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Reproductive Characteristics of White-tailed Deer in Mississippi
Phillip D. Jones, Bronson K. Strickland, Stephen Demarais, and Amy C. Blaylock

Southeastern Naturalist, Volume 9, Issue 4 (2010): 803–812

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2010 SOUTHEASTERN NATURALIST 9(4):803–812 Reproductive Characteristics of White-tailed Deer in Mississippi Phillip D. Jones1,*, Bronson K. Strickland1, Stephen Demarais1, and Amy C. Blaylock2 Abstract - Odocoileus virginianus (White-tailed Deer) in Mississippi have been shown to respond morphometrically to soil resource area, but have not been evaluated for reproductive differences. We analyzed data from herd health checks (1978–2007) and fall harvests (1991–2007) to determine if soil resource area influenced reproductive parameters, and if assumed resource quality interacted with age. Ovulation rates approached unity and were similar across all soil resource areas and age classes, but there was some influence of soils and age class on number of corpora lutea. Pregnancy rate differed only between 2 of 8 soil resource areas, and was unaffected by age. Fetal counts increased with age class, and the incidence of twins among 1.5-year-old females was half that of females ≥2.5 years. Lactation rates differed among 1.5-yearolds by soil resource area, and reflected assumed soil quality among ≥3.5-year-olds. Because lactation occurs later in the reproduction cycle than ovulation or pregnancy, it is more indicative than other metrics of reproductive success. However, because lactation is a binary indicator, age-specific recruitment data is needed to determine potential effects of soil resource area on deer population dynamics. Introduction Odocoileus virginianus Zimmerman (White-tailed Deer; hereafter, “Deer”) have enjoyed a successful comeback in Mississippi since restoration efforts began in the 1930s (Blackard 1971). Restoration has resulted in a continuous distribution of Deer throughout the state, with current estimates placing the statewide population at about 1.75 million (Southeast Deer Study Group 2008). Genetic diversity is high within populations, with variation among populations unrelated to region or interpopulation distance (DeYoung et al. 2003). However, there are regional morphometric differences that appear unrelated to source population, but are correlated with soil resource area (Strickland and Demarais 2000, 2006). Mississippi comprises 10 soil resource areas representing regions of varying soil fertility (Pettry 1977). Deer have been shown to respond morphometrically to soil fertility gradients, growing more slowly and reaching lesser mass in areas of lesser fertility (Jacobson 1984; Smith et al. 1975; Strickland and Demarais 2000, 2006). Body mass is correlated with primiparity in Deer, and reproductive success has been reported to increase until females reach ≥3.5 years of age (Dusek et al. 1989, Roseberry and Klimstra 1970, Strickland et al. 2008, Verme and Ullrey 1984, Woolf and Harder 1979). However, the potential influence of broad-scale soil areas on Deer reproduction has not been investigated. 1Box 9690, Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University, MS 39762. 2Mississippi Department of Wildlife, Fisheries, and Parks, 1505 Eastover Drive, Jackson, MS 39211. *Corresponding author - 804 Southeastern Naturalist Vol. 9, No. 4 Deer populations were monitored statewide by the Mississippi Department of Wildlife, Fisheries, and Parks (MDWFP) through herd health checks performed after mating season and prior to fawning. Females ≥1.5 years old were sampled for reproduction metrics, including corpora lutea (CL) counts, fetal counts, and estimated conception dates. Additionally, during the fall hunting season, harvested females were examined for evidence of lactation as a measure of reproductive success. We evaluated these data to determine if soil area influenced fecundity and reproductive success of female Deer in Mississippi. We hypothesized that females in soil regions with poorer soils would exhibit reduced fecundity, and that age class and soil area would interact such that younger females would be more sensitive to environmental variation and exhibit greater effects of region than more mature females. Methods We obtained herd health check data from the MDWFP for the period 1978–2008, and harvest data from 1991–2008. The timing of herd health checks is crucial to maintaining the validity and comparability of reproduction data. Breeding season is typically earliest in the Batture and Delta, occurs later as one moves east and south, and is latest in the Lower Coastal Plain (LCP) (C. Dacus, MDWFP, Jackson, MS, unpubl. data; Jacobson et al. 1979). Health checks were timed so that the 190 properties monitored were sampled approximately 2 months (x̅ = 60.5 days, SE = 1.2) after mean conception date, thereby providing opportunity for breeding to be completed before sampling and sufficient time for detection of the vast majority of pregnancies. We used health check records to determine 1) ovulation rates (number of females with CL/total number of sampled females), 2) pregnancy rates (number of females with implanted fetuses/total number of sampled females), 3) number of CL per ovulating female, and 4) number of fetuses/ pregnant female for adult females (1.5 years +). Soil area has been correlated with differential growth rates among female Deer in Mississippi, with females in all regions reaching maximum size by 3.5 years of age (Strickland and Demarais 2000), and prior research has demonstrated these age classes may differ in fecundity (Strickland et al. 2008). Consequently, we separated 1.5- and 2.5-year-old Deer from ≥3.5-year-olds so that neither body growth nor age would introduce unnecessary variance into our analyses. Because 0.5-year-old Deer were sampled only incidentally, there was insufficient information from herd health checks to evaluate fawn fecundity, and we did not evaluate fawn records. Females ≥8 years old have been reported to be less productive than younger females (Verme and Ullrey 1984). However, evidence from free-ranging populations has found no evidence of reproductive senescence in females ≤17 years old (DelGiudice et al. 2007, Nelson and Mech 1990). We therefore separated data among 1.5-, 2.5-, and ≥3.5-year-old females. We removed from the health check database entries that did not record any information on reproduction, those that were uncertain as to soil area, and all fawn records, leaving 5296 records available for analysis. We combined data from the Coastal Flatwoods region with the LCP due to low 2010 P.D. Jones, B.K. Strickland, S. Demarais, and A.C. Blaylock 805 sample size; Strickland and Demarais (2000) reported these 2 regions were similar in body mass, antler growth, and growth rate. We also combined the Upper and Lower Thin Loess into a single region, and likewise the Upper and Lower Thick Loess, similar to Jones et al. (2008). The Delta comprises areas protected by a levee system and batture lands between the levees and the Mississippi River. Because the batture lands were subject to regular inundation, we separated Delta samples into Batture (outside levee) and Delta (within levee) regions (Fig. 1). Although the vast majority of records were complete, some were missing data for ≥1 variables. Because we used data when available (regardless of missing data for other variables), sample sizes were not always consistent with expectations. Figure 1. Soil resource areas used for analysis of White-tailed Deer reproductive characteristics in Mississippi. Three areas represent combinations of regions as designated by Pettry (1977). The Thin Loess combines both Upper and Lower Thin Loess; likewise, the Thick Loess combines both Upper and Lower Thick Loess. The Lower Coastal Plain includes the Coastal Flatwoods. In addition, we divided the Delta into areas within (Delta) and outside of (Batture) the river levee system. 806 Southeastern Naturalist Vol. 9, No. 4 We examined 1991–2007 harvest data from hunting clubs participating in the MDWFP Deer Management Assistance Program (Guynn et al. 1983) and from Wildlife Management Areas (WMAs) to determine percentage of females lactating as an indicator of reproductive success. Lactation data typically are taken 3–5 months after peak fawning. To account for the declining probability of lactation detection throughout the hunting season and the potential bias regionally disparate breeding seasons may have had on lactation rate, we used analysis of covariance (ANCOVA) with time between median regional conception date and harvest date as a continuous covariate in the logistic model. Using the GLIMMIX procedure in SAS 9.2 (SAS Institute, Cary, NC) we constructed a 2-way logistic ANCOVA with age, region, and age × region interaction as fixed effects. The response variable was binomial (i.e., lactating or not). For each combination of soil resource area and age class, we estimated ovulation rate, number of CL per ovulating female, pregnancy rate, number of fetuses per pregnant female, and lactation rate. We compared estimates in SAS 9.2 using Proc GLM for numbers of CL and fetuses and Proc GLIMMIX to compare ovulation, pregnancy, and lactation rates. Given our large sample sizes, we decided a conservative approach to assigning significance was warranted. Thus, we elected to use the Bonferroni Type-I error adjustment to determine significance level for post hoc comparisons, starting from a base of α = 0.05. Results We estimated ovulation rate using 5212 health-check records. Ovulation rates were similar across all regions (F7,5188 = 0.08, P = 1.000) and age classes (F2,5188 = 0.00, P = 1.000), averaging 99.5% (SE = 0.3). Among ovulating Deer with data for number of CL (n = 5026), older females tended to have greater numbers of CL than younger Deer, and patterns were consistent among Table 1. Mean number of corpora lutea (SE) found in gravid female White-tailed Deer collected during herd health checks in 8 soil resource areas of Mississippi, 1978–2008. P-values: region = ≤0.001, age class = ≤0.001, and region×age class = ≤0.001. IF = Interior Flatwoods, LCP = Lower Coastal Plain, UPC = Upper Coastal Plain. Age class Region n 1.5 2.5 ≥3.5 Regional Batture 637 1.26 (0.05) A cA 1.81 (0.04) B cd 1.83 (0.03) B d 1.73 (0.02) Black Prairie 346 1.51 (00.08) A bc 2.04 (0.06) B ab 2.11 (0.03) B ab 2.02 (0.03) Delta 967 1.45 (0.05) A c 1.84 (0.03) B bc 1.99 (0.02) C bc 1.87 (0.02) IF 205 1.82 (0.10) A ab 2.09 (0.09) AB abc 2.15 (0.05) B a 2.09 (0.05) LCP 542 1.42 (0.06) A c 1.64 (0.05) B d 1.83 (0.03) C d 1.74 (0.02) Thick Loess 658 1.30 (0.06) A c 1.79 (0.04) B cd 1.92 (0.02) C cd 1.82 (0.02) Thin Loess 482 1.22 (0.06) A c 1.80 (0.06) B bd 1.87 (0.02) B d 1.77 (0.02) UCP 1117 1.81 (0.04) A a 2.03 (0.03) B a 2.21 (0.02) C a 2.11 (0.02) Age class meanB 1.47 (0.02) 1.88 (0.02) 1.99 (0.01) APost hoc comparisons were made using Bonferroni adjustment. Within rows, means followed by the same upper case letter did not differ (α = 0.0167); within columns, means followed by the same lower case letter did not differ (α = 0.0018). BAge class means are means of regions, not weighted by sample size within regions. 2010 P.D. Jones, B.K. Strickland, S. Demarais, and A.C. Blaylock 807 regions, though statistical differences were not always apparent (Table 1). With the exception of the Interior Flatwoods, 2.5-year-olds always produced greater average CL counts than 1.5-year-olds. However, ≥3.5-year-olds averaged greater than 2.5-year-olds in only the Delta, Lower Coastal Plain (LCP), Thick Loess, and Upper Coastal Plain (UCP). Although the effect of region differed somewhat among age classes, the UCP and Interior Flatwoods consistently had the highest CL counts in each age class (x̅ = 2.10), and the Batture, LCP, and Loess regions had the lowest (x̅ = 1.77). We estimated pregnancy rates from 5210 health-check records. Pregnancy rates were affected by region, with the Batture averaging 5.5% greater than the LCP, and all other regions similar (Table 2). Age class did not affect pregnancy rates. Among pregnant females (n = 4740), older females averaged greater numbers of fetuses than younger females consistently across regions (Table 3). Females ≥3.5 years old averaged 0.52 fetuses more than Table 2. Pregnancy rates (SE) of female Deer by age class across 8 soil resource areas in Mississippi, 1978–2008. P-values: region = ≤0.001, age class = 0.131, and region×age class = 0.218. Age class Region n 1.5 2.5 ≥3.5 Regional meanA Batture 683 96.3 (1.8) 98.4 (0.9) 97.7 (1.7) 97.6 (0.7) a Black Prairie 363 97.8 (2.2) 98.8 (1.2) 97.0 (1.1) 98.0 (1.0) ab Delta 983 98.5 (1.1) 95.4 (1.2) 96.4 (0.8) 97.0 (0.8) ab Interior Flatwoods 211 92.9 (4.9) 97.0 (3.0) 98.7 (0.9) 96.9 (1.4) ab Lower Coastal Plain 548 82.9 (4.2) 95.0 (2.2) 94.6 (1.2) 92.1 (1.4) b Thick Loess 692 92.5 (2.9) 94.5 (1.8) 95.7 (0.9) 94.4 (1.1) ab Thin Loess 532 87.7 (3.8) 96.0 (2.0) 93.6 (1.3) 93.1 (1.4) ab Upper Coastal Plain 1198 95.4 (1.6) 96.7 (1.1) 94.5 (0.8) 95.7 (0.7) ab APost hoc comparisons were made using Bonferroni adjustment. Regional means followed by the same lower case letter did not differ (α = 0.0018). Table 3. Mean number of fetuses (SE) found in pregnant female White-tailed Deer collected during herd health checks in 8 soil resource areas of Mississippi, 1978–2008. P-values: region = ≤0.001, age class = ≤0.001, and region×age class = 0.085. Age class Region n 1.5 2.5 ≥3.5 Regional meanA Batture 670 1.22 (0.05) 1.64 (0.04) 1.71 (0.03) 1.61 (0.02) d Black Prairie 336 1.23 (0.08) 1.81 (0.06) 1.92 (0.03) 1.81 (0.03) ab Delta 902 1.38 (0.05) 1.77 (0.03) 1.92 (0.02) 1.80 (0.02) a Interior Flatwoods 195 1.38 (0.10) 1.70 (0.09) 1.84 (0.04) 1.76 (0.03) abc Lower Coastal Plain 505 1.32 (0.06) 1.55 (0.05) 1.73 (0.03) 1.64 (0.02) cd Thick Loess 625 1.21 (0.06) 1.72 (0.04) 1.80 (0.02) 1.71 (0.02) bc Thin Loess 476 1.23 (0.06) 1.71 (0.05) 1.78 (0.03) 1.70 (0.02) cd Upper Coastal Plain 1034 1.46 (0.04) 1.81 (0.03) 1.86 (0.02) 1.79 (0.02) a Age class meanB 1.30 (0.02) A 1.71 (0.02) B 1.82 (0.01) C APost hoc comparisons were made using Bonferroni adjustment. Regional means followed by the same lower case letter did not differ (α = 0.0018). BPost hoc comparisons were made using Bonferroni adjustment. Age class means are means of regions, not weighted by sample size within regions. Age class means followed by the same upper case letter did not differ (α = 0.0167). 808 Southeastern Naturalist Vol. 9, No. 4 1.5-year-old females and 0.11 fetuses more than 2.5-year-old females, reflecting an age-related shift from producing mostly singletons at primiparity to twins in subsequent years (Table 4). Regional means differed across all age classes consistently, with the greatest number of fetuses in the Black Prairie, Interior Flatwoods, Delta, and UCP (x̅ = 1.79) and the least in the Batture, LCP, and Thin Loess (x̅ = 1.65). We estimated lactation rates using 221,395 fall harvest records. Lactation rates were affected by the interaction of age class and region (Table 5). Lactation increased with age class in all regions. However, the effect of region varied with age class. The LCP ranked among the highest in lactation rate for 1.5-year-olds, but ranked lowest at ≥3.5 years. Conversely, the Batture and Thick Loess ranked among the lowest at 1.5 years, then among the highest at 2.5 and ≥3.5 years. Lactation rates in the Delta were consistently among the highest statewide regardless of age class. Table 5. Percentage of lactating (SE) female fall-harvested White-tailed Deer in Mississippi, 1991–2007. P-values: region = 0.001, age class = less than 0.001, and region×age class = less than 0.001. Age class Region 1.5 2.5 ≥3.5 Regional mean Batture 9.0 (0.6) A cA 67.8 (0.9) B a 79.3 (0.7) C ab 48.1 (0.8) Black Prairie 13.0 (0.7) A ab 61.3 (1.1) B cd 72.6 (0.7) C c 46.1 (0.7) Delta 12.9 (0.6) A a 66.3 (0.7) B a 77.9 (0.5) C ab 50.2 (0.6) Interior Flatwoods 13.6 (1.1) A ab 60.7 (1.6) B bcd 73.7 (1.2) C c 46.8 (1.1) Lower Coastal Plain 14.6 (0.6) A a 58.6 (0.8) B d 69.0 (0.5) C d 44.9 (0.5) Thick Loess 10.1 (0.3) A c 65.3 (0.5) B ab 79.4 (0.3) C a 48.3 (0.4) Thin Loess 10.7 (0.4) A bc 62.6 (0.6) B c 77.6 (0.4) C b 47.0 (0.4) Upper Coastal Plain 13.8 (0.4) A a 60.0 (0.6) B cd 71.8 (0.4) C c 45.9 (0.4) Age class meanB 12.1 (0.2) 62.9 (0.3) 75.4 (0.2) APost hoc comparisons were made using Bonferroni adjustment. Within rows, means followed by the same upper case letter did not differ (α = 0.0167); within columns, means followed by the same lower case letter did not differ (α = 0.0018). BAge class means are means of regions, not weighted by sample size within regions. Table 4. Percentage of fetal counts from female White-tailed Deer collected during herd health checks in Mississippi from 1978 to 2008. Fetus countA Age class (yrs) nB 0 1 2 3 1.5 644 2 63 35 0 2.5 1145 1 27 71 1 ≥3.5 2951 1 21 75 4 Overall 4470 1 28 68 3 AIn 2.5-year females, there was 1 observation of 4 fetuses and 1 observation of 5 fetuses. In ≥3.5-year females, there were 3 observations of 4 fetuses. BIncludes Deer for which soil region was unknown. 2010 P.D. Jones, B.K. Strickland, S. Demarais, and A.C. Blaylock 809 Discussion Given the extremely high ovulation rates discovered, it appears unlikely that health-check collections were biased with regard to ovulation estimates. However, because pregnancy may not be achieved during the first estrous cycle and is not immediately detectable, it is more likely that sampling could have been biased with regard to pregnancy rates and fetal counts. The timing of sampling was based on previous reports of region-specific conception dates (Jacobson et al. 1979) and was designed to provide adequate time for fetal development to maximize detectability, thus reducing opportunity for bias among soil regions. Also, conception dates did not differ among age classes (P. Jones, unpubl. data), so age-specific bias was also avoided. Therefore, although it is possible that estimates of pregnancy rates were biased low, we believe that the percentage of missed pregnancies must have been very low and was unlikely to be biased by age or location. Older females are less responsive to short-term environmental factors that may cause greater variation in reproductive effort of younger females (Gaillard et al. 2000, Strickland et al. 2008). Females ≥3.5 years old have reached maximum body size (Strickland and Demarais 2000) and can allocate resources to reproduction more steadily and predictably than younger females (Strickland et al. 2008), and are therefore more likely representative of long-term regional conditions. Natural soil fertility among the regions we examined is generally thought to be greatest in the Delta and Thick Loess, with the UCP and LCP (including the Coastal Flatwoods) lowest (S. Demarais, unpubl. data; Pettry 1977), and regional soil chemical and physical properties are correlated with Deer body mass (Strickland and Demarais 2006). Forage protein content is greater in more fertile soil regions and is a potential limitation for lactating females in the LCP (Jones et al. 2008, 2009). McDonald (2003) reported data from 4 Mississippi WMAs showing fawn recruitment on the LCP site to be less than half that in the Delta and Upper Thick Loess sites. Lactation rates of ≥3.5-year-old females mirrored these regional differences, though at lesser magnitude, and trended along the continuum of assumed resource quality and availability. However, lactation is a binary indicator of reproductive success, insensitive to the number of fawns recruited. Age-specific recruitment data would elucidate whether soil area effects alter population dynamics through differential recruitment. Although soil region affects growth curves and peak body mass in female Deer in Mississippi (Strickland and Demarais 2000), most reproductive metrics did not follow similar or expected patterns. Particularly, the relatively high lactation rates for yearling females in the LCP and UCP were contrary to expectation. A potential consideration in the LCP is the greater likelihood of singleton fawns. Fawns must exceed a threshold body mass and possibly a fat:lean ratio to breed (Hesselton and Sauer 1973, Roseberry and Klimstra 1970, Verme and Ozoga 1987). Singletons may be heavier at birth than twins (Blaylock 2007, Verme 1963), and are thus more likely than twins to reach a threshold mass necessary to ovulate in their first year (Strickland et al. 2008). A second consideration when interpreting lactation rates is the 810 Southeastern Naturalist Vol. 9, No. 4 unknown effect of nutrition on duration of lactation. Although mothers of fawns that die cease milk production and reallocate resources to body growth and reserves (Therrien et al. 2008, Verme 1969), it is not known whether females on low quality diets with live fawns cease lactation sooner than those with better nutrition. Lactation rates may be more indicative of reproductive success than ovulation or pregnancy because they represent data from later in the reproduction cycle when fawns are closer to independence. Expected patterns in fetus counts can be confounded by previous reproductive success and resultant nutritional status. Females that lose fawns during late gestation or lactation can reallocate resources to growth and body reserves, improving their readiness for the coming breeding season (Chan-McLeod et al. 1999, Dusek et al. 1989, Mansell 1974), and females under food restriction have been shown to favor their own maintenance over growth or survival of their offspring (Cook et al. 2004, Therrien et al. 2007). Thus, signs of fertility early in the breeding cycle may not accurately reflect true capacity for successful reproduction. Although pregnancy rates were uniform across age classes, greater lactation rates for ≥3.5-year-old females indicated possibly greater reproductive success for that age class. This finding may be explained by a combination of physical, behavioral, and social factors. Fawn survival has been reported to improve with greater maternal experience (Ozoga and Verme 1986). Furthermore, older females are more likely to be socially dominant, giving them a potential advantage in acquiring necessary resources for successful reproduction (Dusek et al. 1989). Also, the apparent increase in twinning among females ≥2.5 years may provide better opportunity for at least one fawn to survive (Johnstone-Yellin et al. 2009). Density-dependent factors are a primary influence on reproductive success (Keyser et al. 2006, Swihart et al. 1998), and it is possible that differing relative densities may have contributed to regional differences in reproductive success. However, fawn reproduction is sensitive to density, quickly declining when density increases (Strickland et al. 2008, Swihart et al. 1998), and yearling lactation rates indicated very similar rates of fawn breeding among regions. All our samples came from properties managed by the MDWFP, whose management philosophy is to keep Deer populations below the habitat’s carrying capacity. Undoubtedly, inter-population variation in relative animal density existed despite similar population management strategies. Nonetheless, because so many management units were combined to generate regional reproductive estimates, we believe these regional averages are indeed indicative of broad-scale differences in soil resources, and not subtle, site-specific variation in animal density. Acknowledgments The authors thank C. Dacus with MDWFP for providing the datasets, and the numerous MDWFP biologists who collected the vast amount of data they represent. Support for this research was provided through the Department of Wildlife, Fisheries, and Aquaculture at Mississippi State University. This manuscript is contribution number WF301 of the Mississippi State University Forest and Wildlife Research Center. 2010 P.D. Jones, B.K. Strickland, S. Demarais, and A.C. Blaylock 811 Literature Cited Blackard, J.J. 1971. Restoration of the White-tailed Deer to the southeastern United States. M.Sc. 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