Blood Biochemistry Reflects Seasonal Nutritional and Reproductive Constraints in the Eurasian Badger ([ITAL]Meles meles[/ITAL])

450

Xavier Domingo-Roura1,2,3,*Chris Newman1Francesc Calafell3David W. Macdonald1IWildlife Conservation Research Unit, Department ofZoology, University of Oxford, South Parks Road, OxfordOX1 3PS, United Kingdom; 2Centre de Recerca Ecologica iAplicacions Forestals, Universitat Autonoma de Barcelona,08193 Bellaterra, Spain; 3Unitat de Biologia Evolutiva,Universitat Pompeu Fabra, Dr. Aiguader 80, 08003Barcelona, Spain

Accepted 1119101

ABSTRACT

Physiological responses to nutritional and reproductive con-straints were explored in a wild population of Eurasian badgers(Meles meles) inhabiting Wytham Woods, Oxfordshire, UnitedKingdom. We compared seasonal blood levels of lipid an.d pro-tein compounds to variables describing the sex, age, body con-dition, wounds, testes position, and flea abundance of the bad-gers. We found seasonal variations in albumin/globulins andurea/ creatinine ratios matched by differences in body condition.High creatinine, urea, and triglycerides levels were obtained inanimals in poor nutritional condition and with low levels ofbody fat. The maintenance of urea/creatinine ratios indicatesthat the badger does not demonstrate a stage of protein con-seNation in periods of food scarcity during the summer orperiods of cold weather. Hypercholesterolaemia, especially infat animals, was confirmed. We also offer baseline levels ofmetabolites commonly used in clinical biochemistry for theirfurther use in the analysis of the status and the managementof wild badger populations.

logi~.al, ecological, environmental, and demographic conditionsof natural populations ( Seal and Hoskinson 1978; Ferrer 1992) .In spite of the potential for using metabolic biochemical var-iables for monitoring wild and captive populations, their usehas been widely ignored in wild1ife management, and for mostspecies, there are no applied studies and not even referencevalues based on adequate sample sizes. This is the case for mostmustelid species, where only a few references are available (Jo-hansson 1957; Laplaud et al. 1980; Harlow and Nelson 1990;Harlow and Buskirk 1991).

The badger (Meles meles L.) is protected in the United King-dom and many other countries. Malnutrition and diseases affectits survival, social structure, and demography ( Cresswell et al.1992; Woodroffe and Macdonald 1995; Macdonald et al. 1999)and relate to both the role of badgers in the spread of diseases,such as bovine tuberculosis (Cheeseman et al. 1981; Mahmoodet al. 1988), and their use as a model for human physiopath-ological processes, such as arteriosclerosis (Laplaud et al. 1980).Monitoring badgers' health and nutritional status is importantto control and understand diseases in animals and humans andneeds to be considered in the management and conservationof its populations.

Badgers are temperate-region carnivores exposed to lowwin-ter temperatures and periods of food scarcity. Physiologicaladaptations to winter lethargy are evident in other temperatecarnivores, such as the black bear ( Ursus americanus L.; Nelsonet al. 1984). Reduced activity and temperatures below eu-thermic levels were recorded between October and March forbadgers in Scotland (Fowler and Racey 1988). Adipocyte li-polysis and body mass loss in the badger is ma:ximal duringwinter (Chraibi et al. 1982; Kruuk and Parish 1983). In ad-dition, both the gestation and mating periods occur in winter(Lindsay and Macdonald 1985; Fowler and Racey 1988). Femalebadgers rely heavily on stored fat during gestation and the initialstage of lactation ( Chraibi et al. 1982; Fowler and Racey 1988) .For these reasons, badgers offer an ideal model to test thehypothesis that, in species that maintain reproductive activity,winter physical inactivity is not matched by a metabolic slowingdown and a period of conservation of proteins.

The primary objective of this work is to identify the phys-iological consequences expressed as variations in blood bio-chemistry levels of seasonal fluctuations in food availability,winter inactivity, and seasonal reproductive cycles. We alsoidentify biochemical compounds that are useful to monitornutritional conditions in badgers and establish baseline bloodchemistry values for the studied badger population.

Introduction

Metabolic responses expressed as variations in blood chemistry

values can be used to detect changes in physiological, patho-

Correspondil:1g author; e-rnail: [email protected].

Physiological and Biochemical Zoology 74(3):450-460.2001. @ 2001 by The

University of Chicago. All rights rese!"ved. 1522-2152/2001n403-0021$03.00

Badger Blood Biochemistry 451

Material and Methods lysed for biochemical parameters using a Cobas Bio auto-

analyser (Roche) located at the Servei de Bioquímica Clínica

Veterinaria, U niversitat Autonoma de Barcelona. All assays were

conducted with commercial kits from Boehringer Mannheim.

Globulins were calculated as total proteins minus albumin. The

detection limit for hydroxybutyrate was 0.02 mmol/L, and sam-

pIes for which hydroxybutyrate levels were undetectable were

assigned a value of 0.01 mmol/L. Glucose levels were initially

obtained but were excluded from further analysis due to a

possible effect of the long-term storage of the samples on the

variability in levels of this metabolite. In addition, it is known

that excitability factors that could not be evaluated in this study

influence the levels of glucose in the blood (Franzmann and

LeResche 1978). No other metabolite showed any indication

of sample degradation due to long-term storage since no bio-

chemical variable measured in the laboratory showed lower

values for older samples (Table 2).The Kolmogorov-Smirnov test was used to check for nor-

mality in all continuously distributed variables. Stepwise re-

gression was used to decide (i) which length measurements

were significantly related to weight measurements and (ii)

which blood metabolite variables better explained nutritional

condition. Following Macdonald et al. (1999), the relationship

between length measures and weight was used to calculate a

condition index (RESCOND) based on each badger's standar-

dised residual deviation from a regression equation using

LNWEIGHT as the dependent variable and LNLENGTH,

LNPASTERL, and LNARCHW as independent variables (Table

1). The LN prefix indicates naturallogarithm. Simple factorial

ANOVA was used to evaluate the effect of age, sex, and season

on testes position (POSTEST) and on normally distributed

biochemical variables. Mann-Whitney and Kruskal-Wallis tests

were used for levels of flea infestation (FLEAS) and when bio-

chemical variables were not normally distributed. X2 tests were

conducted to evaluate the effect of age, sex, and season on

subcutaneous fat abundance (FATCOND), on testes position

(POSTEST), and on the three variables representing the pres-

ence and characteristics of wounds (WOUND, EXTWOUND,

and AGEWOUND). Depending on normality, either Pearson's

or Spearman's rank correlation coefficients were used to de-

scribe the correlation between biochemical values and RES-

COND and FLEAS. Simple factorial ANOVA and Kruskal- Wal-

lis tests were used to test the relationship that FATCOND,

POSTEST, and the extension of wounds (EXTWOUND) had

on biochemicallevels. The t-tests were used to compare the

levels of globulins between animals with or without wounds

(WOUND) and in animals whose wounds were fresh (with

open skin) or healed (AGEWOUND). Twenty animals were

captured in two different seasons, and six animals were collected

each season, although there were not enough recaptures of

particular individuals for the statistical analyses to be conducted

as paired observations. All tests were conducted using SPSS 7.5

The study was conducted in a Eurasian badger population in-

habiting Wytham Woods Estate, an area of 6 km2 located in

Oxfordshire, United Kingdom. The study site is an area of

woodland surrounded by farmland. Habitat characteristics in

relation to badger ecology are described in Kruuk (197~/l,

1978b) and da Silva et al. (1993).Traps baited with peanuts were sited before sundown at al1

of the active setts associated to each badger group, and each

site was trapped for three successive days. Starting at 7:00 A.M.

the following morning, badgers were collected from the traps

and brought to the nearby Wytham Field Station. Thirty-fivesamples (18 adult females [AF], 16 adult males [AM], one cub

female [CF]) were collected between August 1 and August 10,1996; 33 samples (15 AF, 11 AM, three CF, four cub males

[CM]) between November 5 and November 14, 1997, and 33

samples (13 AF, 14 AM, four CF, two CM) between May 25

and June 6, 1998. Among the 101 animals sampled, 87 were

adults and 14 cubs, and 54 were females and 47 males. We

collected animals from 31 different setts and sett outliers dis-

persed throughout Wytham Woods. Badger adult densities in

Wytham woodland were estimated as 39.0, 37.3, and 33.3 in-

dividuals/km2 for years 1996,1997, and 1998, respectively (D.

W. Macdonald and C. Newman, unpublished data).Between 8:00 and 11:00 A.M., badgers were anaesthetised

using 20 mg/kg body weight ketamine hydrochloride (Vetalar,Pharmacia and Upjohn), and all individuals on initi~l capture

were permanently marked with a tattoo on the inner left thigh

(Cheeseman and Harris 1982). Biometric data were collected

while the badger was anaesthetised. Blood samples were taken

from the jugular vein into a K2-EDTA (ethylene diamine tetra-

acetic acid) Vacutainer tube (Becton-Dickinson), refrigerated,and spun for 10 min at 2,500 rpm to separate plasma, within

a period of 30 min after collection. Plasma samples were frozen

at -20°C and stored until November-December 1998 when

laboratory analyses were conducted. Badgers were released at

the site of capture after full recovery from anaesthesia (>3 h).A temporary colour marker was dabbed on to badgers before

release so that if they were recaptured during the same trapping

season, they could readily be distinguished and released from

the trap without being reprocessed.Table 1 lists and explains all variables used in the analyses.

Biochemical variables include three compounds involved in

lipid metabolisIÍl ( cholesterol, hydroxybutyrate, and triglycer-

ides) and four nitrogenous compounds related to protein me-

tabolism (albumin, creatinine, globulins, and urea). These pa-

rameters were selected because they had been used in the past

to shed light on nutritional and health conditions in other wild

species {Franzmann and Schwartz 1988; Harlow and Nelson

1990), for being common and inexpensive tests in clinical bio-

chemistry of domestic animals, and for covering a wide range

of metabolic pathways (Káneko et al. 1997). Plasma was ana-

452 X. Domingo-Roura, C. Newman, F. Calafell, and D. W. Macdonald

Table 1: Variables used in the study and their method of determination

Kolmogorov.Smirnov

Values

Name Definition Type z p

NANANA

Discrete

Discrete

Discrete

Adult or cubFemale or maleSummer 1996, Autumn 1997, or Spring 1998

Basic variables:

AGE

SEX

SEASON

Morphological variables:

LNWEIGHT

LNLENGTH

LNPASTERL

LNARCHW

RESCOND

ContinuousContinuousContinuousContinuousContinuous

1.1871.379.856

1.417.909

.119

.045*

.457

.036*

.380

FATCOND Discrete 2.105 .000**

WOUNDEXTWOUNDAGEWOUNDPOSTEST

NA

NA

NA

1.327

Discrete

Discrete

Discrete

Discrete .059

LN of weight (kg)

LN of length from nose to beginning of tail (cm)

LN of rear paster left tarsus length (mm)

LN of zygomatic arch width (mm)

Standardised residual of equation 1 (see «Material and

Methods»)Body condition estimated as the presence of subcutaneous

fat palpating at the ribbons level from very thin ( = 1) to

very fat ( = 5)

Presence or absence of wounds

Extension of wounds: none, minor, moderate, or extensive

Age of wounds: fresh or healedPosition of the testes from very descended ( = 1) to very

ascended ( = 5)

Number of fleas found in body flak in a 20-s interval 2.327 .000**Discrete

ContinuousContinuousContinuousContinuousContinuousContinuousContinuousContinuousContinuousContinuous

1.150

1.007

.966

1.252

1.273

1.554

2.146

1.285

1.698

1.548

.142

.262

.309

.087

.078

.016*

.000**

.074

.006**

.017*

FLEAS

Biochemical variables:

ALBUMIN

CHOLESTEROL

CREATININE

GLOBULINS

HYDROXYBUTYRATE

PROTEINS

TRIGLYCERIDES

UREA

ALBUMIN/GLOBULINS

UREA/CREATININE

Colorimetric method of 6romocresol greenCholesterol oxidase-peroxidase colorimetric methodJaffé colorimetric method without deproteinisationProteins minus albuminD-3-hydroxybutyric acid dehydrogenase colorimetric methodTotal proteins using Biuret's colorimetric methodGlycerol phosphate oxidase-peroxidase colorimetric methodUltraviolet urease methodAlbumin divided by globu1insUrea divided by creatinine

Note. Kolmogorov-Smirnov test measures deviation from the normal distribution. LN = naturallogarithm; NA = not applicable.

.Significant at the 0.05 level.

..Significan\ at the 0.01 level.

(SPSS Inc., Chicago) fof Windows and were selected following

Sokal and Rohlf (1995).

LNWEIGHT = (1.768 x LNLENGTH)

+ (1.081 x LNARCHW) -14.296. (I)

The correlation coefficient for equation (1) was r = 0.728.

LNPASTERL did not contribute significantly to equation (1)

and was excluded from the analyses. However, LNPASTERLwas correlated to both LNWEIGHT (r = 0.540, p< 0.001,

N = 96) and LNLENGTH (rs = 0.734, p< 0.001, N = 87).

Confidence intervals for the regression parameters overlapped

for all three length measures for different AGE, SEX, and SEA-

Results

Using the 83 samples for which alllength and weight measures

were available, a regression equation describing the relationship

between weight and length measures was obtained:

Badger Blood Biochemistry 453

-0.271, p = 0.013), and the ALBUMIN/GLOBULINS ratio(rs = -0.245, p = 0.024) were correlated with RESCOND(N = 84 for all tests). LNWEIGHT (N = 98 for all tests)was correlated with GLOBULINS (r = 0.257, p = 0.011),PROTEINS (rs = 0.254, p = 0.012), TRIGLYCERIDES(rs = -0.355, p< 0.001), and the ALBUMIN/GLOBULINSratio (rs = -0.324, p = 0.001). FATCOND classes (N =

94 for all tests) differed significantly with the follow-ing biochemical parameters: CHOLESTEROL (F = 5.378,p = 0.001), CREATININE (F = 5.838, p< 0.001), TRI-GLYCERIDES (X2 = 9.917, p = 0.042), and UREA (F =3.798, p = 0.007; Fig. 4).

GLOBULINS were significantly different among animals de-pending on the wounds they had (EXTWOUND: F = 2.938,p = 0.038, N = 89). When comparing animals with versus

without wounds (WOUND), it became clear that the effect wasmainly due to lower levels of globulins in animals withoutwounds (t = -2.980, df = 87, p = 0.004; Fig. 5). When com-

paring AGEWOUND, there was no change in the levels ofglobulins between animals with fresh versus healed wounds(t = -0.020, df = 27, p = 0.985), although we had only six

animals with fresh wounds for comparisons.CHOLESTEROL and CREATININE were significantly dif-

ferent in males depending on the POSTEST (F = 6.860, p<0.001, N = 42 and F = 5.330, p = 0.002, N = 42, respec-

tively). However, this significance disappeared for both meta-bolic variables when the effect of POSTEST on biochemicallevels was analysed separately for each season.

SON classes. RESCOND represents the standardised residualsof this regression for all animals. FATCOND was positivelycorrelated with RESCOND (rs = 0.766, p< 0.001, N = 81) andLNWEIGHT (rs = 0.612, p< 0.00l, N = 92). Table 1 shows

which of the variables included in the analyses were normallydistributed.

Adu1ts and cubs had different values for GLOBULlNS (F r8.26, p = 0.005, N = 10l), PROTEINS (Z = -3.08, p =0.002, N = 10l), ALBUMIN/GLOBULlNS ratio (Z = -2.90,p = 0.004, N = 10l), and LNWEIGHT (F = 33.691, p<0.00l, N = 98; Fig. 1 ). Males and females had different valuesfor HYDROXYBUTYRATE (F = 6.31, p = 0.0l4, N = 10l; Fig.2). ALBUMIN/GLOBULlNS (X2 = 22.98, p< 0.00l, N = 10l)and UREA/CREATININE (X2 = 7.087, p = 0.029, N = 10l) ra-tios, FATCOND (X2 = 32.308, df = 8, p< 0.00l, N = 94), RES-COND (F = 3.18, p = 0.047, N = 84; Fig. 3), LNWEIGHT(F = 3.179, p = 0.046, N = 98), FLEAS (X2 = 8.802, p =0.0l2, N = 96), and POSTEST (F = 31.603, p< 0.00l, N = 42)

were different across seasons. There was an interaction betweenSEX and SEASON for ALBUMIN (F = 4.49, p = 0.0l4, N =

10l) and between AGE and SEASON for CHOLESTEROL(F = 6.75, p = 0.002, N = 10l). No other AGE, SEX, or SEA-

SON effect was detected in any other variable, and data for allother variables were pooled for all animals. Table 2 shows themeans and standard deviations of biochemical and conditionvariabtes including all animals and separated by significant dif-ferences found by ANOVA, X2, Kruskal-Wa11is, and Mann-Whitney analyses for AGE, SEX, and SEASON.

Stepwise regression was also used to describe the relationshipbetween RESCOND, FATCOND, and biochemical variables.Only CREATININE and total PROTEINS contributed signifi-cantly to predict RESCOND:

RESCOND = -(0.020 x CREATININE)

+ (0.031 x PROTEINS) -0.513, (2)

while a1l other biochemical variables were excluded from the

equation. However, both biochemical parameters could explainonly 21.0 % of the variance in RESCOND (r = 0.458, N =

84). Cho1esterol was included in the prediction of FATCOND

following the equation:

Discussion

The Effect of Starvation, Capture Stress, and Anaesthesia on

Blood-Biochemistry Levels

It is well known that daily rhythms, starvation, method of

capture and restraint, stress, and drugs can alter blood-bio-

chemistry profiles (Seal et al. 1972; Harlow and Buskirk 1991;

Harder and Kirkpatrick 1996). For this reason, our capture,

handling, and sampling procedures were as uniform as possible

throughout the experiment, as recommended in the literature

(Seal et al. 1972; Harder and Kirkpatrick 1996).

Badgers presumably had a large peanut meal when they en-

tered the traps, and the time that they remained in the traps

is comparable to food- and water-deprivation periods that mus-

telids encounter in their daily lives (Harlow and Buskirk 1991).

From research conducted in American martens (Martes amer-

icana), we expect the badger to be still catabolising glycogen

after this short period of starvation (Harlow and Buskirk 1991),

and food deprivation is unlikely to be a key factor in our results.

We found no information available on the effect ofketamine

and stress on blood-biochemistry levels ofbadgers or mustelids.

Research conducted in other species, mainly ungulates, shows

increases in cholesterol related to an increase in the output of

epinephrine and corticosteroids caused by stress (Franzmann

FATCOND = (0.301 x CHOLESTEROL)

-(0.021 x CREATININE)

+ (0.040 x PROTEINS) + 0.326, (3)

while all other biochemical variables were excluded from the

equation. The variance ofFATCOND predicted by this equationwas 21.6% (r = 0.465, N = 94).

In addition, CREATININE (r = -0.383, p< 0.00l),

TRIGLYCERIDES (rs = -0.221, p = 0.043), UREA (r =

Table 2: Values for biochemical and condition variables separated by basic variables

for which differences in mean values are statistically significant

xBiochemical Variable/Unit/Variable Division N Range SD

101

19

1&'

17

16

15

16

22.60-49.20

26.80-35.40

23.70-38.00

24.20-33.00

27.50-49.20

23.80-32.40

22.60-34.80

30.53

30.94

30.30

29.23

34.19

28.69

29.77

3.

2.

3.

2.

5.

2.

3.

101

34

26

27

1

7

6

2.62-9.14

2.62-7 .48

3.20-7.19

2.62-5.92

NA

3.86-5.94

3.51-9.14

4.23

3.96

4.77

3.67

3.67

4.69

5.49

1.12

1.08

.89

.71

NA

.69

2.01

101 30.06-141.4 75.06 21.33

101

87

14

13.70-62.10

13.70-62.10

20.10-38.00

35.85

36.78

30.10

8.11

8.20

4.49

101

54

47

.01-1.80

.01-1.71

.01-1.80

.45

.52

.38

.32

.34

.29

101

87

14

51.00-89.50

51.10-89.50

51.00-68.30

66.39

67.33

60.54

8.19

8.22

5.12

101 .48-5.72 1.28 .84

101 4.44-34.58 13.05 4.85

101

87

14

35

33

33

.41-3.59

.41-3.59

.80-1.54

.50-3.59

.49-1.29

.41-1.54

.91

.881.041.07.83.80

.34

.35

.21

.48

.14

.23

101

35

33

33

.069-0.479

.069-0.354

.093-0.402

.103-0.479

.182

.160

.197

.190

.072

.056

.071

.083

94

33

32

1.00-5.00

1.00-4.00

1.00-5.00

2.66

2.21

3.59

1.21

.93

1.16

ALBUMIN (g/L):SEX x SEASON

Females, summer 1996

Females, autumn 1997

Females, spring 1998

Males, summer 1996

Males, autumn 1997

Males, spring 1998

CHOLESTEROL (mmol/L):AGE x SEASON

Adults, summer 1996

Adults, autumn 1997

Adults, spring 1998

Cubs, summer 1996

Cubs, autumn 1997

Cubs, spring 1998

CREATININE (ILmol/L):

None

GLOBULINS (g/L):

AGE

Adults

Cubs

HYDROXYBUTYRATE (mmol/L):

SEX

Females

Males

PROTEINS (g/L):

AGE

Adults

Cubs

TRIGLYCERIDES (g/L):

None

UREA (mmol/L):

None

ALBUMIN/GLOBULINS:

AGE, SEASON

Adults

Cubs

Summer 1996

Autumn 1997

Spring 1998

UREA/CREATININE:

SEASON

Summer 1996

Autumn 1997

Spring 1998

FATCOND:

SEASON

Summer 1996

Autumn 1997

80

37

76

51

22

24

78

Badger Blood Biochemistry 455

Table 2 (Continued)

Biochemical Variable/UnitNariable Division N Range x SD

29 1.00-4.00 2.14 .95

84

31

27

26

-3.09-~

-3.09-]

-1.44-~

-1.54-]

.00

-.52

.62

-.02

.99

1.00

.91

.65

Spring 1998

RESCOND:

SEASON

Surnrner 1996

Auturnn 1997

Spring 1998

LNWEIGHT:

AGE

Adults

Cubs

98

84

14

2.07

2.13

1.71

.26

.20

.28

Note. NA = not applicable.

and Thorne 1970). Any relationship between hydroxybutyrate

levels and stress or anaesthesia is generally unknown. Urea is

known to be quite stable in stress conditions {Wesson et al.

1979; Marco and Lavin 1998), and creatinine levels are mainly

related to muscle activity. Creatinine levels could increase if the

animals become initially excited and mobile at the time of

trapping; however, by the time they are collected for processing,they are usua1ly still and subdued. Badgers are sensitive to sound

and human presence; thus, the hand1ing cages are covered with

a blanket, and processing is conducted in relative silence. Bad-

gers aJe nocturnal and, thus, would norma1ly be sleeping atthe time ofhand1ing and show no overt signs of distress. Protein

levels have been noted to increase in vertebrates in ielation to

stress {Laid1ey and Leatherland 1988; Marco and Lavin 1998).

In addition, it has been shown that chemical restraint can cause

a decrease in protein levels that could be due to modifications

in capillary permeability {Peinado et al. 1993). Additional re-

search will need to be conducted to get a further insight into

the effect of stress and anaesthesia in badgers resulting from

capture and sampling procedures.

leads to higher availability of earthworms on the soil surface,

the main and preferred food source of badgers in the United

Kingdom (Kruuk 1978a). Earthworms are rich in proteins andfat (Macdonald 1983) and are less available in summer, which

forces badgers to consume other foods (Kruuk 1978a). This

change in diet, depending on the availability of earthworms,

seems to influence and partially explain many of the biochem-

ical variations found in this study. A previous study in the same

badger population demonstrated an interannual variation infood supply related to August rainfall that had a major impact

on badger survival and reproduction (Woodroffe and Mac-

donald 2000).

Seasonal Effects on Body Condjtjon

Seasonal fluctuations in body weight mainly attributable to fat

abundance have been described in the badger (Laplaud et al.

1980; Kruuk and Parish 1983). Levels of body fat are related

to habitat quality, presence of earthworms in the habitat, and

reproductive capacity (Cresswell et al. 1992). In this study, wefound seasonal differences in biochemical variables associated

with seasonal differences in body condition indices (RESCOND

and FATCOND). Although both condition indices were cal-

culated from independent data, they were highly correlated and

showed similar profiles. Both demonstrate higher values in au-

tumn 1997, a period when rainfall was relatively high. Mean

rainfall ~uring the 30 d before the last day of trapping was 0.98

mm in summer 1996,1.51 mm in autumn 1997, and 1.64 mm

in spring 1998. In addition, 25.6 mm of rain was registered on

November 5, 1997, the first day of trapping. Increased rainfall

Lipids, Proteins, and Nitrogenous Compounds

Levels of hydroxybutyrate, a ketone body, were higher in fe-

males than in males. This could be due to differential degrees

of ketogenesis in males and females due to different levels of

lipolysis linked to physiological demands likely imposed by

different reproduction burdens. Pregnancy and lactation would

increase energetic demands on the female and promote lipol-

ysis. In this sense, female badgers might rely more than males

on lipolysis, which is promoted by hormonal changes, to secure

energy in extrahepatic tissues and so reduce protein breakdown.

We found no relationship between hydroxybutyrate levels and

body condition.

Different FATCOND classes were associated with significant

differences in cholesterol, creatinine, triglycerides, and urea

plasma levels. Cholesterol was different among FATCOND clas-

ses, mainly due to an increased level of cholesterol in fat animals

(Fig. 4). Badgers seem to be naturally hypercholesterolaemic

(Laplaud et al. 1980), and we found cholesterol mean values

were much higher than reference values for cats and dogs (Ka-

neko et al. 1997). In adult badgers, we found highest cholesterol

values in autumn. The levels of plasma lipid components, in-

cluding cholesterol, have been shown to reach an annual max-imum during the cold months in hibernating species as well

as in the badger, a species that does not hibernate but is less

1.02

1.11

~.02

.40

1.22-2.64

1.53-2.64

1.22-2.08

456 X. Domingo-Roura, C. Newman, F. Calafell, and D. W. Macdonald

50

--40=:

S(/) 30Z~~ 20mO-J~ 10

oCubsAdults

80

--:::E!(/)zw

bQ:o..

CubsAdults

,2

We found creatinine and proteins to be the best predictors

of body condition with a significant role in the prediction of

RESCOND. In addition, cholesterol was also included in the

equation to predict FATCOND. In both cases, just over 20%

of the variation in condition indices could be explained by

variations in biochemicallevels, indicating that there are other

p'hysiological and probably pathological variables influencing

the relationship between condition and biochemical levels.

CREATININE was also more negatively correlated than anyother biochemical variable (r = -0.383) with RESCOND, al-

though TRIGLYCERIDES, UREA, and ALBUMIN/GLOBU-

LINS were also negatively correlated.

Serum urea rises in response to the ingestion and catabolism

of proteins ( Owen et al. 1969) , whereas creatinine is not affected

by diet (Search 1969) but can be elevated during reducedkidney

function, as has been shown in the American badger ( Taxidea

taxus Waterhouse; Harlow and Nelson 1990). Animals in better

condition might be able to combine the use of body proteins,

which have a greater bound water content than fat, with fat

expenditure to enhance water balance (Harlow and Buskirk

1991) and maintain a normal glomerular-filtration rate. The

higher urea, creatinine, and triglycerides levels we found inanimals with negative RESCOND values and in lower FAT -

COND classes (Fig. 4) can be explained by a reduction in

g1omerular-filtration rate in these animals affecting these three

metabolites. Levels of triglycerides could also be related to the

time that has passed between the last trig1ycerides-rich meal

ingested and sampling time.

The urea/creatinine ratio has been described as an indicator

of the breakdown of proteins adjusted for urinary nitrogen loss

assuming constant g1omerular-filtration rate (Tietz 1976). Ureal

creatinine ratios were different across seasons, with low values

in summer 1996, a period of food scarcity due to drought in

the badgers' habitat. This couldindicate reduced catabolism of

I I

<nz::i~m 0,8O.J<.? 0,6-Z

~ 0,4~m.J 0,2c(

-,oE

9

oAdults Cubs w

¡~;jm

~~c>-:!:

Figure 1. Mean levels of globulins and proteins, and mean ratios ofalbumin/globulin in adults and cubs. Error bar indicates 95% confi-dence intervals around the means.

oactive in winter (Laplaud et al. 1980; Fowler and Racey 1988).

Pathological alterations linked to high levels of cholesterol are

known in other species but unknown in badgers. However, an

increased cholesterol level is also an evolved mechanism with

specific survival value for peripheral tissues (Kaneko et al.lQQ7)

Females Males

SEX

Figure 2. Mean hydroxybutyrate levels in females and males. Error barindicates 95% confidence intervals around the means.

60

40

20

0,7

0,6

0,5

0,4

0,3

0,2

0, 1

Badger Blood Biochemistry 457

czou

'<I¡.

Summer96 Autumn97 Spring98

SEASON

1,5

Qz 0,5O(.)

~ °~

-0,5

Summer96 Autumn97 Spring98

SEASON

proteins, reflected in animals of any condition, due to a diet

poor in proteins in summer, when earthworms are scarce.

The urea/creatinine ratio did not decrease in winter as has

been reported for black bears (Nelson et al. 1984). However,

mean values in summer 1996 were still much higher than values

reported for bears during winter, indicating that protein ca-

tabolism was still relatively high even in periods of food scarcity.

Badgers were not sampled in deep winter to avoid disturbance

during the final trimester of gestation. However, urea/creatinine

ratios for November 1997 samples (the mean air temperature

between October 16,1997, and November 14,1997, was 7.8°C)

still support the fact that the Eurasian badger, unlike the bear

but similarly to the American badger (Harlow and Nelson

1990), does not demonstrate a stage of protein conservation

during winter. This supports the hypothesis that reproductive

needs require thebadgers' metabolism to remain active during

winter, and this should be possible through the consumption

of worms rich in proteins throughout winter. In future research,

comparisons of winter urea/creatinine ratios and diets among

badgers from different latitudes could help to clarify our

arguments.Gluconeogenesis might result in decreased levels of proteins

and might be used to assess dietary inadequacies, although

changes in blood proteins are often difficult to detect and in-

terpret. Overproduction of albumin has not been documented

in animals, but severe dietary deficiencies induce hypoprotei-

naemia. With dietary deficiencies, globulin levels decrease be-

fore albumin levels (Kaneko et al. 1997). We found different

albumin/globulin ratios across seasons, with a high ratio in

summer 1996 that could reflect a decrease in globulins in the

period of higher nutritional constraints. In addition, adults had

higher levels of globulins than cubs, whereas levels of albumin

were not significantly different (Table 2; Fig. 1). An increase of

plasma proteins due to an increase in the synthesis of their

own immunoglobulins as individuals grow is a general trend

in animals (Kaneko et al. 1997). In addition, we found higher

levels of globulins in animals with wounds than in animals

without wounds (Fig. 5). Levels of blood proteins are affected

by metabolic interactions, such as tissue repair, that cause de-

mands on protein reserves and, subsequently, decrease albumin

and increase globulin levels in the blood. Different types of

globulins are considered positive acute-phase proteins that act

as markers of acute inflammatory disease (Kaneko et al. 1997).

Electrophoretic analyses of proteins would be needed to better

clarify globulin variability in the badgers. The presence of

wounds is also known to relate to the social and reproductive

status of badgers (Cresswell et al. 1992; Woodroffe and Mac-

donald 1995). As a sign of fighting, wounds could provide an

indicator of an increased risk of contracting contagious diseases

that could result in morbidity or mortality.

Inz:i~10O..J~Z

~~m..J<

I ~ \

Summer96 Autumn97 Spring98

SEASON

0,25

w~ 0,2z~~ 0,15

~0,1

0,05

Surnrner96 Auturnn97 Spring98

SEASON

Figure 3. Seasonal changes in FATCOND and RESCOND variablesdescribing changes in body condition, and seasonal changes in theratios albumin/globulins and urea/creatinine. Error bar indicates 95%confidence intervals around tlie means.

4,54

3,5

3

2,5

2

1,5

1

0,5°

1 ,4

1 ,2

1

0,8

0,6

0,4

0,2

°

458 X. Domingo-Roura, C. Newman, F. Calafell, and D. W. Macdonald

Blood Metabolites Related to Ectoparasites and Male

Reproductive Cycles

-+;-I--f-

2 3

FATCOND

51 4

120 l

-oE-=-w~z¡=

sU)wc~wu>-..J"~1-

Levels of flea infection were higher in summer 1996, coincidingwith a period when badgers had low condition scores (FAT -

COND and RESCOND). However, we found no major cor-

r~ation between levels of flea infestation and changes in blood

IÍ1etab()lite levels. Woodroffe and Macdonald (1995) found dif-

ferences in body condition between lactating and nonlactating

females and breeding and nonbreeding males, but they could

not find any difference in ectoparasite load between these

groups. This suggests a lack of influence of flea infestation on

important physiological functions in badgers.

Testes position is indicative of reproductive activity since

males with scrotal testes have more sperm in the epididymides

than males with ascended testes (Woodroffe 1922) .At the be-

ginning of the autumn, males with scrotal testes had more

recent bite wounds, were in poorer condition, and had de-

creased haematological parameters than males whose testes as-

cended earlier (Woodroffe and Macdonald 1995). Physiologicalcosts seem to be associated with extended testicular activity in

breeding males. In this study, cholesterollevels were higher in

males with very ascended testes, whereas creatinine levels were

higher in animals with scrotal testes. However, within a given

season, cholesterol and creatinine levels were not related to

testes position. This suggests that the differences in blood bio-

chemistry were due to seasonal factors rather than to testes

position. In November, animals are in better condition, and

the mating season has already finished, thus they have higher

cholesterol levels and testes ascent. A large number of males

sampled at the beginning of the autumn would be needed to

draw further conclusions.This study describes physiological changes expressed as dif-

ferences in blood biochemicallevels due to seasonal nutritional

50

20 .-

"§(/)z:J::>mo.J~

oWithout

WOUND

With

Figure 5. Mean levels of globulins for badgers with and withoutwounds. Error bar indicates 95% confidence intervals around the

means.

Figure 4. Mean levels of cholesterol, creatinine, triglycerides, and ureafor different FATCOND classes. Error bar indicates 95% confidence

intervals around the means.

40

30

20

10

Badger Blood Biochemistry 459

and reproductive constraints and diseases. Biochemical param-

eters can only partially detect nutritional status, but low values

of certain biochemical parameters will certainly indicate mal-

nutrition and imply reduced reproductive performance and

decreased chances of survival. Controlled studies with mea-

surement of nutritional intake and subsequent responses would

help to further refine the application of blood parameters.tO

assessing condition in badgers. Parameters other than condi-

tion, such as habitat, stress, or additional pathological variables,

must also be considered to better explain biochemical variations

in badgers' blood and to expand the use of these biochemical

variables in wildlife management and health.

Acknowledgments

The badgers were captured and sampled under license from

the Home Office and English Nature. We thank A. Bassols for

her friendly advice and support throughout the project. J. Hen-

derson helped in the collection and processing of the samples.

J. Terradas, R. Whiteley, J. Marmi, and J. Pinyol aided in the

logistics of the project. P. Johnson helped with the statistical

analyses. J. Blue, C. Bonacic, C. Buesching, T. Burkey, M. Covas,

J. Kikwood, G. Kollias, J. M. Puig, and two anonyrnous re-

viewers provided useful comments to improve earlier versions

of the manuscript. Climate data were collected by M. Morecroft

and M. Taylor from the Natural Environment Research Council

Centre for Ecology and Hydrology under the Envil;onmental

Change Network Programme. The project was supported by

the People's Trust for Endangered Species and grants to

X.D-R. from the Institut d'Estudis Catalans (Barcelona) and

the Natural Environment Research Council (United Kingdom).

Literature Cited

Cheeseman C.L. and s. Harris. 1982. Methods ofmarkingbad-

gers. J Zool (Lond) 197:289-292.

Cheeseman C.L., G.W. Jones, J. Gal1agher, and P.J. Mal1ison.

1981. The population structure, density and prevalence of

tuberculosis (Mycobacterjum bovjs) in badgers (Meles meles)

from four areas in southwest England. J Appl Ecol 18:

795-804.

Chraibi F., B. Desbals, C. Pejoan, M. Saboureau, D. Maurel,

and J. Boissiri. 1982. Variations saisonnieres de la lipolyse

des adipocytes de Renard, de Blaireau et de Hérisson. Re-

lation avec les cycles annuels des activités testiculaire et thy-

ro:idienne. J Physiol Paris 78:207-312.

Cresswell W.J., S. Harris, C.L. Cheeseman, and P.J. Mallinson.

199L To breed or not to breed: an analysis of the social and

density-dependent constraints on the fecundity of female

badgers (Meles meles). Philos Trans R Soc Lond Ser B Biol

Sci 338:393-407.

da Silva J., R. Woodroffe, and D.W. Macdonald. 1993. Habitat,

food availability and the social structure of the Eurasian

badger, Meles meles. Oecologia 95:558-564.

Ferrer M. 1992. Natal dispersal in relation to nutritional con-

dition in Spanish imperial eagles. Ornis Scand 23:104-107.

Fowler P.A. and P.A. Racey. 1988. Overwintering strategies of

the badger, Meles meles, at 57°N. J Zool (Lond) 214:635-651.

Franzmann A.W. and R.E. LeResche. 1978. Alaskan moose

blood studies with emphasis on condition evaluation. J Wildl

Manag 42:334-351.

Franzmann A.W. and C.C. Schwartz. 1988. Evaluating condi-

tion of Alaskan black bears with blood profiles. J Wildl

Manag 52:63-70.

Franzmann A.W. and E.T. Thorne. 1970. Physiologic values in

wild bighorn sheep ( Ovis canadensis canadensis) at capture,

after handling, and after captivity. J Am Vet Med Assoc 157:

647-650

Harder J.D. and R.L. Kirkpatrick. 1996. Physiological methods

in wildlife research. Pp. 275-306 in T.A. Brookhout, ed. Re-

search and Management Techniques for Wildlife and Hab-

itats. 5th ed. Wildlife Society, Bethesda, Md.

Harlow H.J. and S.W. Buskirk. 1991. Comparative plasma and

urine chemistry of fasting white- tailed prairie dogs ( Cynomys

leucurus) and American martens (Martes americana): rep-

resentative fat- and lean-bodied animals. Physiol Zool 64:

1262-1278.

Harlow H.J. and R.A. Nelson. 1990. Seasonal serum urea-

creatinine ratios in wild and captive American badgers, Tax-

idea taxus. Comp Biochem Physiol 95A:65-68.

Johansson B. 1957. Some biochemical and electrocardiograph-

ical data on badgers. Acta Zool 38:205-218.

Kaneko J.J., J.W. Harvey, and M.L. Bruss. 1997. Clinical Bio-

chemistry of Domestic Animals. Academic Press, San Diego,

Calif.

Kruuk H. 1978a. Foraging and spatial organisation of the Eu-

ropean badger, Meles meles L. Behav Ecol SociobioI4:75-89.

-.1978b. Spatial organisation and territorial behaviour

of the European badger (Meles meles). J Zool (Lond) 184:

1-19.

Kruuk H. and T. Parish. 1983. Seasonal and local differences

in the weight ofEuropean badgers (Meles meles L.) in relation

to food supply. Z Saeugetierkd 48:45-50.

Laidley C.W. and J.F. Leatherland. 1988. Cohort sampling, an-

aesthesia and stocking-density effects on plasma cortisol, thy-

roid hormone, metabolite and ion levels in rainbow trout,

Salmo gairdneri Richardson. J Fish Biol 33:73-88.

Laplaud P.M., L. Beaubatie, and D. Maurel. 1980. A sponta-

neously seasonal hypercholesterolemic animal: plasma lipids

and lipoproteins in the European badger (Meles meles L.). J

Lipid Res 21:724-738.

Lindsay I.M. and D.W. Macdonald. 1985. The effects of dis-

turbance on the emergence time ofEurasian badgers in win-

ter. Biol Conserv 34:289-306.

460 X. Domingo-Roura, C. Newman, F. CalafeU, and D. W. Macdonald

Macdonald D.W. 1983. Predation on earthworms by terrestrial

vertebrates, Pp. 393-414 in J.E. Satchell, ed. Earthworm

Ecology: From Darwin to Vermiculture. Chapman & Hall,

London.Macdonald D.W., M. Anwar, C. Newman, R. Woodroffe, and

P.J. Johnson. 1999. Inter-annual differences in the age-related

prevalences of Babesia and Trypanosoma parasites of Euro-

pean badgers (Meles meles). J Zool (Lond) 247:65-70.

Mahmood K.H., J.L. Stanford, S. Machin, M. Watts, F.A. Stuart,

and D.G. Pritchard. 1988. The haematological values ofEu-

ropean badgers (Meles meles) in health and in the course of

tuberculosis infection. Epidemiol Infect 101:231-237.

Marco I. and S. Lavin. 1999. Effect of the method of capture

on the haematology and blood chemistry of red deer ( Cervus

elaphus). Res Vet Sci 66:81-84.Nelson R.A., T.D.I. Beck, and D.L. Steiger. 1984. Ratio of serum

urea to serum creatinine in wild black bears. Science 226:

841-842.Owen O.W., P. Felig, A.P. Morgan, J. Wahren, and F.G. Cahill.

1969. Liver and kidney metabolism during prolonged star-

vation. J Clin Invest 48:574-583.Peinado V.I., A. Femandez-Arias, G. Viscor, and J. Palomeque.

1993. Haematology of Spanish ibex (Capra pyrenaica his-

panica) restrained by physical or chemical means. Vet Rec

132:580-583.

Seal U.S. and R.L. Hoskinson. 1978. Metabolic indicators of

habitat condition and capture stress in pronghorns. J Wildl

Manag 42:755-763.Seal U.S., J.J. Ozoga, A.W. Erickson, and L.J. Verme. 1972.

Effects of immobilization on blood analyses of white-tailed

deer. J Wildl Manag 36:1034-1040.~e'arch R.L. 1969. Diagnostic Biochemistry. McGraw-Hill, New

YorK:Sokal R.R. and F.J. Rohlf. 1995. Biometry. 3d ed. W.H. Freeman,

New York.Tietz N. W. 1976. Fundamentals of Clinical Biochemistry. Saun -

ders, New York.Wesson J.A., III, P.F. Scanlon, R.L. Kirkpatrick, and H.S. Mosby.

1979. Influence of chemical immobilization and physical re-

straint on packed cell volume, total protein, glucose, and

blood urea nitrogen in blood of white-tailed deer. Can J Zool

57:756-767Woodroffe R. 1992. Factors Affecting Reproductive Success in

the European Badger, Meles meles L. PhD thesis. University

of Oxford.Woodroffe R. and D.W. Macdonald. 1995. Costs of breeding

status in the European badger, Meles meles. J Zool {Lond)

235:237-245.-.2000. Helpers provide no detectable benefits in the

European badger, Meles meles. J Zool (Lond) 250:113-119.