Factors influencing antler size in free-ranging white-tailed deer and mark/recapture estimates of demographic traits

Paramount to understanding how antler size changes throughout the life of a deer is the ability to appropriately age animals with reasonable certainty. Aging white-tailed deer (Odocoileus virginianus) using tooth replacement and wear (TRW) is inexpensive, widely used, and easy to apply in the field. However, the technique may only be accurate enough to place deer into 3 age categories: fawn, 1.5, and 2.5+ yr old. Cementum annuli (CA) may be a more accurate technique, but its applicability in regions that are not strongly seasonal is unknown. My objectives were to collect known-age mandibles to assess biases in the TRW and CA methods for white-tailed deer in South Texas. Known-age mandibles aged using TRW were placed in the correct category 49% of the time. CA-aged mandibles were assigned the correct age 61% of the time; accuracies declined with deer age. Biologists using the TRW method tended to over-age younger mandibles and under-age older mandibles. In light of biases in the TRW technique, I developed new criteria specific to South Texas and tested these with an independent set of known-age mandibles. Mandibles were correctly aged 72, 73, 68% of the time using the new criteria for 2.5, 3.5--5.5, and ≥6.5 age categories. These criteria provide a biologically useful improvement over current suggestions to pool mandibles over 2.5 years old.;Antlers are used as a tool for white-tailed deer management across much of their range. Criteria based on antler size or number of points has been used to reduce harvest of young individuals and to increase harvest or bucks unlikely to reach a preferred antler size. Because age is an important factor in antler growth, management strategics promoting mature males are useful because they ensure bucks meet their age potential for antler growth while encouraging more natural age structures compared to heavily harvested populations. The effectiveness of selective harvest is dependent on the predictability of the relationship between antler size at one age and antler size at a later age. Also, rainfall can have an effect on plant availability and abundance from year to year. This annual variability in nutrition should be evident in the percentage of yearling deer with small antler size among years. My objectives were to describe antler size changes as deer mature, specifically when antler size peaks and the relationship between antler size at one age and antler size at later ages. I also explored the effect of drought on percentage of spike-antlered yearlings among years. I found antler size to increase until 5 years of age. Yearling antler score was an important predictor of antler scores of ≥5 year old deer and was also positively related to antler scores from deer 2--4 years old. Antler size of yearlings with ≤3 antler points had antlers 15 gross Boone and Crockett score points less than yearlings with ≥4 antler points at 5 years old. Because of the positive relationship between successive antler sets, selective harvest of individuals within a cohort has the ability to alter the average antler size of remaining individuals. Small-antlered individuals tended to stay small-antlered later in life, and few individuals exhibited compensatory growth. Harvest of the largest antlered yearlings may reduce the average antler size of the remaining individuals in that cohort, while harvest of the smallest antlered individuals within an age class can increase the average antler size of bucks left in the population. I found no relationship between drought indices and the percentage of spike-antlered deer occurring among years. If management goals include bucks that reach their age potential for antler growth, these results suggest allowing bucks to reach at least 5 years of age.;Survival estimates for heavily harvested deer populations with female biased sex ratios and male age structures dominated by young bucks are well documented. Less known are survival estimates for areas managing for mature buck harvest and are less heavily harvested. By focusing on mature bucks, this type of management encourages more natural age structures which can benefit populations. My objectives were to determine age-specific survival rates and age structures for male white-tailed deer managed for older age classes with moderate hunting pressure. I developed models using deer that were marked and recaptured or harvested to estimate age-specific survival on 4 sites in southern Texas. Because annual climatic conditions may influence survival, I explored the relationship between drought and survival among years. Age structures were determined by summing the frequency of individuals within an age class for each site. Survival was greatest for 1 year old bucks and lowest for ≥4 year old bucks, but survival estimates varied widely among years. Drought indices interacted with age classes at some sites and revealed that harvest rates may be greater in wet years and harvest restricted when drought conditions exist. Two sites with supplemental feed had less annual variation in survival rates within age classes than sites where feeding intensity was less. Age structures were evenly distributed until 5 years of age, and then declined, reflecting management practices promoting harvest of mature bucks. These age structures differed drastically from heavily harvested populations in other portions of white-tailed deer range. Yearling survival estimates were greater than areas with high harvest intensity, and were similar to or greater than areas practicing quality deer management. Survival for deer ≥3 years old was greater than both traditional and quality deer managed herds. Management for mature bucks can reduce the negative effects of traditional management including truncated age structures and altered breeding ecology. This type of management may provide a solution where age structures and breeding more closely mimic the conditions under which deer populations evolved.