Tests of estimation of age from tooth wear on roe deer of known age: variation within and among populations

Tests of estimation of age from tooth wear onroe deer of known age: variation within andamong populations

A.J.M. Hewison, J.P. Vincent, J.M. Angibault, D. Delorme, G. Van Laere, andJ.M. Gaillard

Abstract: The rate of wear of ruminant teeth may vary according to diet, habitat, and individual tooth characteristics.This variation may cause error in estimating the age of wild ungulates from patterns of tooth wear. We tested theability of 10 observers to accurately estimate age from observation of tooth wear in a large sample of jaws of known-age roe deer (Capreolus capreolus) from three populations. Although the average error was not large (±1.02 years),maximum error ranged from –5 to +6 years for jaws of animals between 1 and 7 years old, with observers generallyoverestimating the age of young animals and underestimating the age of old animals. We found significant differencesamong observers in estimation error. When a “jaw-board” of known-age reference specimens was provided, thisobserver effect was largely controlled for, but accuracy was not improved. Error was partly due to variation in toothwear, both within and among populations. Initial cusp height of the first molar was lower, but tooth wear tended to beslower in one population than in the other two populations, possibly reflecting differences in diet and (or) habitat.Individual variation in tooth wear within populations was observed, possibly reflecting variation in tooth characteristics(e.g., enamel mineralisation), which was a source of error in age estimation from observation. Observers tended tounderestimate the age of jaws with a relatively low degree of wear and vice versa. These results show that estimatingthe age of roe deer from observation of tooth wear produces biased results, severely limiting its application inpopulation studies of this species.

Résumé: Le taux d’usure des dents chez les ruminants peut dépendre du régime alimentaire, de l’habitat et descaractéristiques inhérentes à chaque dent. Cette variation peut entraîner des erreurs dans l’estimation de l’âge d’aprèsl’usure des dents chez les ongulés sauvages. Nous avons éprouvé la capacité de 10 personnes d’estimer correctementl’âge des animaux par observation de l’usure des dents dans un échantillon considérable de mâchoires de chevreuilseuropéens (Capreolus capreolus) d’âges connus provenant de trois populations. L’erreur moyenne n’était pas importante(± 1,02 ans) mais l’erreur maximale se situait entre –5 et +6 ans dans le cas de mâchoires de 1 à 7 ans et lesobservateurs avaient généralement tendance à surestimer l’âge des jeunes chevreuils et à sous-estimer l’âge des vieuxanimaux. Nous avons obtenu des différences significatives de l’erreur lors de l’estimation par les différentes personnes.Lorsqu’un tableau de référence présentant des mâchoires d’âge connu était fourni aux observateurs, l’effet observateurétait fortement diminué, mais l’exactitude des déterminations ne changeait pas. L’erreur était partiellement attribuable àla variation dans l’usure des dents, aussi bien à l’intérieur des populations que entre les populations. Chez unepopulation, la hauteur initiale des cuspides de la première molaire était plus faible, mais l’usure avait tendance à sefaire plus lentement que chez les autres populations, sans doute à cause de différences dans le régime alimentaire et(ou) l’habitat. Au sein des populations, il y avait variation de la vitesse d’usure entre les individus, peut-être à causede la variation dans les caractéristiques des dents (e.g., la minéralisation de l’émail) et cette variation entraînait deserreurs dans l’estimation de l’âge. Les observateurs avaient tendance à sous-estimer l’âge des mâchoires où l’usure desdents était relativement faible et vice-versa. Ces résultats démontrent que l’estimation de l’âge des chevreuils parobservation de l’usure des dents peut produire des résultats erronés, ce qui limite fortement l’efficacité de la méthodedans les études des populations de cette espèce.

[Traduit par la Rédaction] Hewison et al. 67

58

Can. J. Zool.77: 58–67 (1999) © 1999 NRC Canada

Received April 20, 1998. Accepted August 28, 1998.

A.J.M. Hewison,1 J.P. Vincent, and J.M. Angibault. Institut de Recherche sur les Grands Mammifères, Institut National de laRecherche Agronomique, BP 27, Castanet-Tolosan Cédex, F 31326 France.D. Delorme and G. Van Laere.Office National de la Chasse, Centre National d’Etudes de Recherches Appliquées Cervidés-Sangliers, 85bis Avenue de Wagram, 75017 Paris, France.J.M. Gaillard. Laboratoire de Biométrie, Génétique et Biologie des Populations, Unité Mixte de Recherche 5558, CentreNational de la Recherche Scientifique, Université Claude-Bernard (Lyon I), 43 boulevard du 11 novembre 1918, VilleurbanneCédex, F 69622 France.

1Author to whom all correspondence should be addressed (e-mail: [email protected]).

J:\cjz\cjz77\cjz-01\JanZoo(A).vpFriday, June 18, 1999 11:30:21 AM

Color profile: DisabledComposite Default screen

Introduction

The permanent cheek teeth of ruminants continue to growthroughout their life-span, owing to the deposition of dentalcement around the root of the tooth. Despite this, the contin-ual grinding of plant matter causes rapid wear of the overly-ing enamel to expose the dentine layer, causing characteristicpatterns of wear and leading to a gradual reduction in toothheight (Morris 1972; Kunz et al. 1996). Many studies haveexploited the gradual wearing process of the teeth to esti-mate age of individuals in free-ranging populations (Morris1972). Among the Cervidae in particular, the relation be-tween the degree of tooth wear and age has been examinedfor species such as red deer,Cervus elaphus(Lowe 1967;Kierdorf and Becher 1997), white-tailed deer,Odocoileusvirginianus (Severinghaus 1949; Gilbert and Stolt 1970),and mule deer,Odocoileus hemionus(Erickson et al. 1970;Thomas and Bandy 1975). Age assessment is an importantprerequisite for most population studies because age isknown to affect all the main ecological characteristics suchas reproductive success (for a review see Clutton-Brock1988) and survival probability (for a review see Caughley1966). In addition, it is essential to take age structure intoaccount in formulating models of most vertebrate popula-tions (Charlesworth 1994), particularly when they are di-rected at sound management (Caughley and Sinclair 1994).

Field studies of roe deer,Capreolus capreolus, have reliedon tooth wear to obtain age-related estimates of survival(Ashby and Henry 1979; Kaluzinski 1982; Pielowski 1984).Indeed, techniques such as this have been routinely used forconstructing life tables (Caughley 1966), a common methodfor estimating survival of free-ranging mammals (e.g.,Caughley 1977). However, Vincent et al. (1994) showed thatslight errors in age estimation may have profound conse-quences for the interpretation of population dynamics fromlife-table analysis. In addition, many authors continue to usethis technique to estimate age for the analysis of age-relatedbehavioural and ecological characteristics of roe deer (e.g.,Wahlström and Kjellander 1995; Johansson 1996), despitethe fact that its validity remains largely untested. Aitken(1975) concluded that the number of cementum layers ob-served in the sectioned tooth (Mitchell 1967) is an accurateguide to roe deer age, while tooth wear provides only an ap-proximation, owing to individual variability among animalsof the same age. However, these conclusions are onlyweakly supported because the author calibrated his methodwith a very small sample (9 individuals) of deer of knownage that originated from an entirely different region. Simi-larly, Ashby and Henry (1979) calibrated the age estimatesfrom tooth-cusp wear with a single individual of known age,while White (1974) compared age estimates from tooth wearwith those from tooth sectioning without reference to ani-mals of known age (for problems with this approach seeDapson 1980).

While it is evident that the teeth of ruminants do becomemore worn with age, the nature of the relation remains un-clear. Because of interpopulation variation due to differencesin habitat and (or) diet, it seems likely that the relation maynot be constant for a given species (Robinette et al. 1957;Szabik 1973; White 1974). Furthermore, differences in toothcharacteristics among individuals (Kierdorf and Becher

1997) may cause differential rates of wear and lead todiscrepancies in estimated ages of animals in a single popu-lation. This casts doubt on the use of tooth wear as a simpletool for age assessment for scientific and (or) managementpurposes (Morris 1972; Kunz et al. 1996). In this paper weinvestigate variability in tooth wear among three populationsof roe deer in France, using a large sample of known-age in-dividuals. We test the validity of age-estimation techniquesusing tooth-wear criteria. In the absence of a scoring schemesuch as that developed for red deer (Brown and Chapman1991) and fallow deer,Dama dama(Brown and Chapman1990), the use of observed tooth wear for age assessment isvery subjective and clearly prone to observer bias. Here wetest the capacity of 10 different observers with various de-grees of experience (specialist, naturalist, hunter) to estimatethe age of roe deer jaws of known age derived from threepopulations with differences in some ecological characteris-tics (i.e., climate, deer density). We present results from twoapproaches, an initial “blind” test and a subsequent test forwhich a “jaw-board” of animals of known age was providedas reference. The latter approach is often used by managersand may help to standardise estimates among observers.Finally, we investigate the possibility of making assessmentof tooth wear more objective by examining the correlationbetween actual age and a standard measure of wear, theheight of the buccal cusp of the first molar. In his work onroe deer, Aitken (1975) found that the height of this cusp de-clined gradually with estimated age. We quantify variationin the rate of tooth wear among and within populations anddiscuss the implications in terms of life history.

Materials and methods

Study sitesOur study included three populations of roe deer in France, in

Chizé (a deer-fenced 2600-ha reserve in western France, 46°05′N,0°25′W), Dourdan (an open 840-ha state forest near Paris,48°19′N, 2°01′E), and Trois Fontaines (a deer-fenced 1360-ha re-serve in eastern France, 48°43′N, 4°54′E), sites where long-termstudies have been carried out on the population dynamics, socialorganisation, and ecology of this species using marked individuals(e.g., see Gaillard et al. 1993; Vincent et al. 1995). All three sitesare predominantly wooded deciduous, composed essentially of oak(Quercus sessiliflora), beech (Fagus sylvatica), and chestnut(Castanea sativa). Conditions are relatively mild in Chizé andDourdan, but the climate at Trois Fontaines is more continental,with fairly severe winters. Deer density varied among populations,as well as over time at each site. More details are given in the citedsources.

Jaw sampleWe collected a total of 121 lower jaws from the three roe deer

populations. All jaws were cleaned and labelled with an identifica-tion number. We considered only those animals that had beenmarked as kid, either within the first few days of life during sys-tematic searches (Delorme et al. 1988) or in their first winter at 8–10 months of age during large-scale net catches (Gaillard et al.1993; Vincent et al. 1995). Thus, all jaws in our study were fromdeer of known age when they died. In most cases, death occurredas a result of accidents during winter catches, road traffic acci-dents, or hunting operations, although a few animals were founddead from unknown causes. The oldest jaw in the Dourdan samplewas from a 7-year-old, therefore in order to balance the samples

© 1999 NRC Canada

Hewison et al. 59



for statistical analysis, we eliminated all animals aged 8 years orolder. For roe deer, eruption of all permanent teeth is complete bythe age of 10–15 months (White 1974; Ratcliffe and Mayle 1992)and it is simple to identify kids by the presence of deciduous(milk) teeth, notably a tricuspid third premolar (the permanentthird premolar is bicuspid). Therefore, kids were also eliminatedfrom the statistical analysis. Thus, we analysed a total of 72 jawsof 1- to 7-year-olds from the three populations (Table 1). Datafrom kids and animals older than 7 years were not included in theanalysis but are presented graphically.

Age estimation from observationTen observers were selected and classified as follows: one

“expert” and one “naturalist” for each of the three populations,plus one expert and one naturalist with no personal experience ofany of the three study sites. The experts were technicians with ex-tensive field experience of the handling and ageing of roe deer.The naturalists were roe deer biologists, but without specific expe-rience of ageing animals from tooth-wear criteria. In addition, twoexperienced hunters were designated.

For the first reading, the “blind test,” all jaws were placed on atable in random order with a reference number but with nothing toidentify the source population. Each observer was allowed 45 minto estimate ages for the total jaw set. Observers were instructed tonote all jaws with a tricuspid third premolar as kids, and otherwiseto estimate age according to the degree of tooth wear and their pre-conceived ideas of the relation between wear and age. For the sec-ond reading, the “jaw-board test,” the jaws for each of the threepopulations were separated. From each pool, four jaws were re-moved to be used as references (a jaw-board) for that population.Reference jaws were selected to represent the age range 1–7 years,and included 1-, 2-, 4-, and 6-year-olds, but were drawn at randomwith respect to the degree of tooth wear. They were placed in frontof their respective population pool, labelled with their true age.The observers were then allowed a further 45 min to estimate theage of all jaws, calibrating their estimates by reference to the jaw-board for that population.

Age estimation from cusp heightThe height of the posterior buccal cusp of the first molar was

measured from the tooth line using vernier callipers (see alsoAitken 1975). The data were recorded in millimetres to one deci-mal place and the repeatability of the measurement was checkedby comparing measurements among four observers. There wereno differences among observers (one-way analysis of variance(ANOVA), F[3,320] = 0.67,P = 0.570), so in all subsequent analyses

we used the average cusp height (averaged over observers) foreach individual jaw.

Statistical analysisWe tested for a relation of true age to age estimated from obser-

vation among populations (Chizé, Dourdan, Trois Fontaines), ob-servers (10 observers with different levels of experience), andreadings (blind test/jaw-board test) using analysis of covariance(ANCOVA). In this analysis, the estimated age is the dependentvariable and the true age the covariable, and the population, ob-server, and reading are factors to be tested. When differences werefound in the slope of this relation among levels of a given factor,we subdivided the data set and performed a separate analysis foreach level of that factor. Similarly, we looked for differencesamong populations in the relation of true age with cusp height us-ing ANCOVA, where true age is the covariable. Finally, we exam-ined whether individual variability in tooth wear was a significantcause of error in age estimation from observation within each pop-ulation. We plotted the residuals from the regression of cusp heighton true age against the total estimation error from observation (thecombined error of the 10 observers for a given jaw) using linear re-gression.

Results

Error distributionError (the difference between true age and estimated age

from observation) for jaws of 1- to 7-year-olds ranged from–5 to +6 years for the blind test and from – 4 to +5 years forthe jaw-board test, but when the older jaws were also con-sidered, a maximum error of –10 years was observed for ajaw from a 16-year-old (Fig. 1). Only one observer classifiedany of the kids incorrectly (3.6% in the blind test), classify-ing them as yearlings despite the presence of a tricuspidthird premolar. In the statistical analysis below, only jaws of1- to 7-year-olds were considered (see Methods).

Relation between true age and age estimated fromobservation

We first tested if the relation between true age and age es-timated from observation varied among populations, observ-ers, and readings in a three-way ANCOVA model. We foundsignificant differences in the slopes of this relation amongobservers (F[9,1200] = 2.49, P = 0.008) and populations andbetween readings (F[2,1200] = 11.25,P < 0.001), therefore wesubsequently analysed each reading separately.

For each reading we tested whether the relation betweentrue age and age estimated from observation varied amongpopulations and observers in a two-way ANCOVA model.For the blind test, this analysis revealed differences in slopesamong populations (F[2,660] = 3.38,P = 0.035) and observers(F[9,660] = 4.28,P < 0.001) but no interaction between the ef-fect of population and the effect of observer on this relation(F[18,660] = 0.34,P = 0.996). For the jaw-board test we founddifferences in slopes among populations (F[2,540] = 9.62,P <0.001) but not among observers (F[9,540] = 0.39,P = 0.941),and again found no interaction between the effect of popula-tion and the effect of observer (F[18,540] = 0.49,P = 0.963).Thus, for both readings, the relation between true age andage estimated from observation still varied among pop-ulations and (or) observers, so we analysed each reading

© 1999 NRC Canada

60 Can. J. Zool. Vol. 77, 1999

True age Chizé DourdanTroisFontaines

1 4 12 52 5 6 43 — 4 44 3 2 65 — 4 —6 3 2 17 2 3 2

Total 17 33 22

Note: One year indicates jaws of 12- to 24-month-olds, 2years indicates 25- to 36-month-olds, etc.

Table 1. Age distribution (years) of the sample ofjaws from three roe deer populations used in thestatistical analysis.



for each population separately in a series of one-wayANCOVAs.

For the blind test we found that the slope of the relation ofage estimated from observation on true age varied amongobservers for Chizé (F[9,150] = 3.62,P < 0.001) and Dourdan(F[9,310] = 3.57, P < 0.001) (see Table 2), indicating differ-ences among observers in their conception of the rate oftooth wear in these populations. For Trois Fontaines theslope of the relation of estimated age from observation ontrue age did not differ among observers (F[9,200] = 0.88,P =0.541, common slope = 0.894 with SE = 0.058), but therewere significant differences among observers in the inter-cepts (F[9,209] = 2.23,P = 0.021) (Fig. 2), indicating that ob-servers differed in their age estimates for a given true age.The proportion of the total variance explained by the fullmodels was 81.9, 70.5, and 57.1% for Chizé, Dourdan, andTrois Fontaines, respectively (for Trois Fontaines the re-tained model explained 55.4% of the total variance). AtChizé and Dourdan, most observers overestimated ageamong the younger animals (intercept > 0 for 9 out of 10 ob-servers at Chizé and for 10 out of 10 at Dourdan) and under-estimated among the older animals (slope < 1 for 9 out of 10observers for both sites) (see Table 2). At Trois Fontaines,six observers overestimated age (intercept > 0) and four un-derestimated age (intercept < 0) among the young animals,but for all observers, the tendency to underestimate becamemore pronounced with increasing age (common slope =0.894, which is not quite significantly <1,P = 0.066).

For the jaw-board test, the slopes of the regression of ageestimated from observation on true age did not differ amongobservers for all populations (Chizé:F[9,110] = 0.80, P =0.621; Dourdan:F[9,270] = 1.21,P = 0.289, Trois Fontaines:F[9,160] = 0.44, P = 0.909). Nor were there any significantdifferences among observers in the intercepts for Chizé(F[9,119] = 1.73, P = 0.089) or Trois Fontaines (F[9,169] =1.03,P = 0.415). The relation between true age and age esti-mated from observation was described by the equations

estimated age = 0.191 (SE = 0.242)

+ 0.895 [true age] (SE = 0.049) for Chizé

and

estimated age = 0.766 (SE = 0.203)+ 0.629 [true age] (SE = 0.046) for Trois Fontaines

However, there were significant differences among observ-ers in the intercepts at Dourdan (F[9,279] = 3.37, P < 0.001,common slope = 0.894 with SE = 0.037) (Fig. 3), indicatingthat observers differed in their age estimates for a given trueage at this site. The proportion of the variance explained bythe full models was 77.3, 70.0, and 54.5% for Chizé,Dourdan, and Trois Fontaines, respectively (the retainedmodels explained 72.6, 68.8, and 50.8% of the total vari-ance, respectively). At all three sites, observers again over-estimated or tended to overestimate age among the youngeranimals (Chizé: intercept = 0.191, SE = 0.242, not signifi-cantly different from 0,P = 0.430; Dourdan: intercept > 0for 8 out of 10 observers, Table 3; Trois Fontaines: inter-cept = 0.766, SE = 0.203, significantly > 0,P < 0.001) butunderestimated age among the older animals (all slopes sig-nificantly <1, Chizé: 0.895, SE = 0.049,P = 0.032;

© 1999 NRC Canada

Hewison et al. 61

Fig. 1. Histogram of the percentages of jaws correctly (dark) orincorrectly (light) classified as to age from observation. The datapresented are from the blind test on animals of known age,pooled for the 10 observers and three populations. Note that onlyjaws of 1- to 7-year-olds were used for the statistical analysis(see Methods).



Dourdan: 0.894, SE = 0.037,P = 0.004; Trois Fontaines:0.629, SE = 0.046,P < 0.001).

Relation between true age and cusp heightFirst we looked for differences in the relation between

true age and cusp height among the three populations, usingone-way ANCOVA. There were no significant differencesamong populations in the slope of the regression of cuspheight on true age (F[2,62] = 2.00,P = 0.144), indicating thattooth wear occurred at approximately the same rate acrosspopulations (common slope = –0.390, SE = 0.049). How-ever, there were significant differences among population inter-cepts (F[2,64] = 5.60,P = 0.006), indicating that cusp heightfor a given age varied among populations. Deer in theDourdan population had lower cusp heights for a given agethan those in Chizé and Trois Fontaines (Fig. 4). The modelsexplained 66.1% of the variation for Chizé, 35.5% forDourdan, and 49.5% for Trois Fontaines.

Subsequently, we looked for a relation between individualvariability in cusp height and error in estimating age fromobservation for each population. To do this, for each of thethree populations we first constructed a “total error” vari-able, the sum of real (algebraic) errors for the 10 observerscombined for a given jaw. Then we used linear regression toinvestigate whether the total error was greater when jaws de-viated to a greater degree from the established relation be-tween true age and cusp height for that population (i.e., theresiduals of this relation were larger). For two of the threepopulations we found a significant negative relation betweenthe residuals of the true age – cusp height relation with thetotal error. For both readings at Dourdan (blind test: totalerror = 3.47 – 5.10 [res (cusp height× true age)],R2 = 0.159,P = 0.029; jaw-board test: total error = 0.92 – 5.21 [res(cusp height× true age)],R2 = 0.173,P = 0.035) and TroisFontaines (blind test: total error = –2.68 – 10.09 [res (cuspheight× true age)],R2 = 0.477,P < 0.001; jaw-board test:total error = –7.39 – 6.41 [res (cusp height× true age)],R2 = 0.274,P = 0.026), the ages of jaws that had higher thanaverage cusp height were underestimated, while the ages ofthose that had lower than average cusp height were overesti-mated (Fig. 5). No such relation was found at Chizé (blindtest: total error = –5.25 – 0.65 [res (cusp height× true age)],R2 = 0.004,P = 0.824; jaw-board test: total error = –2.25 +0.11 [res (cusp height× true age)],R2 = 0.000,P = 0.973).

Discussion

Our results show that estimating age of roe deer from ob-servation of tooth wear produces biased results because ofvariation in rates of tooth wear among populations and indi-viduals, and because of observer bias. In our tests, we foundthat error in age estimation from observation across the roedeer jaw sample using tooth wear criteria was generally nothigh, averaging ±1.02 years (SE = 0.037 years) for the blindtest for jaws from animals between 1 and 7 years old. Over-all, more than 50% of jaws of animals of each age from kidto 6 years old were classified within 1 year of their true age.However, this proportion decreased steadily with age andconsiderable errors did occur for certain specimens, rangingbetween –5 and +6 years for jaws of animals between 1 and7 years old. When older animals were considered (up to 16

© 1999 NRC Canada

62 Can. J. Zool. Vol. 77, 1999

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years old; Fig. 1), maximum error reached –10 years. Gen-erally, observers overestimated age among young animalsand underestimated age among old animals (see also Gilbertand Stolt 1970; Van Laere et al. 1989). This may have oc-

curred because tooth wear follows a negative exponentialcurve, initially rapid but slowing later, as observed in sev-eral species of antelope (Spinage 1971; Anderson 1986). In4 out of 10 cases at Chizé and 3 out of 10 at Dourdan, the

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Fig. 3. Relation between true age and age estimated from observation from the jaw-board test for Dourdan for the 10 observers (manypoints are superimposed). The regression has a common slope of 0.894 (SE = 0.037), but there were significant differences amongobservers in their age estimates for a given true age (intercepts) (see Table 3).

Fig. 2. Relation between true age and age estimated from observation from the blind test for Trois Fontaines for the 10 observers(many points are superimposed). The regression has a common slope of 0.894 (SE = 0.058), but there was significant variation amongobservers in their age estimates for a given true age (intercepts) (see Table 2).



slope of the relation between age estimated from observationand true age was lower than 0.67 for the blind test (a perfectrelation would have a slope of 1; see Table 2), leading togross errors of underestimation among older animals, possi-bly due to a slowing down in the rate of wear (Ashby and

Henry 1979). Similarly, in the jaw-board test the commonslope of this relation was only 0.63 at Trois Fontaines.Vincent et al. (1994) illustrated how small errors in age esti-mation can lead to completely erroneous conclusions con-cerning the demographic status of a population when such

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64 Can. J. Zool. Vol. 77, 1999

Fig. 4. Relation between cusp height and true age for the three populations. The rates of tooth wear did not differ significantly amongpopulations (slopes), but deer from the three populations had different cusp heights for a given age (intercepts).

Chizé Dourdan Trois Fontaines

Observer N R2 N Constant R2 N R2

ChizéExpert 13 0.82 29 –0.37 0.61 18 0.36Naturalist 13 0.63 29 0.45 0.62 18 0.69

DourdanExpert 13 0.71 29 0.17 0.70 18 0.56Naturalist 13 0.69 29 0.89 0.80 18 0.40

Trois FontainesExpert 13 0.88 29 0.89 0.68 18 0.52Naturalist 13 0.79 29 0.10 0.78 18 0.54

Outside observerExpert 13 0.71 29 0.20 0.67 18 0.60Naturalist 13 0.58 29 0.83 0.61 18 0.60Hunter 13 0.89 29 0.72 0.68 18 0.58Hunter 13 0.90 29 –0.31 0.74 18 0.47

Note: Observers were classified as expert, naturalist, or hunter, and as based in one of the three study sites (Chizé,Dourdan, or Trois Fontaines) or as an outside observer. For Chizé and Trois Fontaines there were no differencesamong observers in either the slopes or the constants of the regression, while at Dourdan there was no difference inslopes but the constants differed among observers (see the text). Therefore, we present here constants for Dourdanonly, together withR2 values for each population and each observer in order to compare models.

Table 3. Regression statistics for the jaw-board test of the relation between true age and age estimatedfrom observation for each observer for the three populations.



data are used in life-table analysis (cf. Ashby and Henry1979). In addition, such errors seriously undermine analysisof age-related behavioural and ecological characteristics inroe deer studies that relied on observed tooth wear for ageassessment. There is clearly a need to test whether alterna-tive techniques (e.g., dental cement layer counts) can pro-vide accurate, unbiased age estimates for this species.

Age-estimation error found in this study can be explainedin part by a strong observer bias. In the blind test there weresignificant differences among observers in their perceptionof the relation between age and tooth wear in all three popu-lations. For Chizé and Dourdan there were differencesamong observers in the perceived rate of tooth wear (theslopes of the relation; Table 2). Although this was not thecase for Trois Fontaines, there were differences among ob-servers in their estimates for a given true age (intercepts;Fig. 2). The use of reference samples of known age on ajaw-board helped greatly to control for this source of error(cf. Van Laere et al. 1989). We found no differences amongobservers in the perceived rate of tooth wear for any of thethree populations, and there were differences among observ-ers in their estimates for a given age only at Dourdan (Ta-ble 3, Fig. 3). However, the jaw-board did not improve theaccuracy of the estimates (cf. Quimby and Gaab 1957). Av-erage error was slightly lower (±0.96 years, SE = 0.038years), but was not significantly different from error for theblind test (t test, t = 1.09,P = 0.277). Furthermore, the pro-portion of variation explained by the models was actuallyslightly lower than for the corresponding models for theblind test (compareR2 values in Tables 1 and 2). Inspectionof the R2 values in Table 2 suggests that there is little rela-tion between the level of experience of an observer and hisaccuracy, but that familiarity with a population improves ac-curacy somewhat.

A second source of error was variation among populationsin patterns of actual tooth wear, measured as cusp height.Differences in diet (White 1974) and (or) habitat substrate(Szabik 1973) may result in differences in tooth hardnessand therefore rate of tooth wear in contrasting habitats(Morris 1972). In our study, wear increased, and thereforecusp height decreased, as roe deer aged (see also Aitken1975; Ashby and Henry 1979). There were no significantdifferences among populations in the speed of the wearingprocess, but this process started from different points, asinitial cusp height was lower at Dourdan than in the othertwo populations (Fig. 4). Thus, there are differences amongpopulations in cusp height for a given age, which could re-flect genetic differences or differences in early develop-ment. For instance, poor nutrition may lead to a delay intooth eruption (Robinette et al. 1957) and alter toothheight. Interpopulation variation in the pattern of cemen-tum deposition in both red deer (Lowe 1967) and roe deer(Aitken 1975) has been attributed to genetic and (or) envi-ronmental factors such as nutritional stress. Carter (1997)did not find any differences in tooth development betweenroe deer from Denmark and Britain, but suggested thatthere were differences in tooth wear in animals as young as1 year old. It is worth noting that although the regressionslopes were not significantly different from each other,Fig. 4 suggests that wear is greater in animals at Chizé and

Trois Fontaines than in those at Dourdan. The slopes of theregression models for each population indicate that cuspheight decreases, on average, by just less than 0.5 mm peryear in the former populations (0.49 and 0.48 mm, respec-tively), but by only 0.29 mm in the latter population.Ashby and Henry (1979) estimated that cusp wear ex-ceeded 0.8 mm per year among young and middle-aged roedeer, but slowed among older animals, and Skogland (1988)found that tooth wear differed by a factor of two betweenpopulations of reindeer,Rangifer tarandus. White (1974)suggested that tooth wear was more rapid among roe deerliving in coniferous woodland or moorland than in those onarable land or in deciduous woodland. Our three study siteswere broadly similar in habitat composition and the cause ofthe differences in the pattern of tooth wear among popula-tions is difficult to determine. However, at Dourdan the deermade some use of agricultural crops in the zone surroundingthe study area as a food source (the other two sites werefenced, preventing access to crops) and this may explainwhy the rate of wear tended to be slower in this population.

A third source of error was individual variability in theextent of tooth wear at a given age. Several authors havesuggested that such variation exists (Quimby and Gaab

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Hewison et al. 65

Fig. 5. Relation between the residuals from the regression oftrue age on cusp height (by population) with the combined totalestimation error (blind test) for the 10 observers for Dourdan (a)and Trois Fontaines (b) (see the text for explanation).



1957) without quantifying its extent or influence on age esti-mation. Aitken (1975) found that cusp height decreased withage, but suggested that there was extensive overlap betweenanimals of slightly differing ages, particularly older animals.Our analysis showed that variation in individual wear partlyexplained errors in estimating age from observation. Individ-uals that deviated most from the general cusp height× agerelation for a given population were also those that wereaged least accurately from observation (Fig. 5). Thus, for in-dividuals with relatively low tooth wear, age was underesti-mated, while for those with relatively high tooth wear it wasoverestimated. This relation did not hold for the Chizé popu-lation, possibly because cusp height was least variable at thissite (the regression of cusp height on true age explained66.1% of the variation in the data, compared with 35.5 and49.5% for the other two sites). Morrison and Whitridge(1997) found a stronger relation between cusp height andage in caribou (88% of the variation explained). This mayindicate that variation in tooth wear rate among individualsis greater in roe deer than in caribou. Kierdorf and Becher(1997) detected differences in enamel mineralisation (cal-cium concentration) and hardness among red deer of thesame age and found that this had a strong influence on therate of tooth wear. Individuals with a relatively high calciumconcentration in the dental enamel have harder teeth thatwear more slowly, therefore individual variability in wear isexpected to increase with age (see Aitken 1975; Brown andChapman 1990, 1991). Such variation in tooth characteris-tics probably also exists in roe deer (see Hrab∨e and Koubek1987; Kierdorf and Becher 1997), and could explain our ob-servation of within-population variation among individualsin cusp height for a given age.

Skogland (1988) discussed the importance of efficientmastication of food for ruminants and recognised the poten-tial life-history consequences of individual variability intooth wear. Increased wear may lead to a decrease in the ef-ficiency of mastication, a consequent fall in body condition,and therefore lower rates of reproduction, and eventually theonset of senescence (see Leader-Williams 1988). Individualdifferences in tooth characteristics and therefore in the pat-tern of wear could thus be an important proximal mechanisminfluencing variation in lifetime reproductive success of ru-minants. Gaillard et al. (1993) found survival rates of prime-age adult roe deer at Chizé and Trois Fontaines to be verysimilar (0.85 for males, 0.92 for females) and suggested thata drop in survival associated with a senescence threshold oc-curred around the age of 6 or 7 years. At Dourdan, adult sur-vival rates appear to be slightly lower (0.79 for males, 0.88for females), but we were unable to detect a decline in sur-vival associated with senescence among older animals (un-published data). We might speculate that the lower adultsurvival rate in this population might be due to the fact thatthe lower cusp height during prime age reduces feeding effi-ciency, while, for similar reasons, the relatively slow rate ofwear in animals at Dourdan results in senescence occurringlater in this population. It should be noted that our inabilityto detect senescence in animals at Dourdan could simply bedue to the small sample size of marked old individuals.Clearly, investigations of survival probability in relation totooth wear at the level of the individual are needed in orderto test these hypotheses explicitly.

Acknowledgements

We thank B. Boisaubert and J.M. Boutin for their assis-tance and comments. B. Cargnelutti, S. Griff, and J.P.Chanal participated in the experiments. D. Morrison and J.Bodkin provided constructive reviews of an earlier versionof this paper.

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Tests of estimation of age from tooth wear on roe deer of known age: variation within and among populations