9th International Deer Biology Congress

AUTHORS: Charles A. Deyoung, David G. Hewitt, Timothy E. Fulbright*, Nathan S. Cook, Robin N. Donohue, David B. Wester – Caesar Kleberg Wildlife Research Institute, Texas A&M University-Kingsville; Don A. Draeger, Comanche Ranch, Carrizo Springs, TX

ABSTRACT: Density-dependent behavior underpins white-tailed deer (Odocoileus virginianus) theory and management application in North America. Researchers have not focused on linking vegetation dynamics, nutrition, and deer dynamics, which has left a gap in our knowledge of the mechanisms underlying density dependence. We conducted a series of designed experiments during 2004-2012 to determine how strongly white-tailed deer density, vegetation composition, and deer nutrition (natural and supplemented) are linked in a semiarid environment where the coefficient of variation (CV) of annual precipitation exceeds 30%. Our study was replicated on 2 sites with thornshrub vegetation in Dimmit County, Texas, USA. During late 2003, 6 81-ha enclosures surrounded by 2.4-m tall woven wire fence were constructed on each study site. The experimental design included 2 nutrition treatments and 3 deer densities in a factorial array, with study sites as blocks. Abundance targets for low, medium, and high deer densities in enclosures were 10 deer (equivalent to 13 deer/km2), 25 deer (31 deer/km2), and 40 deer (50 deer/km2). Each study site had 2 enclosures with each deer density. Deer in 1 enclosure at each density were provided with a high-quality pelleted supplement ad libitum, which we termed enhanced nutrition; and the other enclosure at each density provided natural nutrition from the vegetation. We conducted camera surveys of deer in each enclosure twice per year and added or removed deer as needed to approximate the target densities. We maintained >50% of deer ear-tagged for individual recognition. We used reconstruction, validated by comparison to known numbers of bucks, to make monthlyl estimates of density in each enclosure for use in analysis of treatment effects. We analyzed fawn:doe ratios, growth rates of fawns and yearlings, survival from 6–14 months of age and for adults >14 months of age, adult body mass, and population growth rates (lambda apparent, λAPP) to determine density and nutrition effects on deer populations in the research enclosures during 2004-2012. Fawn:doe ratios declined (P = 0.04) from low-medium density to high density in natural nutrition enclosures but were not affected (P = 0.48) by density in enhanced nutrition enclosures. Enhanced nutrition resulted in increased fawn:doe ratios of 0.15 ± 0.12 fawns:doe at low-medium density and 0.44 ± 0.17 fawns:doe at high density. Growth rate of fawns was not affected by deer density under natural or enhanced nutrition (P > 0.14) but increased 0.07 ± 0.01 kg/day in enhanced nutrition enclosures compared to natural nutrition (P = 0.02). Growth rate of yearlings was unaffected (P > 0.24) by deer density but growth rate increased for both sexes in enhanced nutrition enclosures. Adult body mass declined in response to increasing deer density in natural nutrition enclosures for both adult males (P < 0.01) and females (P = 0.10). Enhanced nutrition increased male body mass but female mass did not increase compared to natural nutrition. Survival of adult males was unaffected by deer density in natural (P = 0.59) or enhanced (P = 0.94) nutrition enclosures. Survival of adult females was greatest (P = 0.04) in medium density enclosures with natural nutrition but similar at low and high density. Enhanced nutrition increased survival of females (P < 0.01) and marginally for males (P = 0.11). Survival of fawns 6-14 months old was unaffected (P ≥ 0.35) by density in either natural or enhanced nutrition treatments but was greater (P = 0.04) under enhanced nutrition. Population growth rate declined (P = 0.06) with increasing density in natural nutrition enclosures but not (P = 0.55) in enhanced nutrition. Enhanced nutrition resulted in an increase of 0.32 in λAPP. Some researchers have reported that density dependence is weak in environments where the coefficient of variation (CV) of annual precipitation exceeds 30%. Despite the high variation in precipitation in our study area, we found evidence of density dependence with natural nutrition because fawn:doe ratios, adult body mass, and population growth rate declined with increasing deer density. However, sequential wet years are usually necessary to attain deer densities approximating our medium and high density treatments under natural nutrition. Density dependent effects may be weak or non-existent at other times. Additionally, plant communities and deer diets did not reflect the density dependent response. We hypothesized that variation in quality of small home ranges in enclosures may have disadvantaged some deer, resulting in density effects at higher densities.