Body condition in Svalbard reindeer and the use of blood parameters as indicators of condition and fitness

1566 Body condition in Svalbard reindeer and the use of blood parameters as indicators of condition and fitness Jos M. Milner, Audun Stien, R. Justin Irvine, Steve D. Albon, Rolf Langvatn, and Erik Ropstad Abstract: Body condition is an important determinant of ecological fitness but is difficult to measure in field studies of live animals. Live mass and subcutaneous fat are often used as proxies for body condition and related to fitness. We investigated the relationship between blood-chemistry parameters and live mass and back-fat thickness and assessed their usefulness as predictors of ecological fitness in a wild arctic ungulate population, Svalbard reindeer (Rangifer tarandus platyrhynchus). Female reindeer were sampled in late winter between 1995 and 2002 and concentrations of blood parameters were related to subsequent survival and successful calving. There was marked annual variation in all blood parameters, live mass, and back-fat thickness, reflecting variation in weather and food availability. At the individual level, variation in blood-parameter concentrations was not closely related to variation in live mass or back-fat thickness, instead reflecting shorter term nutritional status. Blood parameters could therefore provide useful additional information, enhancing the predictive power of fitness models based on live mass. The urea:creatinine ratio significantly improved adult survival models, while β-hydroxybutyric acid and creatinine concentrations were significant predictors of calving success. The applications for blood parameters in ecological investigations look promising and should be tested more widely in other field studies. Résumé : La condition physique est un important facteur déterminant du fitness écologique, mais elle est difficile à évaluer en nature chez des animaux vivants. La masse vive et la graisse sous-cutanée dorsale servent souvent de mesures de remplacement et elles sont alors mises en relation avec le fitness. Nous avons déterminé la relation entre les paramètres chimiques du sang, d une part, et la masse vive et la graisse sous-cutanée dorsale, d autre part, et évalué leur utilité comme variables prédictives du fitness écologique chez une population sauvage d ongulés de l Arctique, les rennes de Svalbard (Rangifer tarandus platyrhynchus). Des prélèvement effectués chez les femelles en fin d hiver de 1995 à 2002 ont permis de relier les concentrations des paramètres sanguins à la survie subséquente et au succès de la mise bas. Il y a, au cours de l année, une importante variation de tous les paramètres sanguins, de la masse vive et de la graisse dorsale qui reflète les changements du climat et de la disponibilité de nourriture. Au niveau de l individu, la variation des paramètres sanguins n est pas fortement reliée aux variations de la masse vive ni de la graisse dorsale; elle reflète plutôt le statut nutritionnel à court terme. Les paramètres sanguins peuvent donc fournir des renseignements additionnels qui permettent d améliorer le pouvoir de prédiction des modèles de fitness basés sur la masse vive. L addition du rapport urée:créatinine améliore de façon significative les modèles de survie des adultes, alors que les concentrations d acide β-hydroxybutyrique et de créatinine sont des variables prédictives significatives du succès de la mise bas. L utilisation des paramètres sanguins dans les études écologiques semble donc prometteuse et devrait être évaluée sur une plus grande échelle dans d autres recherches en nature. [Traduit par la Rédaction] Milner et al. 1578 Introduction Body condition encompasses aspects of individual quality such as health, competitive ability, and nutritional status, and is consequently an important determinant of ecological fitness. Although rarely defined explicitly, body condition generally refers to the size of energy stores, such as fat or protein reserves, but these are difficult to measure in live animals (Green 2001). Few studies have therefore been able to demonstrate directly the relationship between energy reserves and fitness in live animals (but see Newton 1993; Atkinson and Ramsay 1995; Gerhart et al. 1997; Keech et al. Received 25 February 2003. Accepted 13 August 2003. Published on the NRC Research Press Web site at http://cjz.nrc.ca on 10 October 2003. J.M. Milner, 1,2 R.J. Irvine, and S.D. Albon. Centre for Ecology and Hydrology, Hill of Brathens, Banchory, AB31 4BW, U.K. A. Stien. Department of Biology, University of Tromsø, N-9037, Tromsø, Norway. R. Langvatn. University Centre on Svalbard (UNIS), N-9170, Longyearbyen, Norway. E. Ropstad. Norwegian College of Veterinary Medicine, Ullevålsveien 72, P.O. Box 8146, N-0033, Oslo, Norway. 1 Corresponding author (e-mail: jos.milner@sue.hihm.no). 2 Present address: Hedmark University College, Evenstad, NO 2480, Koppang, Norway. Can. J. Zool. 81: 1566 1578 (2003) doi: 10.1139/Z03-152

Milner et al. 1567 2000). Instead, body mass, a composite of condition and body size, is often used as an indicator of condition, and numerous studies have shown it to influence survival (e.g., King et al. 1991; Festa-Bianchet et al. 1997; Milner et al. 1999) and reproductive success (e.g., Gaillard et al. 1992; Festa-Bianchet et al. 1998; Clutton-Brock et al. 1996; Overdorff et al. 1999). Many other studies, across a range of taxa, have demonstrated relationships between bodycondition indices and fitness parameters (e.g., Wauters and Dhondt 1995; Bonnet and Naulleau 1996; Civantos and Forsman 2000). However, condition indices based on external morphology, such as mass:length ratios or residuals from regressions of length on mass, though widely used, are often flawed because of imperfect correlations and nonlinear relationships between variables (Green 2001; Hayes and Shonkwiler 2001). Furthermore, the choice of methods used to calculate indices may lead to different conclusions being drawn (Hayes and Shonkwiler 2001). The thickness of subcutaneous back fat is a measure of body condition that has often been used in cervids (Langvatn 1977), and is also a useful and accurate predictor of total fat in a variety of domestic and wild ruminants (e.g., Berg and Butterfield 1976; Reimers and Ringberg 1983; Stephenson et al. 1998; Cook et al. 2001). However, back fat is not easy to measure in live animals and is often based on subjective evaluations (Gerhart et al. 1996b), although technological advances have made the use of ultrasound scanning a viable alternative (Stephenson et al. 1998; Starck et al. 2001; Stien et al. 2002). Blood- and urine-chemistry parameters provide an alternative method of assessing the condition of individuals. This method is commonly used in human and veterinary medicine, but is seldom used in ecological studies of wild ungulates (but see Warren et al. 1982; DelGiudice et al. 1990, 1991; Cook et al. 2001; Säkkinen et al. 2001). However, blood- and urine-chemistry parameters differ from body mass and back-fat thickness as indicators of nutritional condition. While body mass and back-fat thickness reflect an animal s nutritional status over the previous weeks and months, blood- and urine-chemistry parameters may respond to the animal s physiological state in minutes. In addition, the concentrations of the different substances in the blood are generally strictly regulated by complex physiological mechanisms that may only allow individuals under extreme stress to be identified. Although the relationship between some serum- and urine-chemistry indices and body condition has been assessed for elk (Cook et al. 2001), the potential for most blood parameters to be used as indicators of future fitness of ungulates in the wild has not been evaluated. Northern ungulates are adapted to wide seasonal variation in food availability and quality. They show various behavioural, morphological, and physiological responses to periodic undernutrition, such as reduced metabolic rates in winter, cyclical deposition and mobilization of lipid reserves, and, under severe nutritional restriction, use of endogenous protein as an alternative energy source (Nilssen et al. 1984; Gerhart et al. 1996a). Arctic ungulates such as reindeer and caribou (Rangifer tarandus) occur at the northern limit of terrestrial life and, as a consequence of the extreme environment, the relationship between their condition and fitness might be expected to be particularly pronounced. Svalbard reindeer (Rangifer tarandus platyrhynchus) have unusually large fat reserves in autumn (Reimers et al. 1982; Tyler 1987a) and show seasonal changes in body mass of 40% 55%, which are unparalleled among ungulates (Reimers and Ringberg 1983). However, their fat reserves can only provide a maximum of 25% of their winter energy expenditure (Tyler 1987a). The remainder must be provided by the diet, which is dominated by poor-quality fibrous vascular plants (Mathiesen et al. 2000), or through catabolism of body protein (Reimers et al. 1982; Adamczewski and Hudson 1993). In some years, extreme winter conditions cause severe malnutrition and starvation, leading to the dieoff of a high proportion of individuals (Reimers et al. 1982; Aanes et al. 2000; Solberg et al. 2001), followed by extremely low summer calving success. This has important consequences for the dynamics of Svalbard reindeer populations (Reimers et al. 1982; Solberg et al. 2001; Albon et al. 2002). In this study we investigated whether blood-chemistry parameters could be used to evaluate late-winter body condition and predict future fitness in wild female reindeer on Svalbard. Our first aim was to describe the annual variation in a range of blood parameters that are potential indicators of condition, taking into account age and pregnancy status. Secondly, we assessed how these parameters relate to conventional measures of body condition by exploring their relationship with live mass and subcutaneous back-fat thickness in live animals. Finally, we assessed the usefulness of these parameters as predictors of future fitness at the individual level, particularly survival to the end of winter and successful calving in the subsequent summer. Methods Study area and reindeer population The study was carried out in the Colesdalen Semmeldalen Reindalen valley system of Nordenskiöldland, Spitsbergen (77 50 78 20 N, 15 00 17 30 E), which has a population of about 1500 reindeer (Environmental Department, Governor of Svalbard s Office). Approximately 25% of the females were marked with individually numbered ear tags (Allflex Europe (U.K.) Ltd., Hawick, U.K.) and neckmarker straps fitted with numbered sleeves (Dalton Supplies Limited, Henley-on-Thames, U.K.). Of these individuals, many were known-age animals, particularly in the latter years of the study. Marked adults and female calves were caught by net from snow-scooters, weighed, measured, and blood-sampled in late winter (late April early May) each year between 1995 and 2002 (Albon et al. 2002; Stien et al. 2002). Captured reindeer were restrained by hand without using sedatives or medication. Blood samples were collected from the jugular vein with evacuated heparinized tubes (Venoject, Leuven, Belgium). Live body mass was measured using a spring balance (100 0.5 kg; Salter Industries, West Bromwich, U.K.). Since 1998, subcutaneous back fat on the rump has been measured using a real-time portable ultrasound scanner (Scanner 100 linear, 5-MHz transducer, Pie Medical, Maastricht, the Netherlands) with the animals in lateral recumbency (Stien et al. 2003). Fat layers less than

1568 Can. J. Zool. Vol. 81, 2003 about 4 mm thick could not be detected (Stien et al. 2003; see also Stephenson et al. 1998). Pregnancy status was determined by ultrasound scanning of the bare skin of the udder (Scanner 100, linear 3.5-MHz transducer, Pie Medical) and using the progesterone concentration in blood samples (Russell et al. 1998; Ropstad et al. 1999). Ultrasound diagnosis also allowed the status of the foetus (dead or alive) to be determined. However, the total number of individuals scanned was lower than the number diagnosed using progesterone (861 individuals compared with 1093), so for most analyses, pregnancy diagnosis was based on the latter. Total handling time was less than 20 min per individual. Mortality of any sampled individuals that occurred between April May and the summer (June August) was determined by the recovery of their carcass during summer censuses. These were carried out on foot, scanning for marked animals and carcasses with binoculars and telescope, between 25 June and 25 August each year. Survival was confirmed by subsequent live observations. The calving success of pregnant sampled animals was determined by the presence or absence of a calf accompanying a relocated sampled animal during the summer censuses. Peak calving occurred during the first 2 weeks of June (Tyler 1987b), so the timing of censuses allowed neonatal mortality to occur prior to the assessment of calving success. Svalbard is free from predators, so survival is largely dependent on food availability and weather, while fecundity is also regulated by parasites (Albon et al. 2002). Blood parameters and laboratory analysis Blood plasma was separated by centrifugation within 2 8 h and stored at 20 C prior to analysis. Plasma samples were analysed to determine the concentrations of various blood parameters including glucose, β-hydroxybutyric acid (β-ohb), asparate aminotransferase (AST), total protein, albumin, urea, and creatinine in all years from 1996 to 2002, except creatinine in 2000. Concentrations of cortisol and progesterone were also measured in each year between 1995 and 2002. Progesterone concentrations greater than 7 nmol/l were used as an indicator of pregnancy (Ropstad et al. 1999). Glucose and β-ohb, a ketone synthesized during fasting (Bruss 1989), are indicators of energy balance and carbohydrate metabolism. The blood glucose concentration is under strict hormonal control, but during fasting it decreases, triggering lipolysis and the subsequent formation of β-ohb (Kaneko 1989). Therefore, β-ohb is an indicator of increased fat breakdown. AST is an enzyme associated with the breakdown of muscle, but also indicates soft-tissue damage, especially in hepatic tissue (Kaneko 1989). Together, albumin and globulin account for most of the protein in the blood. Although globulin levels reflect the amount of immunoglobulins produced by the immune system rather than nutritional status, they are strongly correlated with albumin level. Albumin and total protein, as well as urea, are indicators of protein supply and its metabolism. Low levels of albumin and total protein indicate dietary-protein depletion and undernutrition, while high concentrations of urea may reflect an increase in protein catabolism associated with starvation (Kaneko 1989). Similarly, creatinine is an endproduct of muscle metabolism, and its concentration varies with muscle mass (Rodwell 2000). Both urea and creatinine are related to kidney function and the glomerular filtration rate, which decreases when protein intake is low. The urea:creatinine ratio has the effect of correcting the urea concentration for variation in the glomerular filtration rate (Säkkinen et al. 2001). Plasma glucose, β-ohb, AST, total protein, albumin, urea, and creatinine were analysed at the Central Laboratory, Norwegian School of Veterinary Science, Oslo. The analyses were performed on a Technichon Axon TM System (Bayer, Tarrytown, N.Y., U.S.A). Each specimen was analysed with appropriate use of control sera (Precinorm E, Boehringer Ingelheim Diagnostics, Indianapolis, Ind., U.S.A.; Seronorm TM, Sero A/S, Asker, Norway). During the period from 1995 to 1999, plasma progesterone was measured by ELISA kits utilizing an enhanced chemiluminescense technique (Amerlite, Kodak Clinical Diagnostics, Amersham, U.K. (Ropstad et al. 1999)). From 2000 onwards progesterone levels were determined by radioimmunoassay using a Spectra kit (Orion, Diagnostica, Espoo, Finland). The assay was done according to kit instructions and was validated with reindeer plasma by demonstrating parallelism between dilutions of plasma samples and the standard curve. The interassay coefficients of variation for samples with 1.25, 19.13, and 44.1 nmol/l were 8.8%, 7.6%, and 5.9%, respectively. Plasma cortisol was measured by radioimmunoassay according to Simensen et al. (1978), with the following modifications: 20 µl of plasma was boiled in 500 µl of 0.75% trichloroacetic acid and 0.225% NaOH for 10 min. After adding antiserum and 3 H-cortisol, the sample was incubated for 1hatroom temperature, then overnight at 4 C. The phosphate buffer used for incubation contained 0.2% bovine serum albumin. The antiserum (No. F3 314) was obtained from Endocrine Science Products, Tarzana, Calif., U.S.A. The assay was validated for use with reindeer plasma by demonstrating parallelism between dilutions of plasma samples and the standard curve. Assay sensitivity was 2.48 nmol/l. The interassay coefficients of variation for samples with 13.4, 48.5, and 102.3 nmol cortisol/l were 9.6%, 6.2%, and 9.1%, respectively. Statistical analysis Between-year variation in blood parameters and measures of body size and condition was investigated using general linear models (McCullagh and Nelder 1989). Variation with respect to age and pregnancy was also investigated. Female Svalbard reindeer reach mature body size by about 3 years of age (Fig. 1a), but since there is relatively little difference in most blood parameters between 2-year-olds and older individuals (see Fig. 1) and these animals are difficult to distinguish in the field, 2-year-olds were pooled with fully grown adults. In most analyses, older adults (aged 7 years and over) were not distinguished from other adults because many were individuals of unknown age, giving only a small sample of known-age old females (75 captures in total). To determine the effectiveness of blood parameters as fitness predictors, logistic regression analysis was used to fit a probability curve through the binomially distributed survival data (0 died, 1 survived) and calving data (0 calf not observed, 1 calf survived) using the logit link function (McCullagh and Nelder 1989). For the survival analysis, only animals with known survival outcomes from capture

Milner et al. 1569 Fig. 1. Age-specific mean live mass (a), back-fat thickness (b), and plasma concentrations of β-ohb (c), glucose (d), AST (e), and creatinine (f) in female Svalbard reindeer (Rangifer tarandus platyrhynchus) in April May, averaged across years. Error bars show ±1 SE. Means for pregnant ( ) and nonpregnant ( ) females are plotted separately where there are significant differences.

1570 Can. J. Zool. Vol. 81, 2003 in April May to the subsequent summer (June August) were included, and for the calving analysis, only animals pregnant in April May with a known outcome of the subsequent calving were included. Blood parameters were fitted into survival and calving models, taking account of year, sampling date, pregnancy status, live mass, and back-fat thickness where necessary. Nonsignificant terms were sequentially dropped. Calving success showed a strong effect of year-to-year variation and so was remodelled using a generalized linear mixed model in which year was fitted as a random effect (McCullagh and Nelder 1989). β-ohb and AST levels were log e -transformed before analysis. Linear regression was used to correct for decreasing trends in back-fat thickness and creatinine concentration with sampling date (Säkkinen et al. 2001). Residuals from the fitted line were added to the value for the mean catch date, 25 April (fitted back-fat thickness = 17.03 0.3369 CD; fitted creatinine concentration = 205.81 1.237 CD, where CD is catch date in days from 1 April). Since glucose levels were affected by the stress of capture and handling, they were corrected for the effect of cortisol (an indicator of stress) by using a smoothing spline with 2 degrees of freedom to model the nonlinear relationship between these two blood parameters. Glucose concentrations were adjusted to a cortisol concentration of 2 ng/ml, associated with a lowstress situation. Results Variation in concentrations of blood parameters at the population level At the population level, a number of blood parameters could be used to identify years or groups of individuals in which average body condition was relatively good or poor, variation that was also well described by average live mass and back-fat thickness. There was highly significant betweenyear variation in all parameters measured (Table 1). The lowest mean body masses and glucose, total protein, and albumin concentrations and the highest β-ohb, urea, and AST concentrations (including five extreme values ranging from 416 to 1245 U/L) were all recorded in 1996, a year with severe winter conditions and relatively high mortality (Solberg et al. 2001; Albon et al. 2002). Similarly, there was high mortality in 2002 and most parameters showed their secondlowest values in that year (Table 1). By contrast, body masses, back-fat thickness, and glucose, total protein, albumin, and creatinine concentrations were, on average, highest and AST and β-ohb concentrations (only in pregnant females) were lowest in 2001, when mortality was also lowest. The strong covariance between years gave rise to high correlation coefficients for between-year variation between annual means of blood parameters, live mass, and back-fat measures (e.g., r > 0.7 between live mass and all bloodparameter concentrations except creatinine concentration (r = 0.40)). There was also significant variation in some parameters with respect to pregnancy status and age. Pregnant females were significantly heavier and had significantly thicker layers of back fat than nonpregnant animals (Table 1, Figs. 1a and 1b). However, with the exception of β-ohb, blood parameters did not vary significantly between pregnant and nonpregnant animals (Table 1). β-ohb was present at higher concentrations in pregnant than in nonpregnant females (Fig. 1c). Like nonpregnant females, calves and yearlings had little back fat compared with pregnant adults (Fig. 1b). While animals reached their maximum adult body mass at 3 years of age, most blood parameters had stabilized at adult levels in yearlings or 2-year-olds. Concentrations of all blood parameters except AST differed significantly in calves from those in yearlings and adults. Concentrations of glucose (F [1,983] = 8.49, P = 0.004; Fig. 1d), total protein (F [1,1007] = 38.19, P < 0.001), albumin (F [1,1009] = 120.24, P < 0.001), and creatinine (F [1,831] = 110.97, P < 0.001; Fig. 1 f ) were lower in calves than in adults, while concentrations of urea (F [1,1003] = 12.04, P < 0.001) and, when pregnancy was controlled for, β-ohb (F [1,1002] = 8.97, P = 0.003) were higher in calves. The difference was particularly marked for creatinine (Fig. 1 f ) and albumin concentrations. Within adults, significantly lower concentrations of glucose (F [1,320] = 13.18, P < 0.001; Fig. 1d), albumin (F [1,320] = 15.82, P < 0.001), and creatinine (F [1,264] = 6.13, P = 0.014; Fig. 1 f ) and significantly higher concentrations of AST (F [1,321] = 5.83, P = 0.016; Fig. 1e) were detected in adults aged 7 years or older than in prime-age (2 7 years old) adults. Old animals also had significantly less back fat than prime-age adults (F [1,242] = 5.21, P = 0.023; Fig. 1b). Relationship between blood-parameter concentrations and individual condition Within years and classes of animals, there was considerable individual variation in concentrations of blood parameters (Figs. 2 and 3). This variation was less closely related to back-fat thickness and live mass than was annual variation. Glucose concentration, while statistically significant, only explained 1.0% of the variation in back-fat thickness after variation due to year, pregnancy status, and sampling date had been accounted for (Fig. 2a). Similarly, log e β-ohb concentration explained only 4.5%, albumin concentration 3.4%, and log e AST concentration 3.2% of variation, while total protein, urea, and creatinine concentrations explained no significant variation in back-fat thickness (Fig. 2). However, a large proportion of the adults sampled (31%) had back-fat thickness less than the detection limit of the ultrasound equipment (~4 mm), yet had a wide range of bloodparameter concentrations, including individuals with extreme values (Fig. 2). This suggested that blood parameters were more sensitive than back-fat thickness to variation in body condition among poor-condition animals. Back-fat thickness was strongly related to live mass (explaining 17% of the variation in live mass after between-year variation was controlled for), but again the blood-parameter concentrations explained little variation. Albumin, total protein and urea concentrations, all indicators of protein metabolism, explained only 5.9%, 2.6%, and 2.5% of the variation in live mass, respectively, once variation due to year and pregnancy were controlled for. No other parameters showed a significant relationship with live mass (Fig. 3). Blood-parameter concentrations as fitness predictors Of the adults caught in April May that were subsequently resighted or found dead in the summer (n = 629), only 11 died during the latter part of the winter (5 in 1996 and 6 in

Milner et al. 1571 Table 1. Between-year variation in fitness measures, live mass, back-fat thickness, and plasma concentrations of glucose, β-ohb, AST, total protein, albumin, urea, and creatinine measured in April May, for adult female Svalbard reindeer (Rangifer tarandus platyrhynchus) aged 2 years or older. 1995 1996 1997 1998 1999 2000 2001 2002 Pregnancy rate (%)*** 65.0±7.6 (40) 64.9±5.6 (74) 87.7±3.7 (81) 92.1±2.3 (140) 88.5±2.8 (131) 66.4±4.5 (113) 91.7±3.0 (84) 56.8±4.7 (111) Survival rate (%)*** 100.0±0 (34) 92.6±6.9 (68) 100.0±0 (78) 100.0±0 (134) 100.0±0 (121) 100.0±0 (90) 100.0±0 (59) 86.7±11.8 (45) Successful calving (%)*** 85.0±13.4 (20) 7.7±7.7 (13) 87.5±11.3 (32) 90.5±8.7 (74) 89.9±9.2(79) 64.1±23.6 (39) 86.5±12.0 (37) 25.0±19.6 (24) Live mass (kg)*** Nonpregnant 46.4±0.8 (14) 36.9±0.8 (26) 43.8±1.3 (10) 48.3±1.4 (11) 50.7±0.9 (15) 45.6±0.7 (38) 52.4±1.4 (7) 40.3±0.6 (48) Pregnant 56.1±0.8 (26) 42.0±0.6 (48) 52.2±0.5 (71) 54.6±0.4 (129) 54.8±0.4 (116) 52.0±0.4 (75) 57.6±0.5 (77) 46.0±0.5 (63) Back-fat thickness (mm)*** Nonpregnant 6.3±2.4 (11) 12.8±1.4 (15) 3.0±1.1 (21) 18.5±2.5 (2) 0.6±0.4 (48) Pregnant 12.7±0.7 (127) 12.5±0.5 (110) 5.2±1.2 (33) 14.1±0.8 (60) 2.8±0.7 (63) Glucose concn. (mmol/l)*** 5.5±0.2 (74) 6.3±0.1 (69) 6.9±0.1 (143) 7.2±0.1 (131) 6.9±0.1 (113) 8.1±0.1 (84) 6.3±0.1 (111) β-ohb concn. (mmol/l)*** Nonpregnant 0.70±0.08 (26) 0.38±0.04 (8) 0.42±0.06 (11) 0.34±0.02 (14) 0.34±0.01 (38) 0.36±0.02 (7) 0.40±0.02 (48) Pregnant 1.27±0.17 (48) 0.80±0.08 (60) 0.65±0.03 (129) 0.62±0.03 (116) 0.70±0.04 (75) 0.57±0.02 (77) 0.79±0.09 (63) AST concn. (U/L)*** 153.1±22.1 (74) 127.2±5.6 (69) 128.6±3.6 (143) 132.7±3.5 (131) 143.1±3.6 (114) 118.4±4.1 (84) 149.9±5.6 (111) Total protein concn. (g/l)*** 51.6±0.5 (73) 56.3±0.4 (69) 57.2±0.3 (143) 57.3±0.4 (131) 55.0±0.4 (114) 58.2±0.4 (84) 51.9±0.4 (111) Albumin (g/l)*** 31.2±0.3 (73) 35.5±0.3 (69) 35.7±0.2 (143) 35.2±0.2 (131) 33.6±0.2 (114) 38.4±0.2 (84) 32.8±0.3 (111) Urea (mmol/l)*** 6.23±0.12 (74) 5.94±0.16 (69) 5.34±0.10 (143) 4.22±0.10 (131) 5.33±0.10 (114) 4.64±0.14 (84) 6.01±0.14 (111) Creatinine (µmol/l)*** 188.8±2.9 (73) 177.0±1.8 (69) 177.8±1.4 (143) 174.7±1.3 (131) 189.8±1.9 (84) 188.1±2.5 (111) Note: Pregnancy rates are based on progesterone concentrations. Rates of survival and successful calving were determined between April May and August (see the text). Values are given as the mean ± standard error, with the sample size in parentheses. The significance of between-year variation is shown (***, P < 0.001).

1572 Can. J. Zool. Vol. 81, 2003 Fig. 2. Relationship between back-fat thickness and plasma concentrations of glucose (a), β-ohb (b), albumin (c), urea (d), creatinine (e), and AST ( f ) in adult female reindeer aged 2 years and older, measured in April May, all years pooled. Pregnant ( ) and nonpregnant ( ) females had significantly different β-ohb concentrations. 2002; Table 1). Live mass was the best predictor of adult survival. However, animals with high urea concentrations, in addition to low live mass, had low survival probabilities. The urea:creatinine ratio was a better predictor than urea concentration on its own, and together with live mass explained approximately 46% of the total deviance in survival (Table 2, Fig. 4). Pregnancy status did not directly affect the probability of survival (χ 1 2 = 3.38, P = 0.07), although, on average, pregnant females had higher body masses (Table 1) and consequently better survival probabilities. Pregnant females also had more back fat than nonpregnant females, but back-fat thickness was not significantly related to survival (P > 0.05; Table 2). No other blood parameters were related to survival (P > 0.05; Table 2). The percentage of pregnant females that calved successfully varied between years from 8% in 1996 to 91% in 1998 (Table 1; see also Albon et al. 2002). Similar between-year variability was noted from summer helicopter counts conducted in seven valleys, including the study area, over the same time period (Environmental Department, Governor of Svalbard s Office). Once the random between-year variation had been controlled for, the best predictors of successful calving were live mass and log e β-ohb and creatinine concentrations (Table 3). Females that calved successfully were significantly heavier and had higher β-ohb and lower creatinine concentrations in late winter than those that lost their calves (Fig. 5). The low β-ohb concentration associated with unsuccessful calving was also evident in the subsample of pregnant females that were carrying a dead foetus in late winter (17 of 36 pregnant females scanned using ultrasound in 1996, 2 of 60 in 1997, and 5 of 62 in 2002). These individuals had β-ohb concentrations similar to those found in nonpregnant females (Fig. 6). No other blood-parameter concentrations differed significantly between females carrying a live and a dead foetus. The between-year variation in calving success covaried with mean annual live mass, calving success being lower in years of low average body mass. The total model explained 40% of the deviance in calving success, of which the fixed-effect variables explained 14%. Although back-fat thickness did not explain any significant variation in calving success (Table 3), an index for the presence or absence of fat and its interaction with live mass were significantly related to the probability of successful calving (χ 2 2 = 3.39, P = 0.034) in a model based on the 4 years in which data were available for both back-fat thickness and creatinine concentration. There was no significant year effect, so a conventional logistic regression model was used. Females with no fat had lower

Milner et al. 1573 Fig. 3. Relationship between live mass and plasma concentrations of glucose (a), β-ohb (b), albumin (c), urea (d), creatinine (e), and AST (f) in adult female reindeer aged 2 years and older, measured in April May, all years pooled. Pregnant ( ) and nonpregnant ( ) females had significantly different β-ohb concentrations. calving success, but as live mass increased, the probability of successful calving increased more steeply in these animals than in animals with fat. Discussion The blood parameters measured in this study showed similar patterns between years in their average concentrations, suggesting that they could all be used to monitor betweenyear variation in body condition at the population level. However, average values of the simple measure live mass followed the same pattern and provide a more straightforward means of assessing population condition. The value of using blood parameters appears to be in explaining additional variation in fitness at the individual level, over and above that which can be explained by live mass. Blood metabolites, particularly glucose, urea, β-ohb, and, to a lesser extent, proteins, reflect short-term nutritional status, whereas individual condition measured by body mass or back-fat thickness reflects nutritional supply in the previous weeks or months (Cook et al. 2001). The relationships between the blood parameters and back-fat thickness and live mass were weak within years, but if they are measuring different states, this is perhaps not surprising. Furthermore, blood parameters are regulated within a relatively narrow range (Kaneko 1989) and are only likely to show a response to starvation when an animal reaches a very high level of nutritional stress, whereas body mass and back-fat thickness change continuously as an animal approaches such a state. Blood parameters are therefore likely to be useful for detecting individuals that have already reached a critical nutritional state. Measurements of back-fat thickness are of little use at this end of the condition distribution, since individuals in very poor condition have no detectable back fat (Stephenson et al. 1998, 2002; Cook et al. 2001; see also Stien et al. 2003). The blood parameters investigated in this study were those that could reflect nutritional status (urea), energy (glucose and β-ohb), and protein metabolism (albumin, total protein, and urea), and liver (AST) and kidney (urea and creatinine) function. Liver-function parameters were included because the liver is where most metabolic processes take place, while kidney function, particularly the filtration rate, is also indicative of individual condition. In general, the range of bloodparameter concentrations we measured broadly agrees with other published data for reindeer and caribou in late winter (Hyvärinen et al. 1975; Larsen et al. 1985a, 1985b; Bubenik et al. 1998; Säkkinen et al. 2001) and expectations from domestic ruminants (Kaneko 1989). However, annual variation was marked and revealed suboptimal concentrations in some years. Although average glucose concentrations were above levels indicative of hypoglycaemia (concentrations below

1574 Can. J. Zool. Vol. 81, 2003 Table 2. Factors explaining variation in the survival of adult female reindeer (aged 2 years and older; n = 489), with logistic regression parameter estimates and standard errors. Term df deviance P Estimate SE Intercept 1 1.28 2.66 Live mass 1 29.4 <0.001 0.24 0.06 Urea:creatinine ratio 1 18.7 <0.001 0.15 0.04 Pregnancy 1 3.38 0.07 1.77* 1.01 log(ast concn.) 1 2.51 0.11 1.07 0.67 Total protein concn. 1 1.12 0.29 0.09 0.08 Year 5 5.10 0.40 Glucose concn. 1 0.56 0.45 0.19 0.25 Albumin concn. 1 0.55 0.46 0.10 0.14 log(β-ohb concn.) 1 0.16 0.68 0.20 0.49 Back-fat thickness 1 0.34 0.56 0.07 0.13 Note: Only significant terms (shown in boldface type) were included in the final model. P values were estimated by assuming the change in deviance ( deviance) caused by including the term, and followed a χ 2 distribution. deviance for nonsignificant terms was calculated as the change from the best fit model (shown in boldface type). Total deviance was 105.2. *Estimated change in log(odds) from nonpregnant to pregnant animals. Fig. 4. Observed relationship between urea:creatine ratio and live mass in adult females that survived ( ) and died ( ) between late winter and summer, together with lines showing the survival probabilities predicted by the model. 4 mmol/l), some individuals were hypoglycaemic in poor years. The mean total protein concentrations measured in the best years, although comparable to those measured in Finnish reindeer herds (Hyvärinen et al. 1975), corresponded to the lower range found in domestic ruminants (Kaneko 1989), and decreased a further 20% in bad years. Since plasma proteins are carriers of essential nutrients, hormones, and metabolites and are used as nutrients themselves, we might have expected proteins such as albumin to be more closely related to fitness parameters. Concentrations of the liver enzyme AST indicated that there was some change in liver function or liver damage associated with malnutrition

Milner et al. 1575 Table 3. Fixed effects explaining variation in successful calving by adult females (aged 2 years and older) diagnosed as being pregnant in spring (n = 259), with mixed-effects logistic regression parameter estimates and standard errors. Term Wald s statistic df P Estimate SE Intercept 5 1.43 3.03 Live mass 14.10 250 <0.001 0.18 0.05 log( -OHB concn.) 10.28 250 0.002 1.68 0.52 Creatinine concn. 6.96 250 0.009 0.035 0.013 Glucose concn. 2.03 247 0.16 0.30 0.21 log(ast concn.) 0.86 249 0.35 0.64 0.69 Total protein concn. 1.41 249 0.24 0.06 0.05 Albumin concn. 0.75 249 0.39 0.09 0.10 Urea concn. 0.80 249 0.37 0.15 0.17 Back-fat thickness 0.50 195 0.48 0.03 0.04 Note: Only significant terms (shown in boldface type) were included in the final model and the other variables were evaluated by adding them to this model. P values were estimated by assuming that Wald s statistic followed a F [1] distribution. The estimated variance component for the random year effect in the final model was 2.39. Fig. 5. Predicted probability of successful calving in relation to live mass and β-ohb concentration in adult female reindeer diagnosed in late winter as being pregnant. or starvation in reindeer in some years. The mean AST concentrations in bad years were comparable to ketotic levels recorded in dairy cows (Ropstad et al. 1989). The fact that these blood parameters were unrelated to survival or calving success indicates that Svalbard reindeer are well adapted to huge annual fluctuations in protein supply. The reduced concentrations of glucose, albumin, and creatinine and elevated levels of AST detected in blood samples from adults aged 7 years and older suggest that older animals were in poorer condition. Poor nutrition in this age class may be due to tooth wear and the indirect effects of being less able to compete for good feeding sites. The blood parameters that differed in concentration between older and prime-aged adults reflected a more catabolic metabolism among the relatively undernourished older adults. Live mass was a good predictor of both adult survival and successful calving, as expected from numerous field studies of ungulates (e.g., Gaillard et al. 1992; Jorgenson et al. 1993; Clutton-Brock et al. 1996; Festa-Bianchet et al. 1998). However, because blood parameters measure something

1576 Can. J. Zool. Vol. 81, 2003 Fig. 6. Concentration of β-ohb in adult females diagnosed by ultrasound as being not pregnant, pregnant with a live foetus, or pregnant with a dead foetus in April May. Sample sizes are shown for each class. Data from all years are pooled. slightly different, they have the potential to add information and predictive power. The adult-survival model was improved by including the urea:creatinine ratio. By using this ratio, urea concentration was corrected for variation in the glomerular filtration rate of the kidneys (Säkkinen et al. 2001). Elevated urea levels arising during periods of restricted food intake and low dietary protein content may result from energy intake being insufficient for rumen microbes to transfer nitrogen to protein or may be due to muscle catabolism. Such levels have been reported in both white-tailed deer (Odocoileus virginianus, Warren et al. 1982) and reindeer (Säkkinen et al. 2001). Increased urea concentrations in April May probably reflect very serious malnutrition followed by the breakdown of body proteins required for the maintenance of life. Concentrations of β- OHB, associated with fat breakdown, were generally highest under the most nutritionally stressful conditions, such as those occurring during pregnancy and in the severest winters, but high β-ohb concentrations were not indicative of mortality. It has been suggested that the production of β- OHB during fasting may have evolved as a survival mechanism (Bruss 1989). After live mass was accounted for, calving success was best predicted by the plasma concentrations of β-ohb and creatinine. Contrary to expectation (see above), the probability of successful calving increased with the β-ohb concentration. We speculate that the significantly higher β-ohb concentrations in females that produced a viable calf might reflect a greater maternal investment in the foetus. Calving success showed greater variation between years than did survival. This is what would be expected from the general observation that, in ungulate populations, adult females show little year-to-year variation in survival and moderate variation in fecundity (Gaillard et al. 2000). The greater fat depth we observed in pregnant than in nonpregnant females agrees with the findings of Tyler (1987a), Gerhart et al. (1997), and Keech (2000) for reindeer, caribou, and Alaskan moose (Alces alces), respectively, and suggests that reproductive success is related to body condition during the autumn rut (Cameron et al. 1993). Russell et al. (1998) also found that embryonic mortality early in pregnancy was higher in leaner, lighter female caribou. Similarly, maternal condition, measured by rump-fat thickness, influenced reproductive success in moose, with fatter animals having a higher probability of twinning, earlier birth dates, heavier offspring, and higher calf-survival rates (Testa and Adams 1998; Keech et al. 2000). In our study, back-fat thickness was more closely related to live mass than any other parameter, but consequently added little to the predictive power of fitness models that also included live mass. An index for presence or absence of back fat was nonetheless related to calving success, despite the relatively large number of individuals with little or no remaining subcutaneous fat in late winter. Few, if any, other studies have looked at the relationships between blood-parameter concentrations and ecological fitness. Our results show that while live mass is a good predictor of fitness for Svalbard reindeer, its predictive powers could be enhanced by using the concentrations of some blood parameters. Late-winter measures of back-fat thickness were less useful fitness predictors in this system, although in studies in less extreme environments, or at other times of the year, back-fat measurements have the potential to give added information. Our study is also unique in terms of the number of animals caught and sampled in the wild. Nonetheless, the sample size of animals not surviving the winter was small, so the robustness of our model predictions will require further validation. In studies where animals are caught and weighed, it is relatively easy to take a blood sample and the laboratory protocols for measuring these parameters are well established. We suggest that there may be useful applications for blood parameters in ecological investigations and these should be tested more widely in other field studies.

Milner et al. 1577 Acknowledgments We are grateful to the Governor of Svalbard for permission to work on Spitsbergen, and for the support of his environmental staff, particularly Jon Ove Scheie and Øystein Overrein. Essential logistical support and equipment was provided by the Norwegian Polar Institute and UNIS. Irma Oskam, Jan Lyche, Inge Engeland, and numerous volunteers provided assistance with the fieldwork. Their effort is greatly appreciated. Hanne Morberg, Stein Istre Thoresen, and the technical staff at the Central Laboratory, Norwegian School of Veterinary Science, analysed blood metabolites and Ellen Dahl analysed plasma progesterone and cortisol concentrations. The work was funded both by the Research Council of Norway (TERRØK program 1994 1996 and Arktisk Lys program 1996 1999) and the U.K. Natural Environment Research Council (1997 2000; GR3/10811). References Aanes, R., Sæther, B.-E., and Øritsland, N.A. 2000. 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