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.
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 - email@example.com.
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.
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).
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.
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
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.
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
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).
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
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
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
Dioscorea villosa L. B (Wild Yam) - - 25 14 - 0.09 -3.74 -14.40 -30.8
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
Dicanthelium spp.(low panicgrass) - - - - - - -3.94 -3.97 -1.22
Oxydendron arboreum de Condolle - - - - - - -2.06 -6.42 -9.22
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
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
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
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
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
Dioscorea villosaB (Wild Yam) 10.02 31.25 37.96 13.76 45.61 68.74
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
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
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
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.
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.
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
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,
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–
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
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
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
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
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
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
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
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
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
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
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,
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
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