Part 16

Dental abnormalities 142 8 5.6 259 5 1.9 90

Jaw necrosis, lumps, 142 6 4.2 259 1 0.4 95 or fractures

Pathology of lower 75 5 6.7 126 1 0.8 95 limbs ---------------------:------:---------:------:---------:-------------

FOOTNOTES:

Two mandibles from wolf-killed deer had large lumps from healed fractures in the region of the diastemas.

If all dental and jaw abnormalities are pooled, the difference between the incidence in the wolf-kill sample (9.8 percent) and that in the hunter-kill (2.3 percent) is significant at the 99 percent level.

Age Structure

Our data strongly indicate that in northeastern Minnesota wolves prey much more heavily on the older members of the deer population, at least during winter (fig. 7). Substantial vulnerability to wolves seems to begin at about the age of 5 years (fig. 13), because the percentage of wolf-killed deer in each year class increases from 9 percent for 4-1/2-year-old animals to 15 percent for 5-1/2-year-olds (table 4). Indeed, 48 percent of the wolf-kills were aged 5-1/2 and over, which compares favorably with the Ontario figure of 58 percent for these age classes (Pimlott et al. 1969).

These figures assume added significance when compared with a sample of deer killed by hunters in the same general area (fig. 1). Only 10 percent of the hunter-killed deer were 5-1/2 years old or older, and the percent killed in each year class dropped off suddenly from 13 percent aged 4-1/2 to 6 percent aged 5-1/2. If the age structure of the hunter-kill sample is reasonably representative of the age structure of the population at large, the wolf-kill data show that wolf predation in our study area during winter has a definite selective effect on the deer population.

There is no direct way of knowing that the age structure of the hunter-killed deer represents the age structure of the deer population at large. However, sampling hunter-kills is the most practical means available for gaining an index to the age structure of the existing herd. Further, there are three indirect pieces of evidence indicating that the hunter-kill sample represents the actual age structure of the population, just as Maguire and Severinghaus (1954) found in New York. First, our sample has the basic theoretical form expected of a stable deer herd; i.e., the youngest year class contained the most members, and each older cohort included fewer (fig. 7). Second, the age structure of our sample has the same form as most other deer age structures from widely diverse areas, (Ontario, Pimlott et al. 1969; southern Minnesota, Erickson et al. 1961; Massachusetts, Shaw 1951). Third, there is no reason to believe that in our area rifle hunting is especially selective for any particular age classes. In talking with large numbers of hunters, we have learned that most shoot at any and all deer they happen to see.

Even if the age structure of the hunter-kill sample did not approximate that of the actual herd, the comparison of the wolf-kill with the theoretical population dictates the same conclusion: the rate of kill of older deer by wolves was several times greater than that of younger deer, excluding fawns (fig. 13). In any case, if the actual deer population in our study area had an age structure similar to that of our sample of wolf-kills (which would be the only age structure that would contradict our conclusion), its numbers would be declining by orders of magnitude each year, and there would now be only a remnant population. Such obviously is not the case.

The only other question that might arise from a comparison of the age structure of our wolf-killed deer with that of the hunter-killed deer concerns the area from which each sample was taken. Fifty of our wolf-kills came from a region almost inaccessible to hunters (fig. 1). However, the other 92 came from the same general area as the hunter-kills. Nevertheless, there was no statistically significant difference in age structure between the wolf-kills from the wilderness versus those from the hunted area (table 1). This fact also suggests that the human hunting in the area is relatively light and has little effect on the age structure of the deer population in the area.

Wolves may also be taking a disproportionately high number of fawns, although our data do not show this. Nevertheless, there may be a bias against fawns in our method. It is not unusual to discover the remains of a wolf-killed deer so completely eaten that there is no indication left of the animal's age. Because fawns often are only about half the size of adult deer, and their skeletons have not yet completely ossified, the chances are better that fawns will be more completely eaten. Pimlott et al. (1969) also recognized this possible bias, although their data did indicate that wolves were killing a higher percentage of fawns than occurred in the population.

Our study does support the other conclusion of Pimlott et al. (1969), based on a study of 331 kills, that wolf predation on deer during winter shows a definite selection for older animals. It does not agree with the tentative conclusion of Stenlund (1955) that wolves in the Superior National Forest do not prey disproportionately on old deer. However, Stenlund's conclusion was based on 36 kills and on the assumption that only deer at least 7 years old were "old." Deer 5 years old and older composed 33 percent of Stenlund's sample, a figure considerably higher than the 10 percent in these age classes in our hunter-kill sample (table 4). Thus Stenlund's data do not contradict our conclusion.

The age of 5 years seems to be the beginning of the period of vulnerability for adult deer. Although 5 years might not seem especially old, there are two aspects of significance concerning deer of this age and older. First, they are in the second half of the life span for most members of the species, and their alertness and ability to bolt quickly away might be expected to decline. It is of interest in this regard that Klein and Olson (1960, p. 87) believed 5 years of age to be "the upper limit of physiological efficiency" of black-tailed deer (Odocoileus hemionus) in Alaska. Second, up to the age of at least 4-1/2 years, and perhaps beyond, the apparent weight-load-on-track of deer increases with age (Kelsall 1969). Thus older deer would sink farther into the snow than younger ones, and their escape might be slowed and hindered more. For further discussion of the effect of snow on the vulnerability of deer, see Mech et al. (p. 51).

Sex Ratio

Statistical tests comparing a number of subsamples of both wolf-killed deer and hunter-killed deer showed a series of significantly different sex ratios (tables 1-3). The ratio of males to females in the fawn cohort of the hunter-kill, which is probably the most representative of the actual fawn sex ratio, was even (table 2). With wolf-kills, however, a significantly higher percentage of females was taken in the fawn subsample (59 percent) than in the adult subsample (46 percent). These results compare favorably with those of Stenlund (1955), who found that from 1948 to 1953 in the same area as the present study 68 percent of 19 sexable fawn wolf-kills were females and 44 percent of 63 sexable adult wolf-kills were females.

If the sex ratio of fawns began even, and more females than males were killed by wolves, then a higher proportion of males would be left in the adult population, unless some other mortality factor kills more male fawns. Thus it is not surprising that in the wilderness area, where little or no hunting is done, the sex ratio of wolf-kills in the adult cohort is significantly heavy toward males (71 percent: 29 percent). This was also true of the wolf-kills in Algonquin Provincial Park, where males made up 57 percent of the total sexable wolf-kill (Pimlott et al. 1969). The latter figure may even have been higher if calculated for adults alone, for a preponderance of female fawns in the Algonquin Park data (such as occurred in our and Stenlund's samples) would tend to obscure the preponderance of males in the adult sample.

The adult subsample of hunter-kills also contained a higher percentage of males (66 percent : 34 percent). Although this might also reflect the influence of wolf predation on female fawns, it probably is more a result of the greater movement of bucks during the hunting season, which overlaps with the rutting season. Even the sex ratio of adult deer killed in wolf-free areas shows a preponderance of males (Erickson et al. 1961).

However, it appears that the higher harvest of bucks by human hunters does markedly affect the sex ratio of the deer population in the hunted area, for the wolf-kill of adults in that area contained a significantly higher percentage of does (56 percent) than did the wolf-kill of adults in the wilderness area (29 percent).

Evidently the hunter harvest is not heavy enough to affect the age structure of the deer population to any marked degree, for no significant difference in age structure was found between the wolf-kill in the hunted area and that in the wilderness area (table 1). This does not conflict with the conclusion that hunting affects the sex ratio of the deer herd, because it would take much less to influence a population characteristic having two classes (sex) than one having 14 (age).

One additional difference in the sex ratio was found between two other subsamples of the wolf-kill--that is, the wolf-kill before and after an unusually high snow accumulation, which reached its peak about February 1, 1969 (table 1). Of a total of 77 animals killed before this snow condition occurred (including those from previous years), 38 percent were females. Of 44 animals killed after the heavy accumulation, 57 percent were females. One possible explanation for this is that females may normally be less vulnerable to wolf predation, for Kelsall (1969) has shown that they probably have a lighter weight-load-on-track than males. Thus when snow conditions changed greatly, making deer generally much more vulnerable to wolves (see Mech et al., p. 35), a preponderance of does suddenly might have become available. There is some evidence that does may be generally less vulnerable under most conditions, for all seven of our wolf-killed deer over 10 years old were females, and the oldest was over 14.

Condition of Wolf-Killed Deer

Because the data show that wolves in our study area tend to kill a disproportionate number of older deer, it is not surprising to discover that wolves also tend to capture a disproportionate number of individuals with abnormalities and pathological conditions (table 8). The explanation for such selection is obvious in regard to the abnormalities of the lower limbs (figs. 14-17): deer with injured or abnormal limbs simply cannot run as fast or as agilely as normal animals (table 7). Our observations show that deer usually depend on their alertness and speed to escape approaching wolves (Mech 1966b, Mech et al., p. 1). Any trait or condition that tended to interfere with either alertness or speed would decrease an individual's chance of escape.

It is more difficult to explain how dental abnormalities or pathological conditions of the mandible (figs. 8-10) would predispose an individual to wolf predation. However, in the case of dental abnormalities the genetic or environmental conditions that caused the abnormality might also have caused some other trait that increased the animal's vulnerability. Or the abnormal condition itself may have caused a further, more critical, disruption of the animal's physiology or behavior, which in turn predisposed it to wolf predation.

The finding of several wolf-kills with poor fat stores could indicate that primary or secondary malnutrition was a factor in the animals' deaths. However, it would take a statistical comparison between the fat stores of the deer at large and those of the wolf-kills to establish this.

The discovery that 13 percent of the fawns and 84 percent of the yearlings killed during January, February, and March had not yet shed their deciduous incisors and premolars, respectively, also fits well with the rest of our information. Evidently some unusual factor had caused the delay in tooth development and replacement. One possibility is that the animals were born in August or September, much later than normal. Although most deer in Minnesota are born in May and June, there are records of births in July and August. In addition, a fetus 181 to 200 days old was found in a doe killed on September 26 (Erickson et al. 1961).

An alternate explanation for the delay in tooth replacement is that the animals were suffering from malnutrition or nutrient deficiency. Severinghaus has evidence that yearling bucks that have not replaced their deciduous premolars during November, and thus are aged at 17 months (Severinghaus 1949), generally have shorter, narrower antlers and fewer points than 18-and 19-month-old individuals. Degree of antler development in turn is considered related to nutritional state (Latham 1950). Thus it is reasonable to conclude that animals behind in tooth development and replacement, whether this is caused by age or diet, are physiologically inferior.