.5% 160 DEE 140 Etis 120 ME Table 2. Energy budget results from the standard power curve and the modified power curve describing the relationship between body mass and DEE for little stint chicks at Medusa Bay in 2002. Peak DME (kJ d 1) TME (kJ) Relative peak DME (% above the prediction) Relative TME (% above the prediction) Total energy accumulated (kJ) Energy of heat produced in biosynthesis (kJ) Total energy for growth including biosynthesis (kJ) Growth efficiency (%) Total energy for growth (%) Total energy for RMR, Ethact (%) Standard power curve Modified power curve 185.9 1413.8 196.6 137.1 1348.4 118.8 116.9 106.9 142.7 47.5 142.7 47.5 190.2 190.2 10.1 13.5 86.5 10.6 14.1 85.9 thereafter. Little stint chicks therefore spent most of their ‘‘unbrooded’’ time foraging. The proportion of time brooded decreased significantly with increasing age and with increasing temperature (Table 3, Fig. 5). The regression lines in Fig. 5 overestimate the brooding times of older chicks as few observations were made on chicks older than 12 d which effectively no longer require brooding. In addition there was a tendency for brooding time to be increased between 22:00 and 04:00 h, indicative of a circadian activity rhythm with sleep accommodated into night-time brooding bouts, but this was not significant (P 0.17), probably as a consequence of the small sample size for ‘‘night’’ relative to ‘‘day’’. Interactions between age, temperature and ‘night’ proved not significant (all P
0.41), nor were additional effects of wind (P0.35), or rainfall (P 0.15), if included in a model containing age and temperature. Results were very similar if body mass was used as a predictor of brooding time instead of age (Table 3). Discussion 100 A new function to describe energy expenditure 80 60 40 20 0 0 5 10 15 Age (d) Fig. 4. Prefledging energy budgets for free-living little stint chicks at Medusa Bay in 2002 growing at an average rate from hatching to fledging. Components shown are daily energy expenditure (DEE), energy in tissue (Etis) and metabolisable energy intake (MEI). 558 The modified power curve with a gradually changing allometric scaling exponent provided a significantly better fit to the daily energy expenditure (DEE) versus body mass relationship than the standard power curve with a constant scaling exponent. In shorebird neonates, mass-specific resting metabolic rate (RMR) is at about 50% of the level observed in adult non-passerine birds (Visser and Ricklefs 1993). During early postnatal growth RMR increases rapidly with increasing body mass (intraspecific allometric scaling exponents being Table 3. Regression analysis for brooding time of little stint chicks at Medusa Bay in 2000, 2001 and 2002. Modelled with (A) age and (B) body mass. F-probabilities are for terms sequentially added to the model; estimates (logit proportion of time brooded are for the final model including all variables). Variable added df Change in deviance Deviance ratio F-probability Estimate (logit) SE Constant Age Temperature ‘Night’ Residual 1 1 1 36 2.7718 0.6881 0.7082 0.0676 1.3756 19.87 20.45 1.95 B0.001 B0.001 0.171 1.674 0.1250 0.2182 0.473 0.501 0.0476 0.0623 0.345 Constant Mass Temperature ‘Night’ Residual 1 1 1 36 2.7718 0.4807 0.8155 0.0993 1.3763 12.41 21.06 2.56 0.001 B0.001 0.12 1.839 0.0878 0.2217 0.574 0.544 0.0349 0.0626 0.356 A B about 2 initially and about two thirds thereafter) to approach adult levels. In the past, multiphasic analyses have been performed in an attempt to describe these changes in RMR (Dietz and Ricklefs 1997), but it is unlikely that changes in the RMR versus body mass relationship occur instantly at a specific body mass. In free-living chicks, DEE versus body mass relationships may exhibit an even more pronounced pattern than RMR versus body mass, because the aforementioned changes in RMR are accompanied by major behavioural changes, e.g. in the time spent actively foraging. Because both physiological and behavioural changes occur gradually the changes in DEE with increasing body mass are better described by a model containing 100 Cold, T < 7° C Warm, T > 7° C T = 3° C T = 7° C 80 Time brooded (%) T = 14° C 60 40 20 gradual change in the allometric scaling exponent, like the modified power curve. According to Tulp et al. (unpubl. data) adult little stints in Medusa Bay have a DEE of 154
160 kJ d 1 during incubation and chick rearing. The modified power curve for chicks predicts a DEE of 124 kJ d 1 at adult body mass (26.6 g), ca 20% below measured adult values. Given the differences in behaviour between adults and chicks (e.g. energy-demanding flights are not made by chicks) this seems a reasonably close match. Extrapolation of the standard power curve results in a value that exceeds the prediction for adults by 145%. The better fit of the modified power curve will therefore also improve the estimates for peak daily metabolisable energy (peak DME), and total metabolisable energy (TME) of little stint chicks (Table 2). The biphasic approach estimates a break-point between the two models that is a mathematical artefact rather than a distinct physiological event. Weathers and Siegel (1995) analysed chick RMR of 25 species (from 31 studies) including 6 passerine and 19 non-passerine species. They found that biphasic analysis did not adequately describe the metabolism of four out of 15 non-passerine precocial and semi-precocial species included in their analysis (Weathers and Siegel 1995). In addition, this method would require five estimated parameters; four for the two power curves and one for the break-point between them. The modified power curve contains only three. Little stint chick energetics 0 0 10 20 Age (d) Fig. 5. Percentage of time little stint chicks at Medusa Bay in 2002 spent being brooded in relation to (A) age (d) and air temperature (8C), (regression lines shown for the lowest, mean and highest air temperatures during observations). Our estimates of prefledging metabolism in little stint chicks, as summarised in values for peak DME and TME can be compared to those of other birds by contrasting them to allometric predictions based on fledgling body mass (Mfl, g) and the length of the prefledging period (tfl, days; Weathers 1992): 559 predicted peak DME 11:69M0:9082 tfl0:428 ; fl and predicted TME 6:65M0:852 t0:71 fl fl : Observed peak DME and TME of little stint chicks were 119% and 107% greater than predicted, respectively. Schekkerman et al. (2003) found that the observed TME of red knots Calidris canutus at 758N was 89% above the predicted value and that this large relative TME conformed to that observed in other arctic-breeding bird species. As observed in little stint chicks of this study, the ADME of arctic-breeding red knots was also large, 2.58 kJ g 1 d1 (Schekkerman et al. 2003). Therefore little stint chick energetics showed similar traits to that observed in other arctic-breeding birds with precocial young. Shorebird chicks in the Arctic grow rapidly in comparison to the expected growth rates for their size (Schekkerman et al. 1998a, 1998b, 2003), and precocial chicks in cooler temperatures exhibit greater overall energy expenditure than expected as a result of increased metabolism (Visser and Ricklefs 1993). Krijgsveld et al. (unpubl. data) found that the chicks of smaller arctic shorebirds had a greater mass-specific DEE than larger species, indicating a higher metabolic capacity (DEE versus RMR) than chicks of larger species. The fast growth and large energy expenditures of shorebird chicks at high latitudes can only be sustained through sufficient food intake. Lack (1968) suggested that the abundance of arthropods increased with latitude. Schekkerman et al. (2003) found no significant difference in arthropod availability between the arctic tundra at Cape Sterlegov, and a temperate meadow in The Netherlands. The higher intake rate of red knot chicks was tentatively attributed to the simpler structure of the tundra vegetation and a larger proportion of wingless or slow-moving arthropods making prey capture easier. This may also apply to little stint chicks. The impact of environmental conditions on energy expenditure, time budgets and growth of little stint chicks The growth rate of shorebird chicks can be influenced by bouts of cold and wet weather (Beintema and Visser 1989a). Schekkerman et al. (1998b, 2003) found that cold weather resulted in a reduction of growth rate in curlew sandpipers Calidris ferruginea and red knots. The growth of little stint chicks less than two days old was influenced by ambient temperature whereas that of larger chicks was not. Adverse weather may affect chick energy budgets in several ways; it may increase energy expenditure, reduce feeding time through an increase of 560 brooding, and reduce feeding success through diminished insect prey availability. Although larger chicks do not suffer the same time and thermoregulatory constraints as young chicks, reduced food availability can have a similar effect on their foraging efficiency and thus their growth. We found no significant effect of ambient temperature, wind or rain on DEE or ME. The range of mean ambient temperatures during DEE measurements was small (5
108C) compared to the range occurring at Medusa Bay over the chick-rearing period (1
178C; unpubl. data 2000
2002). Consequently, our sample had limited power to show such effects. Young chicks are unable to maintain body temperature under conditions of low temperature (Norton 1970, Visser and Ricklefs 1993, Krijgsveld et al. 2003). Consequently, their mobility, rate of food intake (Krijgsveld et al. 2003) and possibly digestive efficiency (Kleiber and Dougherty 1934, Hume 2005) decrease. Young chicks seek brooding to both increase their body temperature and to reduce energy expenditure (Klaassen et al. 1992, Krijgsveld et al. 2003). Although larger chicks do not suffer the same time and thermoregulatory constraints as young chicks, reduced food availability can have a similar effect on their foraging efficiency and thus their growth. In the 2002 breeding season, little stint chicks hatched late in relation to the seasonal peak in arthropod availability (Schekkerman et al. 2004), and this affected chick growth. Little stint chicks that hatched early in the breeding season grew faster than those that hatched later. Being brooded can reduce the heat loss of chicks to the environment and thus can reduce energy expenditure. The amount of time little stint chicks spent brooding decreased with age, and chicks were rarely observed to be brooded during the day after the age of 10 d. However, neither little stint chicks (this study) nor red knot chicks (Schekkerman et al. 2003) took full advantage of the 24-h arctic daylight period to feed. How does the growth of little stint chicks compare to other species? Growth rate coefficients of the different bird species described in Rahn et al. (1984), Beintema and Visser (1989b), and others (Ricklefs 1973, Visser and Ricklefs 1993, Krijgsveld et al. unpubl. data) decrease with increased body size. Shorebird breeding seasons in the Arctic are limited by the short summers and it has been found that birds breeding in the Arctic, for instance red knots (Schekkerman et al. 2003) and purple sandpipers Calidris maritima (Summers and Nicoll 2004) have large growth rate coefficients. The combined effect of breeding latitude and their small size may have resulted A 140 Ccan Relative K G (%) 120 100 Cfer 80 Ccan Cruf 60 40 20 Cpus 0 Cmel Cfus Calp Cbai Cmel Cmar Cpti Calb –20 Cmar –40 1.2 1.4 1.6 1.8 2 2.2 Log A (g) B 140 Ccan Relative K G (%) 120 100 Cfer Ccan 80 Cruf 60 40 Calp 0 Cpti Cmar –20 Cmar Cmel Cfus 20 Cpus Cmel Cbai Calb –40 60 65 70 75 80 85 Latitude (°N) Fig. 6. The relationship between relative Gompertz growth rate coefficient (KG, d 1) and (A) asymptotic body mass (A, g) and (B) latitude (8N) for arctic-breeding sandpipers. The little stint data from Schekkerman et al. (1998a) are represented by ', and data from this study by D. The 14 species represented in this figure by /m are Calb; sanderling Calidris alba (Parmelee 1970 in Beintema and Visser 1989b, Glutz von Blotzheim et al. 1975), Calp; dunlin Calidris alpina (Soikkeli 1975 in Beintema and Visser 1989b), Cbai; Baird’s sandpiper Calidris bairdii (Norton 1973 in Beintema and Visser 1989b), Ccan; red knot Calidris canutus (Schekkerman et al. 2003), Ccan; red knot (Tomkovich unpubl. data), Cfer; curlew sandpiper Calidris ferruginea (Schekkerman et al. 1998b), Cfus; white-rumped sandpiper Calidris fuscicollis (Parmelee et al. 1968 in Beintema and Visser 1989b]), Cmar; purple sandpiper Calidris maritima (Tomkovich 1985, Glutz von Blotzheim et al. 1975), Cmar; purple sandpiper (Summers and Nicoll 2004), Cmel; pectoral sandpiper Calidris melanotos (Norton 1973 in Beintema and Visser 1989b), Cmel; pectoral sandpiper (Andreev 1988), Cptil; rock sandpiper Calidris ptilocnemis (Gill, Tomkovich and McCafferty 2002), Cpus; semipalmated sandpiper Calidris pusilla (Safriel 1975 in Beintema and Visser 1989b) and Cruf; red-necked stint Calidris ruficolis (Morozov and Tomkovich 1988, Tomkovich and Morozov 1994, Schekkerman et al. 1998b). in little stint chicks exhibiting large growth rate coefficients. The predicted Gompertz growth rate coefficient (KG) for shorebird species with an asymptotic mass of 26.6 g using the equation KG 0.390 A0.312 (Beintema and Visser 1989b) was 0.140 d 1. Assuming that the asymptotes are identical in the logistic and Gompertz models, KL can be converted to KG using the equation KG 0.68 KL (Ricklefs 1983). Following this, the little stint chicks we studied at Medusa Bay in 2002 had a KG of 0.159 d 1 which is 14% above the predicted growth for a 26.6 g shorebird. The observed growth rate coefficients for individual chicks at Medusa Bay in 2002 was greater than the prediction (one sample t-test: t  4.12, df9, P B0.001). Schekkerman et al. (1998a) found that little stints breeding between 728N and 768N in Siberia grew rapidly; with a KG of 0.191 d 1 for all three sites combined (Fig. 6a). According to this pooled result little stint chicks grew 37% faster than predicted for a shorebird of 26.7 g (Schekkerman et al. 1998a). The little stint chicks we studied at Medusa Bay (738N, 2002) also grew faster than predicted but not as fast as was observed by Schekkerman et al. (1998a). This may be a combined effect of the lower latitude of our study site, and the different environmental conditions experienced by the chicks during our study breeding seasons. Calidrid shorebird species that breed at latitudes greater than 608N, exhibit growth rate coefficients close to or greater than predicted by the equation of Beintema and Visser (1989b, Fig. 6b). The negative relationship between asymptotic body mass and KG described by Beintema and Visser (1989b) may explain the large growth rate coefficients of little stints compared to that of larger shorebird species growing at similar latitudes, e.g. Baird’s sandpiper Calidris biardii (48 g; Fig. 6b). Some shorebird species, such as the red knot or curlew sandpiper are, however, able to grow at relatively faster rates than the little stint, despite their larger asymptotic body mass. The relative energy expenditure of little stints was greater than that of red knots (Schekkerman et al. 2003), but this was not reflected in an equally large growth rate. This is most likely a consequence of their poor surface to volume ratio resulting in relatively higher thermoregulatory costs. Despite this relatively high energy expenditure they are capable of rapid growth that allows them to fledge within the short period available in the arctic. Acknowledgements
This work was made possible through participation in the program North-South (DWK 404), which was financed by the Dutch Ministry for Agriculture, Nature Management and Food Safety. KMCT’s participation was enabled by a travel bursary from the Skye Foundation. Further support (KMCT and LGU) was provided by the Centre for Isotope Research (CIO) at the University of Groningen, the Darwin Initiative, the Earthwatch Institute, the National Research Foundation, the University of Cape Town, the Association for the Study of Animal Behaviour and the South African Network for Coastal and Oceanographic Research. Cape Storm supplied hard weather equipment and Marine and Coastal Management, Department of Environmental Affairs and Tourism, Cape Town, loaned equipment 561 to KMCT. KMCT and LGU are grateful to Bart and Dorothea Ebbinge for hospitality in the Netherlands and to Gerard Muskens and his team for assistance in the logistical arrangements of getting KMCT to the study site. Staff of the Great Arctic Reserve, Sergei Kharitonov and Alexander Belyashov assisted in the organisation of the expedition. Berthe Verstappen (CIO) performed the isotope analyses of all blood samples. We thank Raymond Klaassen for help in collecting data. References Andreev, A. V. 1988. Food demands and individual survival in the arctic chicks. Studies and protection of birds in northern ecosystems.
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