Accuracies and biases of ageing white-tailed deer in semiarid environments

Abstract

Context The ability to accurately estimate age of animals is important for both research and management. The two methods for age estimation in ungulates are tooth replacement and wear (TRW) and cementum annuli (CA). Errors in estimated TRW ages are commonly attributed to environmental conditions; however, the influence of environmental variables on tooth wear has not been quantified. Further, the performance of CA in environments with weak seasonality has not been thoroughly evaluated. Aims The study had the following three goals: identify environmental and morphological factors that influenced estimated ages, quantify accuracy of TRW and CA, and develop TRW ageing criteria that minimise error. Methods We used data from harvested (n = 5117) and free-ranging, known-age white-tailed deer (n = 134) collected in southern Texas, USA, to quantify environmental and morphological influences on estimated TRW ages, and assess biases in both methods. Key results We observed substantial variation in age estimates for both TRW and CA. Soil, drought and supplemental nutrition had minor effects on tooth wear, insufficient to alter age estimates by ≥1 year. Body mass and antler size influenced age estimates for TRW only for extreme outliers. Both methods were biased and tended to under-estimate ages of adult deer, especially TRW. Wear on the first molar was most correlated with the known age (r2 = 0.78) and allowed biologists to correctly place known-age deer into age classes of 2, 3–5, and ≥6 years old 72%, 73% and 68% of the time, an improvement compared with the 79%, 48% and 28% accuracy from pooled TRW. Conclusions We observed substantial inter- and intra-individual variation in tooth-wear patterns that became more pronounced in older deer. Individual variation had a greater influence on TRW ages than did environmental covariates, whereas CA ages appeared unaffected by environment. Although variable, age estimates were ±1 year of the true age 87% and 93% of the time for TRW and CA respectively. Implications Managers, ecologists and epidemiologists often incorporate ages into population models. The high inter-individual variation in estimated ages, the tendency to underestimate ages of older deer, and the ageing method need to be considered.

The cost of breeding for male common toads

“…A pivotal trade-off around which life histories are thought to evolve, is between allocating limited energy reserves to current reproduction, that may hinder growth and survivorship, or to somatic growth, that may increase the chance of future reproduction (Williams 1966, Harshman & Zera, 2007. The cost of breeding in male vertebrates has been studied in fish (Kawabata et al, 2015), amphibians (Davies & Halliday, 1979;Grafe et al, 1992;Tejedo, 1992;McLister, 2003;Hettyey et al, 2009Hettyey et al, , 2012, reptiles (Olsson, Madsen & Shine, 1997), birds (Moller, 1991) and mammals (Kovacs et al, 1996;Yoccoz, et al, 2002;Galimberti et al, 2007;Lane et al, 2010;Tennenhouse et al, 2012;Meise et al, 2014;Foley et al, 2018).…”

Population dynamics of chital deer (Axis axis) in northern Queensland: effects of drought and culling

“…Factors such as location, diet and observer biases are believed to influence deer age estimated from tooth wear, but the influence can be minor (Hamlin et al . 2000; Foley et al . 2022).…”

“…Deer were placed in one of six age categories (<1, 1-2.5, 2.5-4, 4-6, 6-8 and ≥8 years old) determined from tooth eruption and wear (Buchholz 2022) in the laboratory by the same observer. Tooth eruption indicates deer age up to 3 years old in chital deer (Graf and Nichols 1966;Buchholz 2022), but tooth wear tends to underestimate the true age of older animals particularly ≥6 years old (Foley et al 2022). Factors such as location, diet and observer biases are believed to influence deer age estimated from tooth wear, but the influence can be minor (Hamlin et al 2000;Foley et al 2022).…”

Regional Copper Deficiency in White-Tailed Deer

“…For deer that had been previously captured as a fawn or yearling (0.5 or 1.5 yr.) we corrected ages based on these previous known ages, as assigning age using tooth eruption patterns is more accurate than ages derived from tooth wear (≥2.5 yr. for white-tailed deer) [27]. We collected age-specific morphology measurements to quantify differences in antler size, body mass, and skeletal size.…”