WILDLIFE SCIENCE: LINKING ECOLOGICAL THEORY AND MANAGEMENT APPLICATIONS - CHAPTER 12

12 Density Dependence in Deer Populations: Relevance for Management in Variable Environments Charles A. DeYoung, D. Lynn Drawe, Timothy Edward Fulbright, David Glenn Hewitt, Stuart W. Stedman, David R. Synatzske, and James G. Teer CONTENTS Testing South Texas Deer Counts for Density Dependence ...................................... 206 Foundation Theory and Management Relevance ................................................. 215 Acknowledgments.................................................................................. 220 References .......................................................................................... 220 New-world deer of the genus Odocoileus are commonly assumed to respond to food shortage due to intraspecific competition by reduced recruitment, body mass, and other manifestations. McCullough’s (1979) book on the George Reserve deer herd is commonly cited as the definit-ive work on density dependence in white-tailed deer (O. virginianus), and by extension, mule deer (O. hemionus). The George Reserve is a 464-ha, high-fenced property in Michigan, United States. Two males and four females were introduced in 1928, and by 1933, the population was estimated to be 160. The population fluctuated until 1952, when a series of experiments with deer density began. The population was reduced during this time in a series of steps and data collected to form a population model (McCullough 1979). Strong density dependence was evident in this model. Reductions in the George Reserve population continued into 1975, when an estimated 10 deer remained (McCullough 1982). No deer were subsequently harvested for 5 years to allow the popu-lation to increase. McCullough (1982, 1983) concluded that the population response after 1975 was similar to the original increase from 1928 to 1933. Downing and Guynn (1985) presented a generalized sustained yield table using McCullough (1979) as a starting point. Downing and Guynn (1985) used their experience and literature values to present a table scaled to percent K carrying capacity. McCullough (1979, 1982, 1983) and Downing and Guynn (1985) showed density-dependent responses across the population growth range from low density to K. We define K as the maximum sustainable population level where the deer are in approximate equilibrium with their food supply (Macnab 1985). Downing and Guynn (1985) recognized that their generalized model might not apply to all deer populations.Theywonderediftheirmodelwouldbeapplicabletolow-densitypopulationsandareas 203 © 2008 by Taylor & Francis Group, LLC 204 Wildlife Science: Linking Ecological Theory and Management Applications with poor habitat, which precluded high rates of recruitment. They suggested ways their generalized model could be modified for populations that did not fit the mold of those where recruitment was consistently high and relatively stable across time. McCullough (1984) also recognized that if environmental variation is great, density-dependent effects, while present in the mix of factors impinging on a population, may be masked. He suggested that these situations were rare and occurred at extreme fringes of whitetail range. Mackieetal. (1990)questionedwhetherdensity-dependentmodelshaveutilityformanagement. They presented data from three mule deer and two white-tailed deer populations in Montana, United States, and concluded that there was evidence of density-dependent behavior in one mule deer and one white-tailed deer population. They stated that western North America has a high degree of environmental variation resulting in fluctuating carrying capacity. They suggested that some Montanapopulationshaddeclined, becauseexpecteddensity-dependentresponsestoharvestdidnot happen. Finally, they suggested that in variable environments, managers should employ techniques providing regular tracking of population size and performance and not depend on predictions from density-dependent models. McCullough (1990) issued a strong caution to the conclusions of Mackie et al. (1990). He stressed that density-dependent behavior may be missed because it is obscured by environmental factors and sampling error.Also, experimental and statistical design frequently places the burden of proof on density dependence, that is, the null model is a lack of density dependence. Finally, time lags, study area scale, environmental homogeneity, life history, behavior, and predation may make density dependence difficult to detect when in fact it is present. Importantly, McCullough (1990) hypothesized that several of these factors, singularly or in combination, can result in a population of deer expressing no density-dependent response until very near K. Fryxell et al. (1991) reported on a white-tailed deer population in southeastern Ontario, Canada, thatfluctuatedwidelyover34years.Theyconcludedthatvariationinhuntingeffortstronglyaffected the fluctuation and that the population showed time-lagged density dependence. McCullough (1992) again emphasized that environmental variation can obscure density-dependent responses in deer populations. He stated that this may require study of a population over a large range of densities to detect a density-dependent response. McCullough (1999) also reviewed and extended his concept of some populations of ungulates having a “plateau” of constant growth and then a “ramp” of declining growth in the graph of r on N (Figure 12.1B, b, C, and c). No density-dependent response would be observed in the plateau phase. He hypothesized that this model could fit more K-selected species with low reproductive rates. However, he speculated that a plateau and ramp model may fit Odocoileus deer in desert environments. Bartmann et al. (1992) could not detect differences in fawn survival in response to experimental removal of 22 and 16% in consecutive years in a migratory Colorado, United States, mule deer population. They subsequently simulated density-dependent fawn mortality in enclosures with a wide range of density. Natural mortality of adult does was low in the free-ranging population but fawn mortality was relatively high and varied with winter severity. Relation of this population to K was unknown, but the authors assumed it to be near or at K. Keyser et al. (2005) studied long-term data sets for nine white-tailed deer populations in the southeastern United States. They concluded that eight out of nine populations showed density-dependent responses, but that these responses frequently lagged 1 or 2 years. They stated that the population that did not show density-dependent responses occurred on exceptionally poor habitat. Sheaetal.(1992)collecteddatafromawhite-taileddeerpopulationinFlorida,UnitedStates,that declined 75% in density during a 10-year period. They found little difference in deer physiological indices during this period and concluded that the habitat, which was characterized by low-fertility soils, produced low amounts of high-quality forage and an abundance of poor-quality forage. Lack of nutritious forage, coupled with abundant poor-quality forage precluded a density-dependent response,becausetherewaslittleopportunityforintraspecificcompetition,evenwhendensitieswere high. Shea and Osborne (1995) discussed poor-quality habitat across NorthAmerica. They surveyed © 2008 by Taylor & Francis Group, LLC Density Dependence in Deer Populations 205 A Density (a) dependence expressed cc r N N K Time B Density (b) dependence expressed cc r N N K Time C Density (c) dependence expressed cc r N N K Time FIGURE 12.1 Plateau and ramp graphs (A, B, C) showing a range of deer population density-dependent responses and corresponding graphs (a, b, c) of carrying capacity variation in comparison to population level variation. (Adapted from D. R. McCullough. J. Mammal. 80:1132 and 1133:1999. With permission.) stategamedepartmentsandproducedamapwithinwhitetailrangewheredensity-dependentresponse would be lacking or masked. Dumont et al. (2000) worked on white-tailed deer on the northern limit of their range in south-eastern Quebec, Canada. They stated that severe winters were among the major factors limiting deer populations, but found density-dependent responses during mild winters. Gilbert and Raedeke (2004) worked on Columbian black-tailed deer (Odocoileus hemionus columbianus) and found that minimum temperatures in May and the amount of precipitation in June affected fawn recruitment. However, they also reported that plant production was correlated with deer density in the same year.Also, their best models of fawn production included time-lagged dens-ity or forage terms. They concluded that the population was expressing density-dependent behavior during the study period. McCullough (1999) cited the intrinsic rate of increase of the population, scale of area occupied by the population, heterogeneity of environment, and general quality of the habitat as factors that might explain why ungulates respond differently to a range of densities. Scale of the area occupied bythepopulationreferstoconfinedareassuchasenclosuresorislandswherelimitationsondispersal may change population growth rate. A heterogeneous environment allows ungulates more types of high-qualityfood, leadingtocompetitionamongdifferentclassesofindividualsasdensityincreases. © 2008 by Taylor & Francis Group, LLC 206 Wildlife Science: Linking Ecological Theory and Management Applications Finally, high-quality habitats, including moderate temperatures and precipitation, lead to high plant production. On the contrary, habitats with strong limitations on plant growth may result in most forage being of low quality, except perhaps in occasional good years. White-tailed deer have the potential to have a high rate of increase in rich habitats with stable environments, where female fawns commonly breed. Such populations may have a density-dependentfunction(r onN)thatisallramp,withnoplateau(Figure12.1A).Suchpopulationsexpress density dependence virtually all the time (Figure 12.1a), even though N may be well below K. McCullough (1999) listed mule deer among the species that may exhibit a plateau-ramp density-dependentfunction(Figure12.1Bandb).HestatedthatthesepopulationsmaynotreachK veryoften, because they tend to live in variable environments, and have lower rates of increase as compared to white-tailed deer. Populations that fit the plateau-ramp hypothesis (Figure 12.1B and b) have a plateau of the density-dependent function where no density-dependent responses would occur. Only whenthesepopulationsapproachK aredensity-dependenteffectsobserved.Whenthesepopulations are significantly below K, density-dependent effects are not observed (Figure 12.1B and b). McCullough (1999) felt that desert mule deer (O. H. crooki) may exhibit the density-dependent function shown in Figure 12.1C, based on the work of Short (1979). This hypothesis fits populations withlowintrinsicratesofincrease,homogenoushabitatswithmostlylow-qualityforage,andvariable environments. Figure 12.1c shows that these populations only exhibit density-dependent responses during occasional favorable periods. ThisreviewofliteratureshowsthatOdocoileuspopulationdynamicsarecomplexandfrequently site specific. The complex nature of population dynamics in this genus makes formulating a general population model challenging. Almost without exception, researchers cite McCullough’s (1979) George Reserve work as the conventional model for density dependence. However, as this review has shown, there are many situations where density-dependent behavior in Odocoileus populations cannot be detected. How widespread are habitats where the assumption of density-dependent beha-vior is not useful to management? Our objectives in this chapter are to (1) analyze three long-term setsofwhite-taileddeercountsinSouthTexasfordensity-dependentbehavior, (2)suggestsomeuni-fying concepts for considering density-dependent and density-independent behavior of Odocoileus populations, and (3) suggest regions of deer range where population behavior cannot regularly be predicted with density-dependent models. TESTING SOUTH TEXAS DEER COUNTS FOR DENSITY DEPENDENCE EarlyEuropeanexplorersinSouthTexas,UnitedStates,foundalandscapethatwasmostlygrassland, commonly interspersed with shrub communities (Inglis 1964; Fulbright 2001). White-tailed deer werepresentinwoodedstreambottoms, shrubcommunitiesonuplandareas, andontheopenprairie. Little is known about deer populations from this period, except they were commonly mentioned in traveler’s journals (Doughty 1983, 29; Fulbright 2001). Cattle and horses were at least locally numerous by the mid-1700s (Lehmann 1969). Shrubs probably began to increase at this time, and this trend continued into the twentieth century (Jones 1975). Although famous for cattle ranching, the region harbored millions of domestic sheep in the latter part of the nineteenth century (Lehman 1969). Climatic change may have been a background condition influencing changes in plant ecology in the region, with grazing by domestic livestock beingthedrivingforce(VanAuken2000).Acool, wetperiodlastedfromabout1350to1850(Foster 1998, 9). After 1850, the climate became warmer and dryer, which may also have influenced the increase in shrub density and distribution. Removal of fuel by livestock grazing and suppression by humans reduced or eliminated natural fires that inhibited the increase in woody plants during pre-Columbian times (VanAuken 2000). In the twentieth and early twenty-first centuries, the region has been covered by a canopy of shrubs, frequently in complex taxonomic mixes (Inglis 1964; © 2008 by Taylor & Francis Group, LLC Density Dependence in Deer Populations 207 Jones 1975). Exclusive of the coastal sand plain and coastal prairie, over 90% of the region has been subjected to ≥1 attempts to reduce shrub density to increase cattle-carrying capacity (Davis and Spicer 1965). Increased shrub density during at least the past two centuries may have facilitated increased deer populations. Deer did not become locally extinct in South Texas after European settlement as they did in much of NorthAmerica.This was the result of low human density in the region, and large land ownerships. Roads and highways were scarce until the 1920s when oil exploration began in earnest. South Texas, particularly the King Ranch and the Aransas National Wildlife Refuge, provided deer for reestablishing populations elsewhere in the state. Historically, medium- and large-sized predators of deer have included jaguar (Panthera onca), mountain lion (Puma concolor), bobcat (Lynx rufus), black bear (Ursus americanus), gray wolf (Canis lupus), red wolf (Canis niger), and coyote (Canis latrans). Of these, wolves and jaguar are extirpated. Black bears are limited to occasional dispersers from northern Mexico. Mountain lions are present in generally low, but apparently increasing density with high densities in localized areas (Harveson 1997). Coyotes and bobcats are present throughout the region, often at high population densities. Mountain lions prey on deer in South Texas, but do not appear to exert a region-wide influence on populations. Bobcats kill deer but do not appear to be an important factor to deer populations (Blankenship 2000; Ballard et al. 2001). Studies in the 1960s and 1970s in eastern South Texas showed significant coyote predation on deer fawns (Cook et al. 1971; Beasom 1974; Carroll and Brown1977;KieandWhite1985).Meyeretal.(1984)suggestedthatinadditiontocoyotepredation, poor summer nutrition may be a strong factor in low South Texas fawn survival. Evenbeforetherewasanyformalmanagementofdeerpopulations, SouthTexaswaswellknown for producing large-antlered bucks (Brothers and Ray 1975; Helmer 2002). Large antlers are con-sistent with populations well below K carrying capacity (McCullough 1979). Examples of irruptive behavior in deer populations in the region are lacking, although an irruption was experimentally induced by Kie and White (1985). Fawn survival from birth to fall is erratic (Ginnett and Young 2000) and low compared to white-tailed deer populations in general (Downing and Guynn 1985). Unhunted and otherwise unmanaged deer populations persist in a generally healthy state on some large, remote ranches. The region is virtually all private land, much of which is leased for hunting. Intense interest in deer management has developed among landowners and hunters during the past three decades. Wildlife biologists in the region commonly prescribe management practices for deer populations based on the assumption of density-dependent population behavior (Brothers and Ray 1975: 62). This is particularly true of prescriptions to harvest does, as there is a common belief that without significant doe harvest, deer populations will increase to undesirable levels. In variable environments, K carrying capacity (Macnab 1985) varies from year to year. The same number of animals may be above K in dry years and below K in wet years (McCullough 1979: 156). The negative feedback of animals on food plants is less important as a population influence compared to the annual swings in K. For South Texas, the CV for annual rainfall varies from 29 to 41%(NorwineandBingham1985). RainfalloccursthroughouttheyearwithstatisticalpeaksinMay and September. The average growing season is about 300 days; however, plant growth can occur any month when moisture and temperature permit (Box 1960;Ansotegui and Lesperance 1973). Weanalyzedfordensitydependenceinlong-termtime-seriesofdeercountsonthreestudyareas. The Faith Ranch (28◦15 N, 100◦00 W) was 16,115 ha in the western portion of South Texas, the Chaparral Wildlife ManagementArea (28◦20 N, 99◦25 W) consisted of 5,930 ha approximately in the center, and the Rob and Bessie Welder Wildlife Foundation Refuge (28◦6 N, 97◦75 W) was 3,158 ha in the eastern portion of the region (Figure 12.2). FortheFaithRanch,asinglehelicoptersurveyofdeerwasconductedannuallyduring1975–1977 and1981–1997.Thisconsistedofflyingadjacentbelttransectsabout200mwide,ataheightofabout 20mandspeedofabout55km/h(DeYoung1985;Beasometal.1986).Surveysencompassedvarious © 2008 by Taylor & Francis Group, LLC ... - tailieumienphi.vn