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Keywords:

  • doubly labelled water;
  • energetic limitation;
  • field metabolic rate;
  • fitness;
  • oxidative stress

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

1. The rate at which free-living animals can expend energy is limited but the causes of this limitation are not well understood. Theoretically, energy expenditure may be intrinsically limited by physiological properties of the animal constraining its capacity to process energy. Alternatively, the limitation could be set extrinsically by the amount of energy available in the environment or by a fitness trade-off in terms of reduced future survival associated with elevated metabolism.

2. We measured daily energy expenditure (DEE) using the doubly labelled water method in chick-rearing black-legged kittiwakes (Rissa tridactyla) at a study site close to the northern limit of their breeding range over 5 years. We measured breeding success, foraging trip duration and diet composition as proxies of resource availability during these years and estimated the probability of parent kittiwakes to return to the colony in relation to their energy expenditure in order to determine whether kittiwakes adjust their DEE in response to variation in prey availability and whether elevated DEE is associated with a decrease in adult survival.

3. We found that DEE was strikingly similar across all five study years. There was no evidence that energy expenditure was limited by resource availability that varied considerably among study years. Furthermore, there was no evidence of a negative effect of DEE on adult return rate, which does not support the hypothesis of a survival cost connected to elevated energy expenditure.

4. The additional lack of variation in DEE with respect to ambient temperature, brood size or between sexes suggests that kittiwakes at a time of peak energy demands may operate close to an intrinsic metabolic ceiling independent of extrinsic factors.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Energy is a fundamental resource required to survive and reproduce. The limitation of this resource has important implications for the ecology of animals and constitutes a central concept underlying life-history theory and optimal resource allocation (e.g. Weiner 1992). Although it is widely accepted that the rate at which animals can expend energy is limited, the nature of this constraint is debated (Weiner 1992; Hammond & Diamond 1997; Speakman 2000) and evidence for energetic limitation in free-ranging species is scarce (Tinbergen & Verhulst 2000; Costa 2008; Zub et al. 2009).

In their seminal paper, Drent & Daan (1980) proposed that the maximum metabolic rate that birds may sustain over extended time periods (i.e. long enough for energy expenditure to be balanced by energy intake) may be intrinsically set by physiological constraints. However, despite considerable research in recent years, studies dedicated to defining the limiting processes imposing an intrinsic energetic ceiling have largely failed (e.g. reviewed in Speakman 2000, 2008; but see Krol, Murphy & Speakman 2007), and an intrinsic limitation of the metabolic rate of animals under natural conditions has rarely been demonstrated (Zub et al. 2009). Furthermore, estimates of energetic ceilings derived from interspecific comparisons indicate that the majority of species may usually work well below the supposed physiological limit (Peterson, Nagy & Diamond 1990; Speakman 2000; Ellis & Gabrielsen 2002).

These findings have led to the suggestion that the sustainable rate of energy expenditure even at time periods of peak requirements, such as lactation in mammals and chick-rearing in birds, may be set by extrinsic factors rather than physiological properties of the organism. An extrinsic limitation may be imposed by the availability of food or factors constraining the ability of animals to extract food from the environment (Speakman 2000; Tinbergen & Verhulst 2000; Thomas et al. 2001; Speakman et al. 2003). Although experimental data suggest that some species may be capable of collecting more food than they normally do (e.g. Masman et al. 1989), there is increasing evidence that food limitation may be an important factor restricting the metabolic rate of free-living animals. For example, a number of studies have shown that animals may increase their rate of energy expenditure when the supply of food from the environment is enhanced (Speakman et al. 2003; Jodice et al. 2006; Welcker et al. 2009). Also, interspecific comparisons have indicated that species feeding on energy-rich diets or living in resource-rich habitats have higher metabolic rates than species living in comparatively poor habitats (Speakman 2000; Mueller & Diamond 2001).

Alternatively, animals may spend energy at a lower rate than physiologically possible because an increase in metabolic rate may be associated with a fitness penalty in terms of increased mortality. Both experimental (Wolf & Schmid-Hempel 1989; Daan, Deerenberg & Dijkstra 1996; Golet et al. 2004) and empirical studies (Bryant 1991) have reported a negative relationship between energy expenditure and future survival. Increased mortality may be brought about indirectly by an increased risk of predation or accident in connection with increased activity. More importantly, however, the ‘free-radical damage hypothesis’ (Harman 1956) has been proposed as a proximate mechanistic explanation for a potential direct physiological trade-off between metabolic rate and life expectancy. This hypothesis suggests that somatic damage caused by reactive oxygen species, inevitable by-products of oxidative metabolism, increases with increasing metabolism that may lead to accelerated senescence and death (Harman 1956; Beckman & Ames 1998; Monaghan, Metcalfe & Torres 2009).

A better knowledge of the causes of energetic limitation may help to understand variation in reproductive performance and resource allocation decisions of different species. For example, it has been debated whether or not long-lived species, such as seabirds, would be expected to be flexible in their reproductive investment because an increase in parental effort may lead to reduced future reproduction and therefore to lower lifetime reproductive success (Stearns 1992). It has been argued that stochastic variation in environmental conditions may favour a highly flexible parental investment (e.g. Erikstad et al. 1997, 1998). However, high flexibility in parental effort may partly depend on energetic flexibility and species operating close to an energetic ceiling are likely to be restricted in their set of options to allocate resources (Costa 2008).

Despite the potential significance of metabolic constraints for the ecology of animals, the occurrence and causes of metabolic ceilings in free-ranging animals are not well studied (see Tinbergen & Verhulst 2000). This lack of information may partly be due to a paucity of empirical data, especially multi-year comparisons of energy expenditure of animals during their energetically most demanding life stages, which would allow inference about the flexibility of energy budgets on a species or population level (see Tinbergen & Dietz 1994, for an exception). In this study, we examined the energy expenditure of black-legged kittiwakes (Rissa tridactyla Linnaeus; hereafter referred to as ‘kittiwakes’), a small (body mass c. 370 g), cliff-breeding gull species, at a colony close to the northern boundary of their breeding range over a period of 5 years. Our goals were (i) to examine whether kittiwakes at a time of maximum energy demands operate close to a physiological ceiling or adjust daily energy expenditure (DEE) in response to extrinsic factors, particularly variability in foraging conditions, and (ii) to determine whether energy expenditure in this species is limited due to adverse effects associated with elevated DEE leading to a reduced probability to survive.

Materials and methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Study area and species

The study was conducted at a breeding site of kittiwakes in Kongsfjorden (78°54′ N, 12°13′ E) at the west coast of Spitsbergen, Norway. Field work took place in July and August in 1997 and 1998, and from 2005 to 2008. In Kongsfjorden, kittiwakes breed in several small- to medium-sized colonies, and the study sites used lay in the inner part of the fjord between 0·5 and 7 km apart from each other.

Kittiwakes are long-lived, colonial seabirds with a northern circumpolar distribution. They are surface-feeders and mainly prey on small pelagic fish (e.g. Barrett 2007). Both partners of a pair share parental duties throughout the chick-rearing period and parents provision their chicks by regurgitating partly digested food at the nest site. Kittiwakes are slightly sexually size-dimorphic with males weighing on average 12% more than females (e.g. Angelier et al. 2007).

Energy expenditure

We obtained estimates of DEE (kJ day−1) of kittiwakes with the doubly labelled water (DLW) method (Lifson & McClintock 1966; Speakman 1997) during the mid-chick-rearing stage when DEE is known to peak in this species (Fyhn et al. 2001). The DLW method has previously been validated in birds by comparison to respiration gas analysis (Visser & Schekkerman 1999). Because DEE in kittiwakes varies with chick age (Fyhn et al. 2001) measurements in all years were taken when chicks were about 20 days old (range 17–22). Parent kittiwakes were captured at their nest using a 7-m telescopic pole with a snare fitted to its end. Upon capture, they were weighed to the nearest 5 g (Pesola spring balance), and head plus bill length was measured to the nearest 0·1 mm (Vernier calipers) from the back of the head to the tip of the upper mandible. In addition, birds were individually marked with a numbered steel band and, from 2005 onwards, additionally with a colour plastic band engraved with a unique three digit code. Each bird was then injected intramuscularly (pectoral muscle) with a dosage of DLW using a gastight Hamilton syringe. In 1997 and 1998, we injected 1·20 and 1·10 mL of DLW respectively containing 90·4 and 91·5 atom per cent excess (APE) oxygen-18 (18O) and 0·4 mCi tritium (3H). From 2005 to 2007, the injectate volume ranged from 0·38 to 0·90 mL and contained either 62·1 APE 18O and 33·9 APE deuterium (2H) or 56·8 APE 18O with 41·1 APE 2H. With few exceptions, both partners of a pair were injected. Following injection, individuals were kept in a covered cage or cloth bag for 1 h to allow equilibration of isotopes with the body water (Speakman 1997). Prior to release, an initial blood sample was obtained by puncturing a brachial vein. Blood was collected into two to four 70-μL glass microcapillaries, which were immediately flame-sealed. From 2005 onwards, an additional droplet of blood was collected for subsequent molecular sexing following standard techniques as detailed in Fridolfsson & Ellegren (1999). Sexing of birds in 1997 and 1998 was based on morphometric measurements (see Moe et al. 2002). An additional three to six kittiwakes were captured and bled each year to determine mean background levels of isotopes (Speakman & Racey 1987: method C).

We attempted to recapture labelled individuals twice between 24 and 72 h after injection. Upon recapture, birds were weighed again, a second blood sample was collected as described above and the birds released immediately. In total, 130 kittiwakes were injected in the course of the study of which 36 birds were recaptured only once, 84 individuals were recaptured twice while 10 individuals evaded recapture completely. Because sampling periods exceeding 24 h reduce the error due to high day-to-day variance in DEE (Speakman et al. 1994; Berteaux et al. 1996), we calculated DEE over the extended time period for all individuals that were recaptured twice after injection. The time elapsed between injection and final recapture averaged 49·6 h ± 14·8 (SD) with yearly means ranging from 42·8 h ± 14·4 (SD) to 55·5 h ± 16·4 (SD).

Isotopic enrichments of blood samples taken in 1997 and 1998 were determined by liquid-scintillation spectrometry (3H) and proton activation analysis (18O; Wood et al. 1975) at the University of California, Los Angeles, USA. Samples obtained from 2005 to 2007 were analysed by isotope ratio mass spectrometry as described in Speakman et al. (1990) for 18O and Speakman & Krol (2005) for deuterium. Final isotope enrichment was on average 170 p.p.m. (range: 738–35) and 302 p.p.m. (range: 1533–35) above background for 2H and 18O, respectively. Background level of both isotopes varied <5 p.p.m. among individuals in all years. We calculated the rates of CO2-production using a single pool model as recommended for birds of <1000 g body mass (Speakman 1993). We assumed a fixed evaporative water loss of 25% (equation 7·17, Speakman 1997), which has been shown to minimize error in studies of birds (Visser & Schekkerman 1999; Van Trigt et al. 2002). Total body water at initial capture was determined from the 18O dilution space (Speakman 1997). Final body water content was calculated based on body mass and assuming a constant fraction of body water throughout the experiment (Shaffer et al. 2006).

To convert estimates of CO2-production to DEE, we calculated year-specific caloric equivalents according to Gessaman & Nagy (1988). We assumed that the energy expended during DEE measurements was mainly derived from catabolism of ingested food. Regurgitated food samples from kittiwakes each year were analysed for protein and fat content. The fat : protein ratio of the diet differed only to a small extent between study years and accordingly inter-annual variation in the estimated caloric equivalent was minor (range: 27·60–27·66 J mL−1 CO2).

Water influx rate (WIR; mL day−1) was calculated following Visser et al. (2000). WIR estimates were corrected for isotope fractionation effects (equation 7·6, Speakman 1997) assuming a fractionation factor of 0·94 and, as above, an evaporative water loss of 25% (Speakman 1997; Visser et al. 2000). Assuming that the water content of food and metabolic water production constitute the only sources of water influx, WIR can be used as a proxy for food intake rate.

Adult return rate

To assess potential direct costs of elevated DEE, we estimated the probability of parent kittiwakes to return to the colony in relation to their rate of energy expenditure during the preceding breeding season in three of the five study years. From 2006 onwards, we conducted re-sightings of colour-marked individuals from which we had obtained a DEE estimate the previous year. The presence or absence of these birds was determined the following year through intensive observations, which comprised the specific study sites of the previous season as well as adjacent colonies. Re-sighting effort was scheduled from incubation (June) to late chick-rearing (August) and was carried out for at least 20 days each year. Very high observation effort allowed us to assume a within-year re-sighting probability of close to one.

Additional parameters

To gauge inter-annual variability of foraging conditions of kittiwakes in the study area, we simultaneously recorded diet composition, the duration of foraging trips and reproductive success; parameters that have been shown to be sensitive to food availability in kittiwakes (Oro & Furness 2002; Frederiksen et al. 2005; Piatt et al. 2007). The proportion of fish (% wet weight) in the diet was determined each year from food samples that were collected opportunistically whenever parent kittiwakes or nestlings regurgitated during handling procedures. In that way, a total of 338 samples were obtained. In the laboratory, regurgitations were weighed to the nearest 0·1 g and prey items were identified to species level based on gross morphological characteristics. Partially digested fish were identified by use of sagittal otoliths.

To estimate foraging trip duration, behavioural observations were conducted at 26–40 kittiwake nests each year shortly before the onset of the DLW experiments. Prior to observations, all birds of focal nests were captured and marked as described above. To facilitate easy identification, birds were additionally marked on head and/or breast with colour-marker pens. Observations were carried out continuously for 24 h in 1997, 1998 and 2005, and for 10 h on three consecutive days in 2006 and 2007. The presence and absence of each adult was recorded every 20–30 min, and a bird was assumed to perform a foraging trip whenever it was absent from the nest site during two successive observations.

A measure of breeding success was derived from regular visual inspections of c. 100 (range 92–130) nests each year. Nest visits were started at egg-laying but did not last until the fledging period in all years. Hence, to obtain a measure of breeding success that was comparable between years, we used the number of chicks that were alive at the age of 12 days per active nest (i.e. nests where at least one egg was laid).

Data analysis

To evaluate inter-annual variation in DEE, we used linear mixed-effects models (LME) with ‘nest identity’ as a random component to account for non-independence of partners within a pair. ‘Sex’ and ‘brood size’ (one or two chicks) were included in addition to ‘year’ as fixed effects.

To assess the potential effect of wind speed and ambient temperature on DEE, we calculated mean temperature and wind speed for the DLW measurement period for each individual and included both parameters as covariates in these models. Data on weather parameters (daily means) were obtained from the weather station at Ny-Ålesund (78°55′ N, 11°56′ E), c. 7 km from the study sites. Furthermore, we tested for and did not find an effect of time to recapture (F1,37 = 2·40, P = 0·130) or deviation of the sampling period from a multiple of 24 h on DEE estimates (F1,37 = 0·3, P = 0·577), and therefore did not include these factors in our models. To examine the effects of body mass on our results, we fitted similar models as described above with mass-independent DEE as the response variable. Mass-independent DEE was expressed as the residuals of the regression of loge DEE on loge body mass (R2 = 0·057, F1,97 = 5·8, P = 0·018).

Generalized Linear Models (GLM) with binomial error distribution and logit link function were used to assess the effect of DEE on the probability of adults to return to the colony the following season. ‘Sex’, ‘year’ and ‘body mass’ were included in addition to ‘DEE’ as explanatory variables in these models.

In all cases, we started by fitting maximum models containing all predictor variables and interaction terms. We used likelihood ratio tests (LRT) to simplify models eliminating variables and interactions if their removal from the model did not result in a significant increase in deviance. Significance of terms in the most parsimonious model was assessed by F-tests.

Inter-annual differences in the duration of foraging trips were evaluated by time-to-event analysis. This approach was chosen because relatively short observation periods, especially in 2006 and 2007, led to a relatively high proportion of right censored data that precluded a simple comparison of means. For statistical inference, we used a Cox proportional hazard model (CPH, Cox 1972) to model the ‘risk’ of birds to return to the colony including data of birds that had left the colony but did not return before observation periods had ended. ‘Sex’ and ‘year’ were included as fixed effects, ‘individual’ was included as a random effect to account for repeated measurements of the same individuals. To illustrate the data and obtain predicted foraging trip durations, we additionally fitted a parametric time-event model with Weibull error distribution. All statistical analyses were performed in r 2·7 (packages nlme, survival and kinship; R Development Core Team 2008). We report means ± 1 SE unless stated otherwise.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Energy expenditure

Daily energy expenditure of parent kittiwakes was strikingly similar in all five study years (Fig. 1, LRT: χ24 = 0·5, P = 0·977). The mean rate of energy expenditure of all single years deviated from the overall mean (881·7 ± 19·8 kJ day−1, n = 99) by <3·5%. In addition, the rate of energy expenditure was independent of brood size; mean DEE of parent kittiwakes raising two chicks did not differ from DEE of parents raising singletons (Fig. 2, LRT: χ21 = 0·4, P = 0·508). DEE of males exceeded energy expenditure of females by 13·8% (LME: F1,37 = 8·9, P = 0·005). However, this difference was attributable to body mass as mass-independent DEE did not differ between sexes (LRT: χ21 = 0·8, P = 0·359). Also, mass-independent DEE did not vary between years (χ24 = 1·2, P = 0·872) or with brood size (χ21 = 0·8, P = 0·379).

image

Figure 1.  Variation in daily energy expenditure (DEE, mean ± 1 SE) in chick-rearing kittiwakes over five study years. Sample sizes each year are given in parentheses. In addition, inter-annual variation in breeding success (fledged chicks per active nest, n = 539 nests), diet composition (proportion of fish, n = 338 samples) and the predicted duration of foraging trips are presented for each year. Predicted foraging trip durations are derived from a time-to-event model with Weibull errors based on 710 observed foraging trips. See text for more details.

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image

Figure 2.  Difference in daily energy expenditure (DEE, dots) and water influx rate (squares; means ± 1 SE) between parent kittiwakes rearing one (n = 60) or two chicks (n = 39).

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Ambient temperature during the study periods varied significantly between study years (range 5·0 ± 0·39 to 8·1 ± 0·27 °C; anova, F4,67 = 17·7, P < 0·001), but had no effect on DEE of kittiwakes (LRT: χ21 = 2·5, P = 0·117). In contrast, we found a non-significant tendency for energy expenditure to decrease with increasing wind speed (LRT: χ21 = 3·4, P = 0·066). In addition, we found that DEE was positively related to body mass change during the measurement periods (Fig. 3, LME: F1,37 = 23·8, P < 0·001). On average, DEE increased by 39·2 kJ day−1 with an increase of 1% body mass day−1. This relationship was similar in all study years (LRT: χ24 = 0·8, P = 0·945).

image

Figure 3.  Relationship between daily energy expenditure (DEE) of kittiwakes and their change in body mass (per cent per day) during the DEE measurement period.

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In contrast to energy expenditure, the WIR differed significantly among study years (LME: F4,55 = 2·6, P = 0·044). Also, WIR was lower in parent kittiwakes raising single chicks compared to parents of two chick broods (Fig. 2; F1,55 = 10·8, P = 0·002). Likewise, body mass varied significantly between study years (Table 1, LME: F4,55 = 11·0, P < 0·001), and parents that raised singletons were significantly heavier than parents with two chicks (LME: F1,55 = 13·1, P < 0·001). Furthermore, males weighed significantly more than females (Table 1, LME: F1,37 = 145·2, P < 0·001).

Table 1.   Mean body mass (g, ±1 SE) of female and male kittiwakes during chick-rearing over five study years. In addition, the weighted overall mean is given for each year
 19971998200520062007
MeanNMeanNMeanNMeanNMeanN
Females327·3 ± 4·74335·5 ± 4·613341·2 ± 3·313337·6 ± 3·812380·6 ± 12·09
Males385·01374·9 ± 6·214397·9 ± 7·915376·4 ± 6·29420·6 ± 8·99
Weighted mean356·2 355·2 369·6 357·0 400·6 

Adult return rate

Based on 3 years of data, we did not find a relationship between the rate of energy expenditure of kittiwakes during the chick-rearing period and the probability of these birds to return to the colony the following year (GLM: χ21 = 0·3, P = 0·562). Also, adult return rate was independent of body mass during the previous season and did not differ between the sexes (‘body mass’: χ21 = 0·1, P = 0·830; ‘sex’: χ21 = 0·2, P = 0·670). However, the probability to return to the colony differed significantly between study years (χ22 = 15·3, P < 0·001). Return rate was high from 2006 to 2007 and from 2007 to 2008 (0·95 and 1·0, respectively) but relatively low from 2005 to 2006 (0·64).

Proxies for foraging conditions

There was large inter-annual variation in breeding success among the five study years (Fig. 1; anova: F4,547 = 22·0, P < 0·001). Breeding success was almost three times higher during favourable years (e.g. 2005: 1·37 chicks per nest) compared to poor years (e.g. 2006: 0·56 chicks per nest). Similarly, we found large inter-annual variation in diet composition (Fig. 1; ‘proportion of fish’, anova (arcsin-transformed data): F4,333 = 21·8, P < 0·001). In some years (e.g. 1998), fish constituted only about 50% of the diet, while it made up nearly 100% of the diet in others (e.g. 2007). Finally, also the ‘risk’ of returning from a foraging trip (i.e. the duration of foraging trips) varied considerably between study years (Fig. 1; CPH: χ24 = 42·9, P < 0·001). For example, the ‘risk’ of returning from a foraging trip was more than 50% lower in 2006 compared to 2007 indicating that foraging trip duration varied more than twofold among study years (see Fig. 1).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

In this study, we examined whether kittiwakes close to the northern limit of their breeding range and at the time period of their peak energy demands operate close to an intrinsic metabolic ceiling or whether they adjust DEE in response to variation in foraging conditions. In addition, we tested whether a potential limitation may be explained by a direct cost of an increased metabolic rate in terms of a reduced probability of survival. Despite the data being generated using two completely different analytical approaches in two separate laboratories, we found a striking similarity of mean DEE across five study years. DEE did not vary among years even though we observed high between-year variation in breeding success, diet composition and foraging trip duration, indicating considerable inter-annual variability in foraging conditions. Furthermore, we did not find evidence for a correlation between inter-individual variation in DEE and the probability of parent kittiwakes to return to the colony the following year.

Individual variation in DEE was high in all study years (overall CV = 22·4%). This variation may be at least partly explained by differences in foraging activity during the sampling period. Jodice et al. (2003) could demonstrate that inter-individual variation in energy expenditure of kittiwakes in the short term can to a large extent be explained by the amount of time birds allocate to active foraging. In our study, DEE was positively related to changes in body mass during the DLW measurement period suggesting that birds that actively foraged and hence gained mass had a higher rate of energy expenditure than birds that spent longer time periods at the nest and, consequently, tended to lose mass. In addition, we found a tendency for DEE to be negatively related to wind speed. During our DLW measurement periods, wind speed was low to moderate indicating that modest wind speeds may reduce flight costs and therefore be beneficial for kittiwakes (Furness & Bryant 1996), while strong winds can have the opposite effect in this species (Gabrielsen, Mehlum & Nagy 1987).

In contrast to inter-individual variability, between-year variation in DEE was noticeably low. There was no evidence that kittiwakes adjusted their DEE in response to extrinsic factors. Firstly, ambient temperature, which has previously been shown to affect DEE in a wide range of species including birds (Bryant 1997; Tinbergen & Verhulst 2000; Anderson & Jetz 2005), differed significantly between years, but this difference did not lead to modification of energy expenditure. Second, there was no apparent adjustment of DEE with respect to changes in foraging conditions. We used three independent proxies to gauge differences in foraging conditions between the five study years. Foraging trip duration (Piatt et al. 2007) and especially breeding success reflect the availability of energy-rich fish in kittiwakes (Oro & Furness 2002; Frederiksen et al. 2005, 2006), which in turn is reflected in the composition of the diet (e.g. Barrett 2007). We found that breeding success varied almost threefold, and the proportion of fish in the diet and duration of foraging trips varied twofold among study years. Hence, our data indicate substantial inter-annual variation in foraging conditions. However, there was no corresponding variation in DEE among years. There was no evidence for an increase in DEE during food-rich years (e.g. 2005 and 2007), which would be expected if DEE in kittiwakes were limited by the availability of prey (Speakman 2000; Mueller & Diamond 2001; Welcker et al. 2009). Nor was there indication of elevated energy expenditure during food-poor years (e.g. 2006) suggesting that kittiwakes did not compensate for lower resource availability by increasing their foraging effort (Kitaysky et al. 2000). Because our data set did not include an exceptionally unfavourable year, we can however not rule out the possibility that DEE is modified during extreme foraging conditions.

Furthermore, we found no evidence for a flexible energy budget with respect to brood size. Parent kittiwakes with two chicks seemed to expend energy at similar rates as parents raising singletons. However, a significantly higher WIR of parents with two chicks indicates that these birds ingested more food than their conspecifics with single chicks and therefore presumably delivered more food to their offspring. The ability to feed more with no apparent increase in DEE suggests a higher foraging efficiency of birds with large broods. Thus, brood size within years seemed to be determined mainly by individual quality rather than by the ability of parents to increase their energetic effort.

Finally, we did not find a negative relationship between DEE and the return rate of parent kittiwakes the following breeding season which would be expected if energy expenditure was limited due to a direct or indirect survival cost of high metabolism. Even though the return rate of adults may not only reflect mortality but also (temporal) emigration and breeding propensity, the lack of a negative effect of DEE on return rate strongly suggests that the survival probability of parent kittiwakes was not affected by their rate of energy expenditure during the preceding season. This result is at odds with earlier studies that indicated a negative correlation between the rate of energy expenditure and survival (e.g. Wolf & Schmid-Hempel 1989; Bryant 1991; Daan et al. 1996; but see Jackson, Trayhurn & Speakman 2001; Welcker et al. 2009). The ‘free-radical damage’ hypothesis, which has been invoked to explain these previous findings, suggests that an elevated rate of energy expenditure may increase the generation of superoxide free radicals leading to increased somatic damage and consequently accelerated senescence and death (Harman 1956; Beckman & Ames 1998). However, the direct link between increased energy metabolism and elevated free-radical production has recently been questioned (Brand 2000; Speakman 2005) and several experimental studies failed to demonstrate a direct association between metabolic rate, oxidative stress and mortality (e.g. Speakman et al. 2004; Selman et al. 2008a, b). Our results support this view; it seems unlikely that energy expenditure is limited by a life-history penalty on future survival in kittiwakes. However, this interpretation has to be treated with care as our analysis is based on the assumption that DEE measured over a time period of c. 48 h represents the relative level of energy expenditure over longer time periods. Repeatability of DEE over extended time periods has yet to be demonstrated. In addition, due to the temporal limitation of our data (three study years), additive costs of increased energy expenditure over longer time periods may have remained undetected.

The lack of evidence of an extrinsic limitation of DEE in kittiwakes seems to lend support to the hypothesis of an intrinsic limitation by properties of the birds’ physiology. Assuming a RMR of 217 kJ day−1, measured at the same study site and at a similar age of chicks (Bech, Langseth & Gabrielsen 1999), the sustainable metabolic scope of kittiwakes averaged 4·05 × RMR (range: 3·9–4·1 between years). This estimate is well below recent estimates of the maximum sustainable metabolic scope of about 7 × RMR (e.g. Peterson et al. 1990; Hammond & Diamond 1997). The proposed ceilings were derived by interspecific comparisons of available data and selecting maximum values. Hence, it is unknown to what extent these values can be generalized for different species. Furthermore, they may be biased by inclusion of food intake estimates in lactating mice, which export part of their intake as milk rather than expending it (Johnson, Thomson & Speakman 2001). Large interspecific variation in physiological traits suggests that the intrinsic metabolic ceiling may vary among species and may be reached at about 4 × RMR in kittiwakes, close to the limit suggested by Drent & Daan (1980). However, recent studies put doubt on a strong association between RMR and DEE both among individuals (Speakman et al. 2003) and within (Bech et al. 2002) and among species (Ricklefs, Konarzewski & Daan 1996), which suggests that the metabolic scope may not be a suitable measure of energetic limitation.

Our results contrast earlier studies on energy expenditure in kittiwakes, which indicated a flexible energy budget in this species (Kitaysky et al. 2000; Jodice et al. 2006). Comparing DEE between 2 years at two different colonies, Jodice et al. (2006) found evidence for an extrinsic limitation of DEE by food availability in female kittiwakes. In a similar study, Kitaysky et al. (2000) reported an opposite effect: DEE seemed to be elevated when food was scarce. This was interpreted as a forcing effect with birds compensating for poor food availability by increasing their foraging effort. In contrast to our data, previous studies also indicated a difference in metabolism between parents raising one or two chicks (Golet, Irons & Costa 2000; Jodice et al. 2006) suggesting increased energetic effort in parents with larger broods and hence an extrinsic limitation of DEE. One explanation for these diverging results may be connected to the geographic location of study sites. The proximity of our study colony to the northern limit of the breeding range may be associated with increased energetic costs, e.g. by low ambient and/or sea temperatures (Bryant 1997; Humphreys, Wanless & Bryant 2007). This may reduce their energetic flexibility and push them close to an intrinsic energetic ceiling. Another reason may be related to differences in the timing of DEE measurements in relation to the breeding cycle. Fyhn et al. (2001) demonstrated that kittiwakes increase their DEE from early to late chick-rearing. We measured energy expenditure during late chick-rearing, thus individuals may have been more constrained in their energy budget than during earlier stages, and this may explain contrasting results among different studies (e.g. Kitaysky et al. 2000).

Although our data seem to be best explained by an intrinsic limitation of DEE, without further evidence for the proximate causes of this limitation, this interpretation must remain tentative. Clearly, experimental studies are needed to explore the nature of the apparent metabolic ceiling and its implications for the ecology of the species.

Our data indicate that in kittiwakes at high latitudes parental effort in terms of energy expenditure may be fixed. This may at least partly explain why kittiwakes, in contrast to other seabird species (e.g. Harding et al. 2007), seem to be less able to buffer chicks against stochastic variability in breeding conditions, thus leading to large inter-annual variation in breeding success in this species (Frederiksen et al. 2005; Piatt et al. 2007). However, the lack of flexibility in energy expenditure may not necessarily imply that kittiwakes have a fixed level of parental investment (Bryant 1988; Tinbergen & Verhulst 2000). While there was no variation in DEE, body mass differed considerably among groups. Mean body mass was up to 12% higher during favourable years (e.g. 2007) compared to poor years (e.g. 2006). Body mass also differed with respect to brood size, with parents raising two chicks weighing significantly less than birds with singletons. This suggests that in some years birds may not have been in energy balance during the chick-rearing period. Hence, the amount of energy expended during unfavourable years, and perhaps also to rear larger broods, may not be sustained by energy intake but may partly be subsidized by utilization of body reserves (Costa 2008). Kittiwakes seem therefore to some extent be able and willing to increase their parental investment and absorb some of the costs of poor foraging conditions by reducing their allocation to self-maintenance (Erikstad et al. 1998). Costs of reduced allocation to self-maintenance, however, may have been small as we did not find an association between body mass and the return rate of adult birds.

A reduction in body mass during unfavourable years may help kittiwakes to adjust their energy budget by two different processes. First, lower body mass is associated with reduced energetic costs of flying (e.g. Norberg 1996), which may allow birds to allocate more energy to foraging activity with no increase in total DEE. Second, a reduction in body mass in kittiwakes during chick-rearing is associated with a disproportionately large mass loss of kidneys and especially the liver (Langseth et al. 2000; Bech et al. 2002) and a decrease in metabolic intensity of these organs (Rønning et al. 2008). This down-scaling of internal organs leads to a decrease in RMR during the breeding cycle (Bech et al. 2002). Assuming an additive model for the relationship of RMR and DEE (partitioned pathways model, Ricklefs et al. 1996), modification of their RMR may enable kittiwakes to allocate a flexible amount of energy to activity. Hence, kittiwakes may adjust their energy budget in response to extrinsic factors not by adjusting their total energy expenditure, which may be intrinsically limited, but by reducing their basal metabolic costs.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We are indebted to S. Christensen-Dalsgaard, I. Dorresteijn, E. Noreen and K. Lye for their help in the field, and the staff of the Sverdrup Station (Norwegian Polar Institute) in Ny-Ålesund, especially W. Moskal, for logistic support. Many thanks to P. Thomson and P. Redman for technical assistance with isotope analysis. J.W., J.S. and G.W.G. were supported by the Research Council of Norway (MariClim, 165112/S30) and Svalbard Science Forum. The research during 1997–1998 was funded by the Research Council of Norway (Arctic Light and heat, 112871/720). We thank A. Harding, R. Ims and three anonymous referees for helpful comments on an earlier draft of the manuscript. All fieldwork was conducted with the permission of the Governor of Svalbard.

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  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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