Wildlife Society Bulletin 40(1):41–49; 2016; DOI: 10.1002/wsb.626
Risks Posed by Captive Cervids
Simulated Effects of Releasing Pen-raised Deer into the Wild to Alter Population-level Antler Size STEPHEN DEMARAIS,1 Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University, Box 9690, Mississippi State, MS 39762, USA BRONSON K. STRICKLAND, Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University, Box 9690, Mississippi State, MS 39762, USA STEPHEN L. WEBB, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway, Ardmore, OK 73401, USA TRENT SMITH, Department of Animal and Dairy Sciences, Mississippi State University, Box 9815, Mississippi State, MS 39762, USA CHRIS McDONALD, Mississippi Department of Wildlife, Fisheries, and Parks, Mississippi State University, 1505 Eastover Drive, Jackson, MS 39211, USA
ABSTRACT The ability to develop large antlers in penned deer (Odocoileus sp.) has increased interest in
releasing pen-raised deer to increase antler size of wild populations. We used a model based on population genetic theory with random removal as the form of population control and either 10% emigration and 10% immigration to represent a free-ranging population (Free Range) or with no egress or ingress to represent a fenced property (Fenced). We compared results with a livestock model with no egress or ingress and selective removal of smaller antlered males as the form of population control (Best Case). We modeled release of fawns with an antler distribution averaging 200 gross Boone and Crockett (B&C) score at 5 rates (1%, 5%, 10%, 25%, and 50% replacement of existing population of 2,000) and report the change from a population average of 127.5. The impact of releasing pen-raised deer into native populations was minimal below 25% replacement rate. Replacing 5% of a free-ranging population with 100 pen-raised deer increased B&C score by 0.8, whereas replacing 25% with 500 pen-raised deer increased score by 12. Releasing pen-raised deer into a fenced property was 50% more effective; a 25% replacement increased score by 18. The Best Case Model increased score by 33 at 25% replacement. The cost for each unit increase in score was US$115,000 in a freeranging population, US$75,000 in a fenced population, and US$33,000 in the best case. Our results suggest that altering genetic composition of white-tailed deer populations is not feasible for free-ranging populations and very costly within fenced populations. Ó 2016 The Authors. Wildlife Society Bulletin published by Wiley Periodicals, Inc. on behalf of The Wildlife Society. KEY WORDS antler score, genotype, Odocoileus virginianus, phenotype, selection, white-tailed deer.
White-tailed deer (Odocoileus virginianus) phenotype varies greatly across North America (Miller et al. 2003). Potential antler size is genetically regulated, whereas the phenotypic expression of this potential is modified by the environment (Demarais and Strickland 2011). Phenotypic variation exists at a variety of spatial scales (Gill 1956, Richie 1970, Strickland and Demarais 2000, Monteith et al. 2009), and has been related to the interaction of soil fertility, vegetation types, and land-use with availability of adequate nutritional quality and quantity as the likely underlying cause (Strickland and Demarais 2008, Jones et al. 2010). Patterns of Received: 6 May 2015; Accepted: 3 November 2015 Published: 6 February 2016 This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. 1 E-mail:
[email protected] Demarais et al.
Altering Antler Size with Pen-raised Deer
precipitation and nutrient supplementation also have been found to influence annual antler traits (Foley et al. 2012). The interaction between genetic and environmental effects makes estimating true genetic effects on phenotypic characteristics difficult, especially in wild populations (Webb et al. 2012). However, under controlled settings, where environmental factors are consistent and meet all the needs of an animal, breeders can make notable progress toward genetic improvement. For example, when white-tailed deer are bred under controlled settings with the aid of pedigrees, breeding sires with the largest antlers to dams with a known pedigree of offspring with large antlers produced a doubling of antler size (Lockwood et al. 2007). The larger antler size in future generations resulted from a controlled environment and selective breeding. When environments are more variable, and selection does not occur, the ability to make genetic improvement in antler size in free-ranging populations will be diminished despite deer having 41
moderate to high repeatability of antler characteristics (Foley et al. 2012). In the commercial market, larger antlered males are more valuable to private landowners; extremely larger antlered males are sold as “breeders,” because their semen is used for artificial insemination, whereas males with less impressive antlers are sold as “shooter bucks” for shooting reserves. One Michigan, USA, deer breeder sells semen for up to US$7,500 per straw (Whitehouse Whitetails 2015). A property in Texas, USA, operates breeding pens and offers hunts within a larger enclosure with fees dependent on size of antlers, ranging from US$2,500 for antlers with 130–139 antler score up to US$18,000 for antlers scoring >241 (LaRoca Range 2015). Commercial deer-breeding operations have had success at increasing antler size through controlling the breeding and environment. Production of large-antlered, penned deer by private breeders has increased interest in the feasibility of releasing pen-raised deer into the wild to attempt to alter genetics of wild deer populations. Such releases are common within fenced enclosures in states that allow breeding facilities, such as the 15,529 captive-raised deer sent to release sites during 2009 in Texas (C. Cerny, Texas Parks and Wildlife Department, personal communication). More recently, breeders proposed, but were prohibited from releasing, pen-raised deer to increase antler size of freeranging deer in Marengo County, Alabama, USA (Cole 2012). In spite of this interest, there are no published data on the effectiveness of changing population-level genetics by releasing pen-raised deer into existing wild populations (Jacobson et al. 2011). To facilitate understanding of the potential effects of releasing penned deer into the wild, we used computer simulations to evaluate the effectiveness of releasing penraised deer at varying levels of release intensity (% replacement of existing natural population) at 2 sex ratios and within confined and free-ranging populations. Further, we compared these results with a quantitative genetics model developed for livestock (Kinghorn 1992) that intensively selects individuals for removal, based on smaller phenotypes, but does not model emigration or immigration. Results of these simulations can be used to guide decisions regarding the biological and economical effectiveness of releasing penraised deer into wild populations for the purpose of increasing population-level antler size.
METHODS Response Variable: Antler Score We modeled the response of gross Boone and Crockett antler score (hereafter, B&C score), which is a cumulative measure of inside spread of main beams, main beam lengths, beam circumferences, and lengths of all points (Nesbitt et al. 2009) and an accurate reflection of the total antler size of deer (Demarais and Strickland 2011, Strickland et al. 2013). We calculated the change in average B&C antler score at maturity (5 yr) after release of penned deer compared with the starting average antler size at maturity (5 yr) for males 42
harvested in Mississippi, USA (127.5 14.4 SD; B. K. Strickland, unpublished data), which we used as the starting parameter value for antler size. The difference between the starting value and 10-year response to release will indicate whether improvement occurred. Models We modeled impact of release on average antler score at maturity using 2 modeling approaches to predict genetic change resulting from release of pen-raised deer. First, we developed a simulation model with simplified assumptions that included effective emigration and immigration rates of 10% for yearlings to represent a large, free-ranging population (hereafter, Free Range Model). We also used this model to simulate no dispersal or immigration to represent a fenced population (hereafter, Fenced Model). Harvest was assigned randomly to all age classes following immigration or emigration at the level needed to return the population to 2,000 animals. We simplified the typical agestructured model processes, allowing all animals to breed during their second year, allowing each breeding female to produce 1.5 fawns, and allowing for no natural mortality. Second, we used a quantitative genetics model (Popsim module of GENUP, http://www-personal.une.edu.au/ ~bkinghor/genup.htm), originally designed for livestock (Kinghorn 1992) that provides a “best case scenario” with intensive culling of smaller antlered males and no emigration or immigration to represent a fenced property (hereafter, Best Case Model). The Best Case Model is a typically complex, age-structured model (Kinghorn 1992) with parameter values listed in Webb et al. (2012). It has been shown to accurately reflect genetic modeling applied to penned white-tailed deer and used to model genetic responses to various deer-management scenarios (Webb et al. 2012). We report the average antler score potential at maturity for the male population existing 10 years after the single release of pen-raised deer at year 0. The model included measures of variation representative of biological systems, so results from the Free Range and Fenced Models represent the average of 100 iterations, whereas the results from the Best Case Model represent 10 iterations. Free-ranging and Fenced Models Antler score.—We chose an average antler score of 200 B&C (SD ¼ 8.4) to represent the breeding-pen antler-size distribution, assuming a normal distribution to incorporate variability around the mean. This value exceeds the statewide average by 72.5, so the breeding pen deer represent an extreme increase in the antler size trait over average wild deer. Unfortunately, breeding pen operators do not maintain records on antler development of all offspring, so they cannot provide antler-size distribution data as we used in our models. Deer breeders can provide lineage of sires and dams and antler size of the sire and some offspring, but not antler size of all offspring. Very large, unique individuals are often maintained until maturity or longer, but they are not representative of the typical deer produced. Smaller antlered males are removed from the pens, average-antlered males are Wildlife Society Bulletin
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sold as “put-and-take bucks” for hunting enclosures, and the largest males are sold as potential sires to other breeding pen operators. Therefore, variance estimates are not available for breeding pens. However, we assume the variance within a breeding pen would be less than in a natural population because of previous phenotypic selection. Thus, we reduced our natural population variance based on the 42% reduction in variation seen through 6 generations of intense antlerbased phenotypic selection in the only published example of the process (Lockwood et al. 2007; M. Lockwood, Texas Parks and Wildlife Department, unpublished data). Population size.—We modeled a starting population of 2,000 animals and maintained that population size throughout the 10-year simulation. Deer above the modeled population size were removed randomly. Density was not part of the model, but the area occupied by this population could vary with the nutritional carrying capacity of the habitat, which would influence antler size through environmental variation. For example, in Mississippi, 2,000 deer could occupy an area as large as 15,000 ha or as small as 5,000 ha based on observed deer densities. Our choice of a 2,000-animal population was a practical consideration, in contrast to the private proposal to release deer into Marengo County, Alabama (Cole 2012), which would have required altering genetic composition across 2,543,000 ha. We created a simulated population of 2,000 deer at 2 sex ratios, resulting in 1,000 males and 1,000 females at 1:1 sex ratio, or 500 males and 1,500 females at a 1:3 sex ratio. For each individual, we assigned a genetic potential for B&C score at maturity drawn randomly from a normal distribution for wild deer (x ¼ 127.5, SD ¼ 14.4) or for pen-raised deer (x ¼ 200.0, SD ¼ 8.4). We assumed that male and female deer contributed equally to the genetic potential for antler size, although there is likely an additional maternal contribution associated with her nutritional status and early natal support (Lukefahr and Jacobson 1998, Monteith et al. 2009). Release intensity.—To include a range of potential release efforts, we modeled the impact of replacing 1%, 5%, 10%, 25%, and 50% of the wild population (n ¼ 2,000) with penraised deer, which is equivalent to 20, 100, 200, 500, and 1,000 animals, respectively. Each release was made within the initial population before breeding and removal. Based on release intensity, we would model the number of males and females at the 2 sex ratios until the total replacement number was met. Heritability.—We used narrow-sense heritability (h2) from published literature as a deterministic value. Narrow-sense heritability is the ratio of additive genetic variance to phenotypic variance and expresses the extent to which phenotypes are determined by genes transmitted from parents to offspring (Falconer and Mackay 1996). Because most individual components of antler score are heritable, we assume total B&C antler score is similarly heritable and assigned a value of 0.35 (Williams et al. 1994, Lukefahr and Jacobson 1998), which is similar to the 0.33 heritability of antler mass in a free-ranging red deer (Cervus elaphus) population (Kruuk et al. 2002). Webb et al. (2012) also found Demarais et al.
Altering Antler Size with Pen-raised Deer
that modeling antler score at h2 ¼ 0.35 resulted in similar results between modeled antler score and empirical antler score from 8 years of selection in breeding pens (Lockwood et al. 2007). Dispersal.—Our choice of 10% effective rate of emigration and immigration for yearlings may appear small, compared with rates of 46–86.5% reported for males in a review by DeYoung (2011). This rate was chosen because after dispersal many deer would still be within our virtual population’s boundary, which would have a diameter of 7– 15 km depending on population density. Dispersal distance of yearling white-tailed deer is a population-specific behavioral characteristic associated with landscape characteristics and home range area (Bowman et al. 2002, Long et al. 2005, Diefenbach et al. 2008). Average dispersal distance in forested areas in Pennsylvania, USA, varied from 7 km to 9.6 km and was negatively correlated with relative forest cover (Diefenbach et al. 2008). To show how alternative dispersal rates would affect our results, we also ran the Free Range Model (at 1:1 adult sex ratio and 10% replacement rate) at values of 0%, 10%, 20%, and 30% emigration and immigration of yearling males. Population demographics.—We developed a stochastic model using simplifying assumptions to make predictions of genetic change resulting from release of pen-raised deer. Starting with a virtual population at year 0, we randomly paired males and females (i.e., nonassortative mating) and each pair produced one fawn. Each fawn was assigned a genetic potential for antler score at maturity based on the antler score potential assigned to its parents. Each fawn was allowed to produce its own fawn the following year. We applied a random mortality rate sufficient to remove the number of adults equal to fawn recruitment. In the Free Range Model, additional adults were randomly removed to mimic emigration. An equal number of adults with antler score attributes selected from the normal distribution of B&C scores for the native population were added to mimic immigration. Prior to each year’s simulated run, we assigned new random numbers to animals, which we used to determine their subsequent pairing and fate. We calculated a breeding value (BV) for each deer according to the formula, BV ¼ ðRandomly assigned B&C score Average population B&C scoreÞ Heritability value
Each fawn was assigned a B&C score based on the following formula: Fawn B&C score ¼
MaleBV FemaleBV þ 2 2
þ Average population B&C score
Best Case Model For our Best Case Model we used GENUP (Kinghorn 1992) Version 5.3 (http://www-personal.une.edu.au/~bkinghor/ genup.htm) and the POPSIM module to simulate the 43
pen-raised deer by about 25% across the varying release rates (Table 4). Effects of the penned deer release on antler size varied across the 10-year temporal window for the Free Range and Best Case Models (Tables 1–3). For example, antler score improvement in the Free Range Model, at 1:1 adult sex ratio, declined 33–38% over the 10 years following release depending on the replacement rate (Table 1). However, within the Fenced Model population, at 1:1 adult sex ratio, antler score was relatively stable across the 10-year simulation (Table 2). In contrast to the Free Range and Fenced Models, the Best Case Model, with a 1:1 adult sex ratio, antler score generally increased over time by 17–120% depending on replacement rate (Table 3). However, annual changes were not consistently positive because of the stochastic variability of the Best Case Model. Deer movements, including emigration from the release population and immigration from the surrounding native deer population, influenced the impact on B&C score. Eliminating dispersal within the Fenced Model increased score by roughly 50% at all release rates, and the effects remained essentially unchanged during the 10-year modeling horizon (Tables 1 and 2). The importance of dispersal rate is evident when we compare results for a 10% replacement rate with 0%, 10%%, 20%, and 30% dispersal (Table 5). Effectiveness after the 10-year modeling horizon declined approximately 25% for each 10% increase in dispersal rate, dropping from 7.2 at 0% to 2.8 at 30%.
combined response to penned deer release and selection on white-tailed deer antler size, similar to that described in Webb et al. (2012). Modules within GENUP are algorithmbased rather than data-based, which allows the user to adjust parameters to simulate different scenarios (Kinghorn 1992). The POPSIM module draws on parameters to generate a population with overlapping generations. A foundation population is generated and then allowed to reproduce according to a single-trait selection policy chosen by the user. Specifically, the model included the following input parameters: trait mean and standard deviation, heritability, and population size, sires or dam (i.e., mating ratio at 1:1 and 1:3 M:F), distribution of number of offspring weaned per female (see Webb et al. 2012), and annual survival (M ¼ 82%; F ¼ 88%). Model parameter values were similar to the Free Range and Fence Models or came from existing data sets or published literature (Webb et al. 2012). Additional settings were: selection on individual phenotype (not using information from relatives to help evaluate each male), mate allocation (i.e., random rather than assortative), and culling across adult age groups.
RESULTS Effects of releasing pen-raised deer on antler size potential within a wild population, as measured by change in B&C score 10 years after release, varied greatly based on the percentage of the population replaced by pen-raised animals (Tables 1–4). Within the Free Range Model, with a 1:1 adult sex ratio, the change in B&C score varied from a low of 0.5 with 1% replacement to 24.2 with 50% replacement 10 years after the release (Table 1). A 25% replacement rate of the native population, or a release of 500 pen-raised deer, increased B&C score by only 12.1, which would be a 9% increase over the B&C score for a native population. Within the Fenced Model, at 1:1 adult sex ratio, the impact varied from a low of 0.8 at 1% to 36.2 at 50% replacement 10 years postrelease (Table 2). With the Best Case Model, at a 1:1 adult sex ratio, the impact increased from 1.1 at 1% to 46.5 at 50% replacement rate 10 years postrelease (Table 3). Changing adult sex ratio from 1M:1F to 1M:3F in the Free Range Model improved the effectiveness of releasing
DISCUSSION The lack of substantive increase in population-level genetic potential for antler size at replacement rates
