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The Effects of Extreme Drought on Native Forage Nutritional Quality and White-tailed Deer Diet Selection
Marcus A. Lashley and Craig A. Harper

Southeastern Naturalist, Volume 11, Issue 4 (2012): 699–710

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2012 SOUTHEASTERN NATURALIST 11(4):699–710 The Effects of Extreme Drought on Native Forage Nutritional Quality and White-tailed Deer Diet Selection Marcus A. Lashley1,* and Craig A. Harper1 Abstract - Forage availability is often used as a measure of habitat quality for Odocoileus virginianus (White-tailed Deer; hereafter “Deer”). Many studies have evaluated treatment effects on forage availability, but the effects of other abiotic factors, such as drought, on native forages and Deer diet selection are poorly understood. We measured diet selection and nutritional quality of commonly occurring forages following extreme drought (2007) and normal rainfall years (2008) in 4 closed-canopied hardwood stands in the Central Hardwoods region. Deer selected 6 forage species in both years of the study. Within these 6 species, crude protein (CP) and acid detergent fiber (ADF) were not different, and neutral detergent fiber (NDF) increased during the year of normal rainfall. Thirteen other commonly occurring forages showed a different trend, with CP negatively affected by drought and ADF and NDF unaffected. Less-selected species in the drought year and a greater selection-index cut-off value suggest Deer were more selective of species consumed during extreme drought because fewer plants met their nutritional requirements. Our data support the selective quality hypothesis, predicting Deer become more selective of plant species to meet nutritional requirements when resources are limited. Our data suggest more frequent and intense droughts predicted as a result of global climate change may influence diet selection of deer and decrease forage quality enough to limit lactation during the late-summer stress period in the Southeast. Introduction Odocoileus virginianus Zimmerman (White-tailed Deer; hereafter “Deer”) are among the most important wildlife species, economically and ecologically, in the southern United States (Miller 2001). Deer are the most sought-after game species by hunters (US Fish and Wildlife Service and US Department of Commerce, Bureau of the Census 1993) and they directly impact forest regeneration, understory species composition and structure, and consequently habitat quality for other wildlife species (Anderson and Katz 1993; Casey and Hein 1983; de Calesta 1994; Rossell et al 2005, 2007; Tilghman 1989; Webster et al. 2005). Previous literature has evaluated effects of various forest treatments on forage quality, availability, and nutritional carrying capacity (NCC) (Beck and Harlow 1981, Blake et al. 1987, Brose and Van Lear 1999, Chamberlain and Miller 2006, Edwards et al. 2004, Jones et al. 2009, Lashley et al. 2011, Masters et al. 1993, Miller and Miller 2004, Mixon et al. 2009, Peitz et al. 2001, Shaw et al. 2010, Wood 1988). Data related to diet selection in unmanaged and managed forests have been reported for much of the Southeast (Harlow and Hooper 1972, Johnson et al. 1995, McCullough 1985, Shaw et al. 2010, Warren and Hurst 1981). However, data evaluating the effects of other factors, such as drought, on forage 1Department of Forestry, Wildlife and Fisheries, University of Tennessee, Knoxville, TN 37996. *Corresponding author - malashl2@ncsu.edu. 700 Southeastern Naturalist Vol. 11, No. 4 quality, availability, and diet selection are limited, and as a result, the inter-relationships among forage quality, availability, selection, and NCC and their impact on Deer are largely unknown. For example, Lashley et al. (2011) reported NCC decreased among treatments of similar forage availability, which they attributed to lower crude protein values in some plants in response to drought during 1 year of the study. To the best of our knowledge, no other study has presented related data in the southeastern US. The effects of water deficits on annual and perennial forage legumes have been documented (Carter and Sheafer 1983, Peterson et al. 1992); however, the effects of drought on native forages or food habits of Deer have not been evaluated in the Southeast. Studies on Odocoileus hemionus Rafinesque (Desert Mule Deer) in the western US have reported that during extreme drought, deer diets change to favor evergreen shrubs and drought-resistant plants, and that mortality is increased (Anthony 1976, Lawrence et al. 2004). Given the economic importance of Deer, and the potential for droughts to become more frequent and intense as a result of global climate change (Easterling et al. 2000), further investigation of drought effects on ungulate ecology and native plant species is warranted. We evaluated the effects of extreme drought on native forage quality and diet selection by Deer in 4 closed-canopy hardwood stands in the Central Hardwoods region within the Southern Appalachian Ridge and Valley physiographic province. Our objectives were to 1) measure drought effects on nutritional quality among common plant species in the Central Hardwoods and 2) evaluate the effects of drought conditions on diet selection by Deer. Study Area We conducted our study across 4 upland hardwood stands located in four separate watersheds on the Chuck Swan State Forest and Wildlife Management Area (CSF) in Union, Campbell, and Anderson counties, TN (Fig. 1). CSF is jointly managed by the Tennessee Division of Forestry (TDF) and the Tennessee Wildlife Resources Agency (TWRA). CSF encompasses 9892 ha and is 92% forested, with the remaining acreage in mowed fields, wildlife food plots, logging decks, and maintained roads. Hardwood stands range from 1–200 years in age and are generally managed on an 80–100-year rotation following natural regeneration. Upland hardwood, bottomland hardwood, and mixed pine-hardwood are the primary vegetation types on CSF. For a more detailed description, refer to Lashley et al. (2011).The majority of openings are dominated by nonnative perennial cool-season grasses and maintained by mowing; others are planted in warm-season food plots, including Zea mays L. (Corn) and Sorghum bicolor (L.) Moench (Grain Sorghum). Sandstone ridges with 15–30% northwest-facing slopes 365–490 m in elevation characterize the topography of CSF. The majority of the soils on the study area are classified in the Clarksville-Fullerton-Claiborne association. Temperatures range from a yearly average high of 20.4 °C to a yearly average low of 7.9 °C. The area receives approximately 120-cm of rain per year (National Oceanic 2012 M.A. Lashley and C.A. Harper 701 and Atmospheric Administration 2008). However, 2007 was the driest year on record with a departure of -38 cm for the year and a departure of -22 cm for April–September (National Oceanic and Atmospheric Administration 2008). Surveys conducted by the TWRA estimated 10–12 Deer per km2, and herd management includes a draw-hunt system following state regulations. The average annual Deer harvest at CSF has been 3–4 Deer per km2 since 2005 (TWRA 2009). Methods Species selection We used 50-m line transects to determine plant selection by Deer at CSF during mid-August of 2007 and 2008. Two transects were randomly placed in all 4 stands. Each transect was sampled at 3 systematically located plots. Plot centers were located at 10, 25, and 40 m along the transect, and we recorded all stems of each species and number of stems browsed in a 1.5-m x 1.2-m x 1.2-m plot (Shaw et al. 2010). We used the structure of damage in remaining forage tissues and the foraging ecology of Deer and other wildlife to distinguish herbivory between wildlife species (Rezendez 1992). We distinguished Deer herbivory from that of Lagomorphs, other small mammals, and insects Figure 1. Chuck Swan State Forest and Wildlife Management Area located in Anderson, Campbell, and Union counties, TN. 702 Southeastern Naturalist Vol. 11, No. 4 by the nature of the bite, considering blunt-tipped bites to be Deer herbivory with angular or wavy bites attributed to other mammals and insects, which were excluded from the survey. Although Shaw et al. (2010) reported herbaceous species were not a significant portion of Deer diet following burning, we included all forages detected in the selection transects regardless of their classification (e.g., grass, forb, semi-woody vines, and woody), and all plants with <5 stems in a year were lumped into a common category within the respective year. Shaw et al. (2010) reported a lack of herbaceous species in closed-canopy stands following burning, herbaceous species were prevalent in our study site, and we included all forages detected in the selection transects regardless of their classification. We calculated a selection index (Chesson index; Chesson 1978, 1983; Lashley et al. 2011; Shaw et al. 2010) by dividing the ratio of use and availability for a given species by the sum of ratios for all species, including all woody, semi-woody, and herbaceous plants. This index generates a value for each species and a cut-off value for comparison. We compared index values for each species to the index cut-off (0.035 in 2007, 0.028 in 2008) to determine selection. Greater cut-off values indicate more stringent guidelines for a resource to be considered selected. Species with a selection rating > the cut-off value were considered selected more than available, while species with 50–99.9% of the cut-off value were considered moderately selected. Moderately selected plants were not considered to be species that were sought-after for consumption, but also were not avoided by Deer. In other words, Deer do not seek out moderately selected plants but may consume them if available. Any plant species below 50% of the cut-off value were considered avoided by Deer and generally not browsed by them. Forage analysis We collected representative samples, including leaves and tender shoots from the current growing season of 19 forages, within each stand on 15 August 2007 and 2008. We chose mid-August to accurately reflect nutritional quality of plants during the late-summer stress period, which is the most stressful period for lactating females because of decreased available nutrition and more stringent nutritional requirements (Verme and Ullrey 1984). We dried all samples to constant mass in an air-flow dryer at 50 °C and ground them using a 1-mm-mesh Wiley mill. We recorded moisture content as a precautionary measure to ensure we did not catalyze the malliard reaction (non-enzymatic browning) when drying the forages. Similar to caramelization, this process could artificially inflate lignin content in the subsequent assay. Forages ranged from 50 to 91% water, and there were no apparent inflations in resulting fiber measurements. Nutrient analyses included crude protein (CP), using the combustion analyzer method (AOCS 1999), and acid detergent fiber (ADF) and neutral detergent fiber (NDF), using ankom fiber determination (AOCS 2005, AOAC 2005), in 2007 and 2008, and were conducted by SURE-TECH™ Laboratories (2435 Kentucky Avenue Indianapolis, IN 46221; SURE-TECH™ Laboratories is certified by the National Forage Testing Association). We considered CP an important metric during the growing season, 2012 M.A. Lashley and C.A. Harper 703 as there is a large protein burden on females during lactation that must be met through their diet rather than body reserves (Sadleir 1987). CP is a measure of proteins in the cell cytoplasm and chloroplasts of plants, but some of the proteins may be unavailable for animal utilization (Ball et al. 2002). Thus, we also measured NDF and ADF, which chemically distinguish the readily available, soluble cell contents from the less digestible cell walls. NDF represents all cell-wall material, while ADF is a measure of only the lignified or otherwise undigestible portions (Ball et al. 2002). We did not consider the role of condensed tannins in compromising the digestibility of CP because recent literature concluded tannins were not a great threat to summer diet quality of Deer in the Southeast (Jones et al. 2010). Data analysis We conducted a two-sampled t-test using SYSTAT to compare nutrient levels within selected forages between years. A separate analysis was conducted on the other species sampled but not selected by Deer. CP, ADF, and NDF values were each averaged by year to assess differences between the drought year and normal year, not to evaluate differences between species within a year or an individual species across years. Results Five woody/shrubs and 1 herbaceous species were selected more than available in the drought year (2007), whereas 6 woody and 2 herbaceous species were selected in the normal rainfall year (2008). Five of the 6 species selected in the drought year were also selected in the normal year, with Cornus florida L. (Flowering Dogwood) being the exception (Table 1). During the drought year, only 1 species was moderately selected compared to 7 species during the normal year (Table 2). In all species collected, CP was negatively affected (P = 0.001), NDF decreased (P = 0.017), and ADF was unaffected by drought (P = 0.204). Both CP (P = 0.285) and ADF (P = 0.922) were unaffected during the drought year within the 6 species selected in both years. NDF was greater during the normal year among these 6 species (P = 0.01). The 13 common species which were not selected in both years showed a different trend than the 6 selected species. CP was negatively affected by drought (P = 0.002), while ADF (P = 0.165) and NDF (P = 0.133) were not affected (Tables 3, 4). Discussion Drought affected nutritional quality among native forages and forage selection by Deer. CP decreased in all plant species evaluated during the drought year with the exception of Nyssa sylvatica Marsh (Blackgum). NDF also decreased in all plant species during the drought year with the exception of Coreopsis spp. (tickseed). Only Desmodium spp. (desmodium) met the nutritional requirements for a lactating doe with one fawn during the drought year, while 7 species met the 704 Southeastern Naturalist Vol. 11, No. 4 requirements during the normal year (14% CP for lactating doe with one fawn; Verme and Ullrey 1984; Table 3). Fewer species were selected and fewer species received moderate use during the drought year, suggesting Deer were less selective of plant parts consumed during the drought year and less selective of plant species during the normal year. Intake may be affected most by physical factors, such as bulkiness (large volume per unit of mass), suggesting our results might have been influenced by intake differences during times of nutritional stress (Verme and Ullrey 1984). In general, voluntary intake of forage in ruminants will increase as NDF of that forage decreases (Mertens 1987). We observed a decrease in NDF in the drought year of the study, indicating forage intake could increase during drought years. Nutritional quality possibly decreased within species because of accelerated plant maturation resulting from drought, and the negative effects of plant maturity on CP content and digestibility are well documented (Ball et al. 2002). However, our data showed ADF was unaffected in any of the species groups Table 1. Forages selected and/or important deer foods at Chuck Swan State Forest and Wildlife Management Area, August 2007–2008. T = total, B = bites, D.i. = drought index, N.i. = normal index. Drought Normal Change from normal year year to drought years T B T B D.i. N.i. CP ADF NDF Selected species Nyssa sylvatica Marsh A (Blackgum) 10 3 23 14 0.12 0.10 1.37 0.04 -41.9 Desmodium spp.A (desmodium) 9 3 11 8 0.14 0.12 -9.20 5.11 -17.3 Smilax spp.A (greenbrier) 113 64 84 49 0.23 0.10 -1.80 4.03 -20.9 Euonymous americana L. A 9 7 5 4 0.32 0.13 -1.35 -11.00 -14.9 (Strawberrybush) Vitis spp.A (grape) 197 33 139 63 0.07 0.08 -3.95 -3.02 -4.13 Rubus spp.B (blackberry) - - 22 12 - 0.09 -3.04 -0.95 -1.32 Cornus florida L.B (Flowering Dogwood) 19 2 23 3 0.04 0.02 -9.53 -9.17 -12.2 Parthenocissus quinquefolia PlanchB 213 6 151 35 0.01 0.04 -3.19 4.44 -7.75 (Virginia Creeper) Dioscorea villosa L. B (Wild Yam) - - 25 14 - 0.09 -3.74 -14.40 -30.8 Non-selected speciesC Prunus serotina Ehrhart (Black Cherry) 9 0 32 1 0 0.01 -3.31 -10.40 -18.6 Vaccinium spp. Aiton (Blueberry) 98 8 - - 0.03 - -1.45 2.40 -1.05 Acer spp. (maple) 210 6 194 19 0.01 0.02 -3.06 1.30 -5.48 Quercus spp. (oak) 54 1 65 3 0.01 0.01 -9.36 -3.25 -10.1 Sassafras albidum Nuttall (Sassafras) 31 0 31 4 0 0.02 -2.44 -9.81 -23.5 Liriodendron tulipifera L. (Yellow Poplar) 21 0 15 2 0 0.02 -1.86 -5.80 -16.2 Phytolacca americana L. - - - - - - -18.80 -0.60 -1.46 (American Pokeweed) Dicanthelium spp.(low panicgrass) - - - - - - -3.94 -3.97 -1.22 Oxydendron arboreum de Condolle - - - - - - -2.06 -6.42 -9.22 (Sourwood) Coreopsis spp. (tickseed) - - - - - - -3.26 -1.21 13.33 AForages selected in both years of the study. BForages selected in one year of the study. CForages not selected, but reported as important Deer forages in the literature. 2012 M.A. Lashley and C.A. Harper 705 analyzed. Lashley et al. (2011) reported significant decreases in available CP and increased lignin content in Maturity Group 4 soybeans, and a shorter duration to hard seed during the drought year. That finding was consistent with other literature evaluating the effects of drought-induced stress on annual and perennial forage legumes (Carter and Sheafer 1983, Peterson et al. 1992), but it is unclear why ADF in our study did not conform to the same trends within the literature. Our data support the selective-quality hypothesis (Weckerly and Kennedy 1992) derived from the feeding strategies of Damaliscus korrigum Burchell (Topi; Jarman and Sinclair 1979). Deer were less selective when resources were abundant, which supports the findings of Weckerly and Kennedy (1992). Some species (e.g., Smilax sp. [greenbrier], Cornus florida, etc.) showed a shift in the magnitude of selection, whereas other forages, such as Parthenocissus quinquefolia (L.) Planch (Virginia Creeper), were avoided in the drought year even though they were more abundant. Some herbaceous species, such as desmodium, were browsed less in the drought year despite an increase in abundance. The selection cut-off in the drought year was much greater than in the normal year. According to the Chesson index, heavier selection on fewer species will increase the index value, so species must meet more stringent guidelines to qualify as selected (Chesson 1978, 1983). Also, the number of selected species and the number of plants receiving moderate use was greater in the normal year, indicating Deer were less selective of species because more plants met the nutritional Table 2. Magnitude of selection of forages at Chuck Swan State Forest and Wildlife Management Area 2007–2008. T = total, B = bitten, % = % cut off. Drought year Normal year T B Index % A T B Index % A Selected species Euonymous americana (Strawberrybush) 9 7 0.32 914.91 5 4 0.13 473.25 Vitis spp. (grape) 9 3 0.14 392.11 11 8 0.12 430.23 Nyssa sylvatica (Blackgum) 10 3 0.12 352.89 23 14 0.10 360.08 Smilax spp. (greenbrier) 113 64 0.23 666.23 84 49 0.10 345.08 Dioscorea villosa (Wild Yam) - - - - 25 14 0.09 331.28 Rubus spp. (blackberry) - - - - 22 12 0.09 322.67 Desmodium spp. (desmodium) 197 33 0.07 197.05 139 63 0.08 268.12 Cornus floridaB (Flowering Dogwood) 19 2 0.04 123.82 23 3 0.02 77.16 Parthenocissus quinquefolia 213 6 0.01 33.14 151 35 0.04 137.12 (Virgininia Creeper) Moderately selected Fagus americanus (American Beech) 9 0 0 0 7 1 0.02 84.51 Liliaceae spp. (lilly) 23 0 0 0 37 5 0.02 79.94 Lireodendron tulipifera (Yellow Poplar) 21 0 0 0 15 2 0.02 78.88 Sassafras albidum (Sassafras) 31 0 0 0 31 4 0.02 76.33 Toxicodendron radicans Kuntze 40 0 0 0 40 4 0.02 59.16 (Poison Ivy) Acer spp. (maple) 210 6 0.01 33.61 194 19 0.02 57.94 AIndicates magnitude of selection. Greater values indicate greater selection. BSpecies only selected more than available in one year of the study. 706 Southeastern Naturalist Vol. 11, No. 4 Table 3. Discrete nutritional values for selected and important Deer foods in drought and normal rainfall years at Chuck Swan State Forest and Wildlife Management Area, August 2007–2008. Drought year Normal year CP ADF NDF CP ADF NDF Selected species Nyssa sylvaticaA (Blackgum) 12.61 17.84 23.82 11.24 17.80 65.69 Desmodium spp.A (desmodium) 16.95 32.53 40.90 20.90 35.55 45.03 Smilax spp.A (greenbrier) 10.85 28.23 39.76 12.65 24.20 60.64 Euonymous americanaA (Strawberrybush) 9.71 26.29 27.57 11.06 37.27 42.51 Vitis spp.A (Wild Grape) 10.96 30.05 30.45 20.16 24.94 47.79 Rubus spp.B (blackberry) 10.08 23.87 28.81 13.12 24.82 30.13 Cornus floridaB (Flowering Dogwood) 8.52 14.98 17.20 18.05 24.15 29.44 Parthenocissus quinquefoliaB 11.23 29.97 28.36 14.42 25.53 36.11 (Virgininia Creeper) Dioscorea villosaB (Wild Yam) 10.02 31.25 37.96 13.76 45.61 68.74 Non-selected speciesC Prunus serotina (Black Cherry) 9.93 24.38 26.14 13.24 34.75 44.75 Vaccinium spp. (blueberry) 7.76 35.55 37.75 9.21 33.15 38.80 Acer spp.(maple) 7.81 28.00 30.82 10.87 26.70 36.30 Quercus spp. (oak) 10.20 30.97 37.74 19.56 34.22 47.84 Sassafras albidum (Sassafras) 11.34 33.79 61.79 13.78 43.60 85.24 Lireodendron tulipifera (Yellow Poplar) 10.60 32.42 33.44 12.46 38.22 49.61 Phytolacca americana (American Pokeweed) 11.06 11.24 20.59 29.81 11.84 22.05 Dicanthelium spp. (low panicgrass) 10.73 32.67 56.18 14.67 36.64 57.40 Oxydendron arboreum (Sourwood) 9.48 19.48 26.03 11.54 25.90 35.25 Coreopsis spp. (tickseed) 7.58 30.55 40.41 10.84 31.76 27.08 AForages selected in both years of the study. BForages selected in one year of the study. CForages not selected but reported as important Deer forages in the literature. Table 4. Nutritional quality of Deer foods in drought and normal rainfall years at Chuck Swan State Forest and Wildlife Management Area, August 2007–2008. Drought year Normal year Mean SE Mean SE All speciesA Crude protein 10.5 0.47 14.8 1.08 Acid detergent fiber 27.4 1.53 30.5 1.88 Neutral detergent fiber 35.2 2.73 46.4 3.56 SelectedB Crude protein 11.47 1.28 14.2 2.05 Acid detergent fiber 28.41 2.50 28.82 3.13 Neutral detergent fiber 31.38 2.89 50.08 4.36 Non-selectedC Crude protein 9.89 0.34 15.09 1.41 Acid detergent fiber 26.43 2.00 31.06 2.54 Neutral detergent fiber 34.27 3.57 43.84 5.01 AIncludes all 19 species collected in the study. BIncludes only the 5 species selected in both years of the study. CIncludes the 14 species that were not selected in both years of the study. 2012 M.A. Lashley and C.A. Harper 707 requirements of Deer. Nine percent of stems detected during the drought year showed evidence of herbivory, while 18% did during the normal year, and the average % cut-off for selected species in the drought year (441.17) was greater than during the normal year (333.48), further suggesting Deer focused diet selection on fewer plants during drought (Tables 1, 2). Deer likely were more selective of plant species rather than plant parts, selecting fewer species more aggressively during the drought. This finding was illustrated in our data by heavier selection on greenbrier during the drought year when other plants were nutritionally insufficient even though the relative abundance was greater. With less abundant tender shoots and leaves, as in extreme drought, Deer must become more selective of plant species consumed and thus dependent on fewer plant species to meet their late growing-season nutritional requirements. Harlow and Hooper (1972) found Deer actively seek out particular plants and plant parts within each season. Their findings were consistent within hundreds of rumens from many physiographic regions across the southeastern US (Johnson et al. 1995). Global climate change has become a topic of interest and could have implications in diet selection and forage quality across the range of Deer. If climatic conditions, such as drought, become more frequent and intense (Easterling et al. 2000), our data suggest recruitment within local Deer populations and persistence of commonly eaten Deer forages could be impacted. Without foods to support lactation, recruitment could decrease during drought years as a result of neonate starvation, which is already a common source of mortality in ungulate neonates in the Southwest in drought years (Carrol and Brown 1977, Pojar and Bowden 2004). Furthermore, commonly eaten plant species could be reduced by intense herbivory because of changes in diet selection during drought years (Rossel et al. 2005). The effects of Deer on the understory strata have been reported in the literature in areas where Deer exceed NCC (Casey and Hein 1983, de Calesta 1994), but our data suggest intense browsing could be exacerbated by drought in areas where Deer densities otherwise would not exceed NCC. Management implications Drought played a key role in the nutritional quality and selection of plants by Deer during the late-summer stress period. Managers should be aware of the potential effects of drier conditions on NCC for Deer and should consider how Deer density might need to be adjusted to offset reductions in forage quality. Further investigation is warranted on how climate change may affect the ecology of Deer and associated plant and animal communities in the Southeast. Acknowledgments We thank the University of Tennessee—Department of Forestry, Wildlife, and Fisheries, National Wild Turkey Federation, Tennessee Division of Forestry, and Tennessee Wildlife Resources agency for their contributions to this research. We acknowledge logistic and technical support provided by T. Daily, D. Baily, D. Hall, C. Chitwood, and B. Sherrill. We thank M. McCord, C. Shaw, and numerous field technicians for assistance with data collection. 708 Southeastern Naturalist Vol. 11, No. 4 Literature Cited American Oil Chemist Society (AOCS). 1999. Official methods and recommended practices of the AOCS, 5th Edition. The Association, Champaign, IL: Method Ba4e-93. AOCS. 2005. Official Methods and Recommended Practices of the AOCS. 11th Edition. The Association, Champaign, IL: Method Ba6a-05. Anderson, R.C., and A.J. Katz. 1993. Recovery of browse-sensitive tree species following release from White-tailed Deer Odocoileus virginianus Zimmerman browsing pressure. Biological Conservation 63:203–208. Anthony, R.G. 1976. Influence of drought on diets and numbers of desert deer. Journal of Wildlife Management 40:140–144. Association of Analytical Chemists (AOAC). 2005. Official methods of analysis of AOAC international, 18th Edition. AOAC international, Gaithersburg, MD: 990.03. Ball, D.M., C.S. Hoveland, and G.D. Lacefield. 2002. Southern Forages. Third Edition. Potash and Phosphate Institute and the Foundation for Agronomic Research, Norcross, GA. Beck, D.E., and R.F. Harlow. 1981. Understory forage production following thinning in Southern Appalachian cove hardwoods. Proceedings Annual Conference Southeastern Association of Fish and Wildlife Agencies 35:185–196. Blake, P.M., G.A. Hurst, and T.A. Terry. 1987. Response of vegetation and deer forage following application of hexazinone. Southern Journal of Applied Forestry 11:176– 180. Brose, P.H., and D.V. Lear. 1999. Effects of seasonal prescribed fire on residual overstory trees in oak-dominated shelterwood stands. Southern Journal of Applied Forestry 23:88–93. Carrol, B.K., and D.L. Brown. 1977. Factors affecting neonatal fawn survival in southern- central Texas. Journal of Wildlife Management 41:63–69. Carter, P.R., and C.C. Sheaffer. 1983. Alfalfa response to soil water deficits. I. Growth, forage quality, yield, water use, and water-use efficiency. Crop Science 23:669–675. Casey, D., and D. Hein 1983. Effects of heavy browsing on a bird community in deciduous forest. Journal Wildlife Management 47:829–836. Chamberlain, M.J., and D.A. Miller. 2006. Effects of two site preparation techniques on biomass of forage plants for White-tailed Deer in eastern Louisiana. Proceedings of the Annual Conference Southeastern Association of Fish and Wildlife Agencies 60:64–69. Chesson, J. 1978. Measuring preference in selective predation. Ecology 59:211–215. Chesson, J. 1983. The estimation and analysis of preference and its relationship to foraging models. Ecology 64:1297–1304. de Calesta, D.S. 1994. Effects of White-tailed Deer on songbirds within managed forests in Pennsylvania. Journal of Wildlife Management 58:711–718. Easterling, D.R., G.A. Meehl, C. Parmesan, S.A. Changnon, T.R. Karl, and L.O. Mearns. 2000. Climate extremes: Observations, modeling, and impacts. Science 289:2068–2074. Edwards, S.L., S. Demarais, B. Watkins, and B.K. Strickland. 2004. White-tailed Deer forage production in managed and unmanaged pine stands and summer food plots in Mississippi. Wildlife Society Bulletin 32:739–745. Harlow, R.F., and R.G. Hooper. 1972. Forages eaten by deer in the Southeast. Southeastern Association of Game and Fish Commission Annual Conference Proceedings 25:18–46. 2012 M.A. Lashley and C.A. Harper 709 Jarmin, P.J., and A.R.E. Sinclair. 1979. Feeding strategy and the pattern of resource partitioning in ungulates. Pp.130–163, In A.R.E. Sinclair and M. Norton-Griffiths (Eds.). Serengeti: Dynamics of an Ecosystem. University of Chicago Press. Chicago, IL. Johnson, A.S., P.E. Hale, W.M. Ford, J.M. Wentworth, J.R. French, O.F. Anderson, and G.B. Pullen. 1995. White-tailed Deer foraging in relation to successional stage, overstory type, and management of Southern Appalachian forests. American Midland Naturalist 133:18–35. Jones, P.D., S.L. Edwards, and S. Demarais. 2009. White-tailed Deer foraging habitat in intensively established Loblolly Pine plantations. Journal of Wildlife Management 73:488–496. Jones, P.D., B. Rude, J.P. Muir, S. Demarais, B.K. Strickland, and S.L. Edwards. 2010. Condensed tannins’ effect on White-tailed Deer forage digestibility in Mississippi. Journal of Wildlife Management 74:707–713. Lashley, M.A., C.A. Harper, G.E. Bates, and P.D. Keyser. 2011. Forage availability for White-tailed Deer following silvicultural treatments in hardwood forests. Journal of Wildlife Management 75:1467–1476. Lawrence, R.K., S. Demarais, R.A. Relyea, S.P. Haskell, W.B. Ballard, and T.L. Clark. 2004. Desert Mule Deer survival in southwest Texas. Journal of Wildlife Management 68:561–569. Masters, R.E., R.L. Lochmiller, and D.M. Engle. 1993. Effects of timber harvest and prescribed fire on White-tailed Deer forage production. Wildlife Society Bulletin 21:401–411. McCullough, D.R. 1985. Variables influencing food habits of White-tailed Deer on the George Reserve. Journal of Mammology 66:682–692. Mertens, D.R. 1987. Predicting intake and digestibility using mathematical models of ruminal function. Journal of Animal Science 64:1548–1558. Miller, K.V. 2001. White-tailed Deer. Pp. 95–107, In J.G. Dickson (Ed.). Wildlife of Southern Forests: Habitat and Management. Hancock House Publishers, Blaine, WA. Miller, K.V., and J.H. Miller. 2004. Forestry herbicide influences on biodiversity and wildlife habitat in southern forests. Wildlife Society Bulletin 32:1049–1060. Mixon, M.R., S. DeMarais, P.D. Jones, and B.J. Rude. 2009. Deer forage response to herbicide and fire in mid-rotation pine plantations. Journal of Wildlife Management 73:663–668. National Oceanic and Atmospheric Administration. 2008. Climates of the states, climatology of the US, Number 60, National Climate Data Center, NOAA, Department of Commerce, Washington, DC. Pojar, T.M., and D.C. Bowden. 2004. Neonatal Mule Deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550–560. Peitz, D.G., M.G. Shelton, and P.A. Tappe. 2001. Forage production after thinning a natural Loblolly Pine-hardwood stand to different basal areas. Wildlife Society Bulletin 29:697–705. Peterson, P.R., C.C. Sheaffer, and M.H. Hall. 1992. Drought effects on perennial forage legume yield and quality. Agronomy Journal 84:774–779. Rezendez, P. 1992. Tracking and the Art of Seeing: How to Read Animal Tracks and Sign. Camden House, Charlotte, VT. 320 pp. Rossell, C.R., Jr., B. Gorsira, and S. Patch. 2005. Effects of White-tailed Deer on vegetation structure and woody seedling composition in three forest types on the Piedmont Plateau. Forest Ecology and Management 210:415–424. 710 Southeastern Naturalist Vol. 11, No. 4 Rossell, C.R., Jr., S. Patch, and S. Salmons. 2007. Effects of deer browsing on native and non-native vegetation in a mixed oak-beech forest on the Atlantic coastal plain. Northeastern Naturalist 14:61–72. Sadleir, R.M.F.S. 1987. Reproduction of female cervids. Pp. 123–144, In C.M. Wemmer (Ed.). Biology and Management of the Cervidae. Smithsonian Institution Press, Washinghton, DC. Shaw, C.E., C.A. Harper, M.W. Black, and A.E. Houston. 2010. Initial effects of prescribed burning and understory fertilization on browse production in closed-canopy hardwood stands. Journal of Fish and Wildlife Management 1:64–71. Tennessee Wildlife Resources Agency (TWRA). 2009. Big game harvest report 2005– 2009. Technical Report 09-01.299. Nashville, TN. Tilghman, N.G. 1989. Impacts of White-tailed Deer on forests regeneration in northwestern Pennsylvania. Journal of Wildlife Management 53:524–532. US Fish and Wildlife Service and US Department of Commerce, Bureau of the Census. 1993. 1991 National survey of fishing, hunting, and wildlife-associated recreation: Virginia. US Government printing office, Washington, DC. Verme, L.J., and D.E. Ullrey. 1984. Physiology and nutrition. Pp. 91–118, In L.K. Halls (Ed.). White-tailed Deer: Ecology and Management. Stackpole, Harrisbur g, PA. Warren, R.C., and G.A. Hurst. 1981. Ratings of plants in pine plantations as White-tailed Deer food. Mississippi Agricultural and Forestry Experiment Station, Information Bulletin 18. Webster, C.R., M.A. Jenkins, and J.H. Rock. 2005. Long-term response of spring flora to chronic herbivory and deer exclusion in Great Smoky Mountains National Park, USA. Biological Conservation 125:297–307. Weckerly, F.W., and M.L. Kennedy. 1992. Examining hypotheses about feeding strategies of White-tailed Deer. Canada Journal of Zoology 70:432–439. Wood, G.W. 1988. Effects of prescribed fire on deer forage and nutrients. Wildlife Society Bulletin 16:180–186.