nena masthead
SENA Home Staff & Editors For Readers For Authors

Soil Region Effects on White-tailed Deer Forage Protein Content
Phillip D. Jones, Stephen Demarais, Bronson K. Strickland, and Scott L. Edwards

Southeastern Naturalist, Volume 7, Number 4 (2008): 595–606

Full-text pdf (Accessible only to subscribers.To subscribe click here.)


Access Journal Content

Open access browsing of table of contents and abstract pages. Full text pdfs available for download for subscribers.

Issue-in-Progress: Vol. 22 (2) ... early view

Current Issue: Vol. 21 (4)
SENA 21(3)

All Regular Issues


Special Issues






JSTOR logoClarivate logoWeb of science logoBioOne logo EbscoHOST logoProQuest logo

2008 SOUTHEASTERN NATURALIST 7(4):595–606 Soil Region Effects on White-tailed Deer Forage Protein Content Phillip D. Jones1,*, Stephen Demarais1, Bronson K. Strickland1, and Scott L. Edwards2 Abstract - Body mass and antler development of Odocoileus virginianus (Whitetailed Deer) vary by soil resource region in Mississippi, but a causative link from soil to deer morphology has not been established. We investigated crude protein (CP) content of 8 important deer forages in 5 soil-resource regions to determine if regional differences in available nutrition could potentially explain some variation in morphometrics. Crude protein levels of a species composite and all but 1 individual forage species decreased from spring to summer. Every species exhibited regional differences in spring, and only 1 species did not vary by region in summer. Composite CP also differed by region. Differences in potential nutritional planes among regions may be substantial enough to impact lactation success, fawn recruitment, and body growth. Directly sampling seasonal diet quality among regions and comparing nutritional planes among deer herds of different densities may further explain regional morphometric differences. Introduction Mississippi is commonly divided into 10 soil-resource regions based on differences in soils, topography, and climate (Pettry 1977). Odocoileus virginianus Zimmerman (White-tailed Deer; hereafter, “deer”) differ in body mass and antler development among soil-resource regions (Jacobson 1984; Strickland and Demarais 2000, 2006), but a direct nutritional link via forage quality has not been established. Soil fertility is correlated with plant biomass production (Biere 1995, Chapin 1980, Fraser and Grime 1998), and mineral soil richness is correlated with deer body mass (Jacobson 1984, Smith et al. 1975a). Factors other than soil fertility, however, can impact nutrition levels and thus development in deer. Higher herd densities may lead to reduced diet quality as deer are forced to consume less nutritious forage (Kie et al. 1980); management actions which favor more nutritious plants may increase the nutritional plane without altering the quality of individual plant species (Jones 2008). Different soils infl uence protein levels of deer forages (Hundley 1959, Kreuger and Donart 1974, Pettorelli et al. 2001, Thorsland 1966). The purpose of our study was to determine whether several common deer forages differed in crude protein (CP) content among sites in 5 soil regions in Mississippi differing in fertility (Jacobson 1984, Pettry 1977) and deer 1Forest and Wildlife Research Center, Box 9690, Mississippi State, MS 39762. 2Mississippi Department of Wildlife, Fisheries and Parks, Box 9690, Mississippi State, MS 39762. *Corresponding author - 596 Southeastern Naturalist Vol. 7, No. 4 morphometrics (Strickland and Demarais 2000). If basic differences in forage quality do occur among regions, they might partly account for differences in body size and antler development associated with these regions. Site Description We collected forage plant samples from 4 state Wildlife Management Areas (WMAs), and 3 private properties representing 5 soil regions (Fig. 1). We chose these regions to correspond with Strickland and Demarais’ (2000) study of regional deer morphometrics in Mississippi. Delta samples were taken from Sunflower WMA in Sharkey County, where the Sharkey-Alligator-Dowling soil association was ubiquitous in coverage. The Upper Thick Loess (Thick Loess) samples were collected on Figure 1. Sites (􀁏) sampled for deer forage plant quality in 5 soil resource regions of Mississippi during spring and summer 2006. 2008 P.D. Jones, S. Demarais, B.K. Strickland, and S.L. Edwards 597 Malmaison WMA in Grenada and Carroll counties on areas dominated by Memphis association soils. Upper Thin Loess (Thin Loess) samples were collected on private property in Attala County; Gillsburg soils were prominent on lower slopes, Hills-Providence soils on uplands. The Upper Coastal Plain (UCP) samples were collected on Choctaw WMA in Choctaw and Winston counties. Soil associations included a variety of sandy, silt, and clay loams, including Susquehanna, Ruston, Pheba, and Collins. The Lower Coastal Plain (LCP) samples were collected on Wolf River WMA and two industrial forest sites in Lamar, Perry, and George counties. Soils included the McLaurin-Heidel-Prentiss, McLaurin-Savannah-Susquehenna, and Prentiss-Rossella-Benndale associations. Methods We selected 8 forage species important to deer in Mississippi (Warren and Hurst 1981), representative of vines, forbs, and browse which we expected to be available statewide. We collected 5 independent sets of samples of each species found from each study site in spring (April) and summer (18 July–15 August) 2006. Sites were sampled in order of average date of last spring freeze. Each set of samples included enough plant material to yield ≥50 g wet weight per species. Samples included all leaves and growing stem tips from selected plants. We selected individual plants with little or no evidence of depredation or disease. Samples were not collected from locations where fertilizer may have been recently used, such as food plots or agricultural fields. We dried samples in a forced-air oven for 72 hours at 60 ºC, then tested for CP on a dry-matter basis using the Kjeldahl procedure (Helrich 1990). We compared species individually, both by regions and between seasons, and by season and among regions, using 2-way analysis of variance with PROC MIXED (SAS Institute 2000). We also averaged CP across species successfully collected at all 5 sites within each season to create a composite CP, which we tested for overall effects of region and season using 2-way analysis of variance with PROC MIXED (SAS Institute 2000). We tested assumptions of homogeneity of variance before each analysis and used heterogeneous variance models that accounted for differing variances among fixed effects when necessary (Littell et al. 2006). We used LSMEANS SLICE to identify region effects within seasons and season effects within regions following a significant interaction (Littell et al. 2006). When differences were found, we conducted pair-wise tests using Fisher’s protected LSD (Carmer and Swanson 1973, Peterson 1985). We considered differences significant if P ≤ 0.05. Results We successfully collected 6 of 8 species on all sites and in both seasons; 1 species was collected on 4 sites, and 1 other on 2 sites (Table 1). Seven 598 Southeastern Naturalist Vol. 7, No. 4 Table 1. Crude protein content (SE) of selected White-tailed Deer forages in 5 soil regions of Mississippi collected in 2006. P-valuesA Site Season x Species Season Delta Thick Loess Thin Loess UCPB LCPB RegionC region Campsis radicans Seemann Spring 24 ABD (2) 27 A (1) 16 C (1) 26 A (1) 22 B (1) <0.001 <0.001 (Trumpet Creeper) Summer 12 BE (0) 11 B (1) 9 C (1) 17 A (2) 8 C (0) <0.001 Lonicera japonica Thunberg Spring 14 A (0) 13 BC (0) 12 CD (1) 12 D (0) 14 AB (0) <0.001 <0.001 (Japanese Honeysuckle) Summer 15 AE (0) 8 BE (0) 8 BE (0) 9 BE (1) 8 BE (1) <0.001 Rubus trivialis Michaux Spring 18 A (0) 18 A (1) 15 B (1) 16 AB (1) 18 A (1) 0.002 0.001 (Southern Dewberry) Summer 10 AE (0) 10 ABE (1) 11 AE (1) 9 BCE (0) 8 CE (0) <0.001 Smilax glauca Walter Spring 21 A (1) 24 A (1) 15 B (2) 19 B (0) 11 C (0) <0.001 <0.001 (Sawbrier) Summer 10 BE (0) 10 AE (0) 9 BCE (0) 10 ABE (0) 9 CE (0) 0.011 Ambrosia artemisiifolia Linnaeus Spring 20 B (1) 21 B (1) 26 A (1) 22 B (2) 23 AB (1) 0.004 0.029 (Common Ragweed) Summer 20 (1) 21 (0) 20 e (2) 20 (1) 20E (1) 0.844 Desmodium ciliare Willdenow Spring 24 A (2) 18 B (1) <0.001 0.629 (Tickclover) Summer 20 AE (1) 14 BE (0) Phytolacca americana Linnaeus Spring 30 C (1) 37 A (1) 28 C (1) 34 B (0) 24 D (1) <0.001 <0.001 (Pokeweed) Summer 21 BE (1) 26 AE (1) 27 A (2) 23 BE (1) 22 B (1) <0.001 Vaccinium arboreum Marshall Spring 21 A (1) 8 C (0) 13 B (1) 12 B (0) <0.001 <0.001 (Sparkleberry) Summer 8 AE (0) 7 AB (0) 7 BCE (0) 6 CE (0) <0.001 AP-values correspond to least-square means. Degrees of freedom for Trumpet Creeper, Japanese Honeysuckle, Dewberry, Sawbrier, Ragweed, and Pokeweed were: Region = 4,40, Season = 1,40, Interaction = 4,40; for Tickclover: Region = 1,16, Season = 1,16, Interaction = 1,16; for Sparkleberry Region = 3,32, Season = 1,32, Interaction = 3,32. BUCP = Upper Coastal Plain, LCP = Lower Coastal Plain. CWhen Season×Region is significant, Region P-values are for within-region comparisons. DMeans within a row followed by the same letter are not different (α = 0.05). ESeasonal effect within region (α ≤ 0.05). 2008 P.D. Jones, S. Demarais, B.K. Strickland, and S.L. Edwards 599 species showed region x season interactions; Desmodium ciliare (Tickclover) showed differences due to both region and season. In spring, CP differed among regions for all species; in summer, all species except Ambrosia artemisiifolia (Ragweed) showed regional differences. In spring, 5 of 7 species collected from the Thick Loess were ranked in the group with the highest CP, followed by 4 of 6 in the Delta, 4 of 8 in the UCP, 3 of 8 in the LCP, and 1 of 7 in the Thin Loess. In summer, the Thick Loess placed 5 of 7 species in the highest grouping, followed by 4 of 7 in the Thin Loess, 3 of 6 in the Delta, and 4 of 8 in UCP. The LCP placed only Ragweed in the highest CP grouping, and had the numerically lowest CP in 6 of 8 species. Most species decreased in CP from spring to summer, though not necessarily across all sites (Table 1). Ragweed decreased at 2 of 5 sites; Phytolacca americana (Pokeweed) 3 of 5, and Vaccinium arboreum (Sparkleberry) at 3 of 4. Lonicera japonica (Japanese Honeysuckle) increased by 1% CP in the Delta and decreased in all other regions by a mean of 4.5% CP. All other species showed consistent decreases from spring to summer on every site from which they were collected. Composite CP was affected by season (F1,290 = 77.60, P ≤ 0.001; Table 2). Spring composite CP averaged 1.5 times greater than summer (range = 1.3–1.6), refl ecting an average decrease of 6.6% CP (range = 4.6–8.7% CP) from spring to summer. Region affected composite CP (F4,290 = 2.94, P = 0.021) consistently across seasons (F4,290 = 0.62, P = 0.647). The Thick Loess provided the highest CP level, the LCP the lowest, differing by 3.5% CP. Discussion Although digestible energy (DE) is a possible limiting factor for deer (Meyer et al. 1984, Parker et al. 1999), we elected to test CP because of lower reported nutritional carrying capacity estimates for diets based on CP requirements than on DE requirements in the Mississippi Lower Coastal Plain (Jones 2008). Nitrogen requirements for growth (French et al. 1956, Table 2. Composite crude protein levels of 6 deer forage species common to 5 soil resource regions in Mississippi, 2006. Region Thick Thin Season Delta LCPA UCPA Loess Loess All Spring Mean 21 19 21 23 19 21 (SE) (1) (1) (1) (1) (1) (1) Summer Mean 15 12 15 15 14 14 (SE) (1) (1) (1) (1) (1) (1) Combined Mean 18 BCB 16 C 18 AB 19 A 16 BC (SE) (1) (1) (1) (1) (1) AUCP = Upper Coastal Plain, LCP = Lower Coastal Plain. BMeans within a row followed by the same letter are not different (α = 0.05). 600 Southeastern Naturalist Vol. 7, No. 4 Holter et al. 1979, McEwen et al. 1957, Ullrey et al. 1967) and antler development (Asleson 1996) are well documented in the literature. Additionally, body mass of deer in Oklahoma was reported as greater in areas with greater dietary nitrogen (Soper et al. 1993). We assumed that composite CP value represented potential forage quality within each region. Deer are selective foragers (Cote et al. 2004, Crawford 1982, Weckerly and Kennedy 1992) capable of discriminating among forages to meet nutritional requirements (Berteaux et al. 1998, Vangilder et al. 1982). While our samples did not account for all possible forages, we believe they are indicative of real differences among soil regions, especially since the composites used identical species across all regions. The range from 16–19% composite CP could potentially impact nutritional plane and habitat quality for White-tailed Deer and may partly explain the variation in deer morphometrics among soil-resource regions reported by Strickland and Demarais (2000). Deer may select forest clearings with greater biomass of high-quality forage (Beckwith 1964) even if overall forage biomass is less than other areas (Stewart et al. 2000). Greater availability of high-quality forage combined with selective foraging could potentially overcome reduced composite CP where deer herds are well below carrying capacity. However, access to alternative forages would be limited in herds at or near carrying capacity (Kie et al. 1980). The Thick Loess site appeared to produce the highest potential nutritional plane, followed by the UCP, Delta, Thin Loess, and LCP. Strickland and Demarais (2000) reported greater body weights and antler development in the Delta, followed by the loess regions, the UCP, and the LCP. They assumed this pattern was related to regional variation in soil fertility. The discrepancy between their rankings of morphometrics and ours of potential nutritional plane might be explained in that models explaining deer growth and antler size in these regions often contained a positive correlation with the nearby acreage of agricultural fields (Strickland 2005), an abundant source of high-quality forage. The Delta is the most heavily agricultural region in Mississippi, containing about 44% of the state’s total cropland (National Agricultural Statistics Service 2004), so it is likely deer diets in the Delta are infl uenced by agricultural crops. Comparisons of deer body measurements and soils in Missouri found deer from prairie soil regions were heavier and consumed greater amounts of cultivated crops than deer from other regions (Murphy and Porath 1969), and that antler characteristics were positively correlated with area of harvested cropland (Kissell et al. 2002). Additionally, Strickland and Demarais (2000) combined the 2 loess regions into a single entity; averaging our results for those regions might reasonably result in the same order as theirs. Seasonal differences in CP are common among deer forages (Fuller 1980, Meyer and Brown 1985, Smith et al. 1956, Thorsland 1966), and our 2008 P.D. Jones, S. Demarais, B.K. Strickland, and S.L. Edwards 601 results reflect predictable seasonal growth cycles (Chapin 1980, Mattson 1980). Protein levels fell in nearly all forages from spring to summer, reducing but not eliminating regional differences in composite CP. Because our samples were limited to 1 spring and 1 summer sample, it is possible that species were not always sampled at either their greatest or lowest CP within each region. If not, it is possible that seasonal differences may be either greater or lesser than what we detected. However, we sampled in accordance with long-term weather data such that spring samples were taken in order of average latest freeze date, and followed the same order for summer sampling. Thus, species were sampled at similar phenological stages among regions. Comparing seasonal protein needs with seasonal protein levels in forage reveals potential deficiencies, especially in the LCP. Fawning dates in Mississippi range from late June to early September (Jacobson et al. 1979), making does dependent on summertime forage to provide nutritional requirements for lactation. A diet level of 14% CP is minimal for lactating does (Murphy and Coates 1966, Verme and Ullrey 1984). On the LCP site, this need could only be met by foraging more selectively on higher quality plants which exhibited summer CP values ≥14%, such as Pokeweed, Tickclover, and Common Ragweed; does on sites in the other 4 soil regions could afford to forage more generally and still maintain sufficiently high diet quality. Average fetal rates of does ≥2.5 years old do not differ among regions (B.K. Strickland, unpubl. data); however, data from 4 Mississippi WMAs showed fawn recruitment on the LCP site to be less than half that in the Delta and Upper Thick Loess sites (McDonald 2003). Deficiencies in summertime nutrition for lactating does may impact fawn survival and limit their recruitment in the LCP. Growth potential for young deer may also be infl uenced by regional forage quality. Fawns require from 15–25% CP for optimal growth (French et al. 1956, Smith et al. 1975b, Ullrey et al. 1967). All sites had springtime CP levels within this range (Table 3); however, mean values differed by up to 4.7% CP, suggesting biologically meaningful differences in spring forage quality among regions. Lambert (1998) documented greater mass gain in fawns receiving higher protein diets during the 6 months following weaning, a period equivalent to winter and spring in Mississippi. Newly weaned male fawns gained mass faster on a 20.2% CP diet than on a 12.7% CP diet (Ullrey et al. 1967). Holter et al. (1979) tested weight gain in yearlings given experimental diets from 7.9–24.0% CP and found the percentage of retained body nitrogen to be constant across that range, indicating that growth was directly correlated with CP during May–October. We might therefore reasonably expect faster growth in regions with higher forage CP levels. Growth-rate curves for these regions coincide with composite CP, with the exception of the Delta (Strickland and Demarais 2000), which may be affected by enhanced diet quality from cultivated crops. 602 Southeastern Naturalist Vol. 7, No. 4 Forage protein digestibility is reduced by tannins (Robbins et al. 1987). Plant species may respond to changes in soil fertility by altering growth patterns and levels of tannins. Species growing in lower fertility soils may produce more tannins in their leaves than when grown in more fertile soils, and these differences may be significant over relatively subtle gradients (Kraus et al. 2004, Muller et al. 1987). Plants on more fertile soils increase their total biomass (Biere 1995, Chapin 1980, Fraser and Grime 1998, Kraus et al. 2004) and often divert fewer resources to herbivore defense (Coley et al. 1985), though this response varies by species (Almeida-Cortez et al. 1999). If this general relationship between soil fertility and tannin production holds across the areas we sampled, it is possible that differences in forage protein availability among these sites would be increased. Average precipitation is similar across all sampled regions, with weather stations nearest each sampling area reporting long-term annual means of 142–159 cm and similar patterns of monthly accumulation (National Climate Data Center 2008). Cumulative precipitation during January–April 2006 at the LCP site was 38 cm, 38% below the long-term mean. Sites in other regions ranged from 9% below to 16% above normal for this period. All sites suffered rainfall deficits for the period of May–July, ranging from 32–61%. Moderate moisture deficits are unlikely to have significant effects on CP (Peterson and Scheaffer 1992, Seguin et al. 2002); because the LCP sites received an average 37 cm rainfall in January–April, we believe it unlikely that CP was reduced. Forage plants under moisture stress in this region may actually increase their CP and total dietary nutrients as plant growth slows (R. Lemus, Mississippi State University Extension Forage Specialist, pers. comm.). Because rainfall deficits during late spring–early summer were similar across all sites, we do not believe they were a biasing factor. The next logical step in understanding the relationship of soil regions with deer morphometrics is to explore whether differences in forage quality find their way into actual diet quality. We suggest direct measurement of diet quality through ruminal sampling to determine seasonal CP levels in deer diets among regions for comparison with morphometric data. Because diet quality can be impacted by population density, nutritional plane should be compared within regions among populations at different densities relative to carrying capacity. We need to quantify the effects of habitat management activities on plant quality, deer diet quality, deer morphometrics, and population dynamics, especially fawn recruitment. Acknowledgments The authors are grateful to 3 anonymous reviewers for helpful comments on the manuscript, and to P. Hanberry for sample collection. Support for this research was provided through the McEntire-Stennis Fund and the Mississippi Department of 2008 P.D. Jones, S. Demarais, B.K. Strickland, and S.L. Edwards 603 Wildlife, Fisheries, and Parks through project W-48-57 of the Federal Aid in Wildlife Restoration Program. This manuscript is contribution number WF257 of the Mississippi State University Forest and Wildlife Research Center. Literature Cited Almeida-Cortez, J.S., B. Shipley, and J.T. Arnason. 1999. Do plant species with higher growth rates have poorer chemical defences? Functional Ecology 13:819–827. Asleson, M.A., E.C. Hellgren and L.W. Varner. 1996. Nitrogen requirements for antler growth and maintenance in White-tailed Deer. Journal of Wildlife Management 60:744–752. Beckwith, S.L. 1964. Effect of site preparation on wildlife and vegetation in the Sandhills of central Florida. Proceedings of the Annual Conference of the Southeastern Association of Game and Fish Commissioners 18:39–48. Berteaux, D., M. Crete, J. Hout, J. Maltais, and J.-P. Ouellet. 1998. Food choice by White-tailed Deer in relation to protein and energy content of the diet: A field experiment. Oecologia 115:84–92. Biere, A. 1995. Genotypic and plastic variation in plant size: Effects on fecundity and allocation patterns in Lychnis fl os-cuculi along a gradient of natural soil fertility. Journal of Ecology 83:629–642. Carmer, S.G., and M.R. Swanson. 1973. An evaluation of ten pairwise multiple comparison procedures by Monte Carlo methods. Journal of the American Statistical Association 68:66–74. Chapin III, F.S. 1980. The mineral nutrition of wild plants. Annual Review of Ecology and Systematics 11:233–260. Coley, P.D., J.P. Bryant, and F.S. Chapin III. 1985. Resource availability and plant antiherbivore defense. Science 230:895–899. Cote, S.D., T.P. Rooney, J.-P.Tremblay, C. Dussault, and D.M. Waller. 2004. Ecological impacts of deer overabundance. Annual Review of Ecology, Evolution, and Systematics 35:113–147. Crawford, H.S. 1982. Seasonal food selection and digestibility by tame White-tailed Deer in central Maine. Journal of Wildlife Management 46:974–982. Fraser, L.H., and J.P. Grime. 1998. Top-down control and its effect on the biomass and composition of three grasses at high and low soil fertility in outdoor microcosms. Oecologia 113:239–246. French, C.E., L.C. McEwen, N.D. Magruder, R.H. Ingram, and R.W. Swift. 1956. Nutrient requirements for growth and antler development in White-tailed Deer. Journal of Wildlife Management 20:221–231. Fuller, K.T. 1980. The relationship between soil fertility and deer browse nutritive quality in Nathan Bedford Forrest State Park. M.Sc. Thesis. University of Tennessee, Knoxville, TN. Helrich, K. (Ed.). 1990. Official Methods of Analysis. Fifteenth Edition. Association of Official Analytical Chemists, Arlington, VA. Holter, J.B., H.H. Hays, and S.H. Smith. 1979. Protein requirements of yearling White-tailed Deer. Journal of Wildlife Management 43:872–879. Hundley, L.R. 1959. Available nutrients in selected deer-browse species growing on different soils. Journal of Wildlife Management 23:81–90. 604 Southeastern Naturalist Vol. 7, No. 4 Jacobson, H.A. 1984. Relationships between deer and soil nutrients in Mississippi. Proceedings of the Southeastern Association of Fish and Wildlife Agencies 38:1–12. Jacobson, H.A., D.C. Guynn, Jr., R.N. Griffin, and D. Lewis. 1979. Fecundity of White-tailed Deer in Mississippi and periodicity of corpora lutea and lactation. Proceedings of the Southeastern Association of Fish and Wildlife Agencies 33:30–35. Jones, P.D. 2008. Effects of five different intensities of stand establishment on wildlife habitat quality and tree growth in Loblolly Pine (Pinus taeda) plantations in southern Mississippi. Dissertation, Mississippi State University, Mississippi State, MS. Kie, J.G., D.L. Drawe, and G. Scott. 1980. Changes in diet and nutrition with increased herd size in Texas White-tailed Deer. Journal of Range Management 33:28–34. Kissell, R.E., Jr., C.G. Wieberg, L. Hansen, and J. Berringer. 2002. Deer antler characteristics in relation to land use and spatio-temporal factors in Missouri. Proceedings of the Southeastern Association of Fish and Wildlife Agencies 56:322–330. Kraus, T.E.C., R.J. Zazoski, and R.A. Dahlgren. 2004. Fertility and pH effects on polyphenol and condensed tannin concentrations in foliage and roots. Plant and Soil 262:95–109. Kreuger, W.C., and C.G. Donnart. 1974. Relationship of soils to seasonal deer forage quality. Journal of Range Management 27:114–117. Lambert, B.C., Jr. 1998. Growth of White-tailed Deer fawns following dietary protein restriction. M.Sc. Thesis. Texas Tech University, Lubbock, TX. Littell, R.C., G.A. Milliken, W.W. Stroup, R.D. Wolfinger, and O. Schabenberger. 2006. SAS for mixed models. SAS Institute, Cary, North Carolina, USA. Mattson, W.J., Jr. 1980. Herbivory in relation to plant nitrogen content. Annual Review of Ecology and Systematics 11:119–161. McDonald, C.G. 2003. Estimating White-tailed Deer population characteristics on wildlife management areas in Mississippi. M.Sc. Thesis. Mississippi State University, Mississippi State, MS. McEwen, L.C., C.E. French, N.D. Magruder, R.W. Swift, and R.H. Ingram. 1957. Nutrient requirements of the White-tailed Deer. Transactions of the North American Wildlife Conference 22:119–132. Meyer, M.W., and R.D. Brown. 1985. Seasonal trends in the chemical composition of ten range plants in South Texas. Journal of Range Management 38:154–157. Meyer, M.W., R.D. Brown, and M.W. Graham. 1984. Protein and energy content of White-tailed Deer diets in the Texas coastal bend. Journal of Wildlife Management 48:527–534. Muller, R.N. P.J. Kalisz, and T.W. Kimmerer. 1987. Intraspecific variation in production of astringent phenolics over a vegetation-resource availability gradient. Oecologia 72:211–215. Murphy, D.A., and J.A. Coates. 1966. Effects of dietary protein on deer. Transactions of the North American Wildlife Conference 31:129–139. Murphy, D.A., and W.R. Porath. 1969. Forest soils and game nutrition. Proceedings of the Southeastern Association of Game and Fish Commissioners 23:18–25. 2008 P.D. Jones, S. Demarais, B.K. Strickland, and S.L. Edwards 605 National Agricultural Statistics Service. 2004. 2002 Census of Agriculture. Volume 1, Geographic Area Series, Parts 1–50. US Department of Agriculture, Washington, DC. National Climate Data Center. 2008. National Oceanic and Atmospheric Administration Satellite and Information Service. Monthly Time Series. Available online at Accessed 21 March 2008. Parker, K.L., M.P. Gillingham, T.A. Hanley, and C.T. Robbins. 1999. Energy and protein balance of free-ranging Black-tailed Deer in a natural forest environment. Wildlife Monographs 143. Peterson, R.G. 1985. Design and Analysis of Experiments. Marcel Dekker, Monticello, NY. 429 pp. Peterson, P.R., and C.C Scheaffer. 1992. Drought effects on perennial forage legume yield and quality. Agronomy Journal 84:774–779. Pettorelli, N., J.-M. Gaillard, P. Duncan, A.-P. Ouellet, and G. van Laere. 2001. Population density and small-scale variation in habitat quality affect phenotypic quality in roe deer. Oecologia 128:400–405. Pettry, D.E. 1977. Soil resource areas of Mississippi. Mississippi Agricultural and Forestry Experiment Station Information Sheet 1278, Mississippi State, MS. Robbins, C.T., T.A. Hanley, A.E. Hagerman, O. Hjeljord, D.L. Baker, C.C. Schwartz, and W.W. Mautz. 1987. Role of tannins in defending plants against ruminants: Reduction in protein availability. Ecology 68:98–107. SAS Institute. 2000. SAS/STAT user’s guide, version 8. SAS Institute, Cary, NC. Seguin, P., A.F. Mustapha, and C.C. Scheaffer. 2002. Effects of soil moisture deficit on forage quality, digestibility, and protein fractionation of Kura Clover. Journal of Agronomy and Crop Science 188:260–266. Smith, F.H., K.C. Beeson, and W.E. Price. 1956. Chemical composition of herbage browsed by deer in two wildlife management areas. Journal of Wildlife Management 20:359–367. Smith, C.M., E.D. Michael, and H.V. Wiant, Jr. 1975a. Size of West Virginia deer as related to soil fertility. West Virginia Agriculture and Forestry 6:12–13. Smith, S.H., J.B. Holter, H.H. Hays, and H. Silver. 1975b. Protein requirements of White-tailed Deer fawns. Journal of Wildlife Management 39:582–589. Soper, R.B., R.L. Lochmiller, D.M. Leslie, Jr., and D.M. Engle. 1993. Condition and diet quality of White-tailed Deer in response to vegetation management in central Oklahoma. Proceedings of the Oklahoma Academy of Science 73:53–61. Stewart, K.M., T.E. Fulbright, and D.L. Drawe. 2000. White-tailed Deer use of clearings relative to forage availability. Journal of Wildlife Management 64:733–741. Strickland, B.K. 2005. Harvest intensity, habitat configuration, and environmental effects on White-tailed Deer morphometrics and reproduction. Ph.D Dissertation. Mississippi State University, Mississippi State, MS. Strickland, B.K., and S. Demarais. 2000. Age and regional differences in antlers and mass of White-tailed Deer. Journal of Wildlife Management 64:903–911. Strickland, B.K., and S. Demarais. 2006. Effectiveness of the State Soil Geographic Database (STASGO) to predict White-tailed Deer morphometrics in Mississippi. Wildlife Society Bulletin 34:1264–1272. 606 Southeastern Naturalist Vol. 7, No. 4 Thorsland, O.A. 1966. Nutritional analyses of selected deer foods in South Carolina. Proceedings of the Southeastern Association of Game and Fish Commissioners 20:84–104. Ullrey, D.E., W.G. Youatt, H.E. Johnson, L.D. Fay, and B.L. Bradley. 1967. Protein requirement of White-tailed Deer fawns. Journal of Wildlife Management 31:679–685. Vangilder, L.D., O. Torgerson, and W.R. Porath. 1982. Factors infl uencing diet selection by White-tailed Deer. Journal of Wildlife Management 46:711–718. 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 Books, Harrisburg, PA. Warren, R.C., and G.A. Hurst. 1981. Ratings of plants in pine plantations as Whitetailed Deer food. Information Bulletin 18, Mississippi Agricultural and Forestry Experiment Station, Mississippi State, MS. Weckerly, F.W., and M.L. Kennedy. 1992. Examining hypotheses about feeding strategies of White-tailed Deer. Canadian Journal of Zoology 70:432–439.