Population Dynamics of Small Mammals in Virginia Forests: Testing the Impacts of                           Weather, Deer, ...
Introduction       Small mammal populations have been the subject of intense study for several reasons. Onan ecological le...
forb levels is directly associated with re-colonization by small mammal populations. Finally,specific vegetation compariso...
Food       Populations of small mammals have also been correlated to mast crops and factorsaffecting their production. A s...
Methods and MaterialsStudy sites (McShea 1992,McShea 2000)       Twelve study sites total were investigated within the con...
sites (3 CRC sites and 5 SNP sites) in 1990. Shrub cover data was collected in 1990, 1992, 1994,1996, and 1997 at four sit...
Measuring Shrub Surface Area       Shrub data was collected twice at each site over the period of our study. Shrub surface...
acorns inaccessible to foraging animals. The cumulative count of acorn density per site per yearfor was used for analysis,...
Statistical analysis was performed using JMP®(SAS Software). Small mammals, acorndensity, and shrub density variables were...
ResultsShrub and deer                 Figure 1: ANCOVA of response of ln summer small                 mammal population to...
Acorn Density and Deer                          Figure 2: Linear Response of ln winter small                          mamm...
4000                 3500                 3000  Total Acorns                 2500                 2000                    ...
Climate variables on small mammal population                  Figure 5: Response of March small mammal                  po...
Figure 6: Lack of response of acorn density to winter              precipitation.Discussion       The results indicate tha...
reduced vegetative understory that would have provided rodents with a habitat in which to hoard,as deer have been found to...
Summer weather and winter precipitation did not explain any of the variety in the smallmammal populations. It is unsurpris...
and logs may have played a larger role in controlling the population. The weather data couldhave been more precise in orde...
Work CitedBarry RE and Francq EN. 1980. Orientation to Landmarks within the Preferred Habitat by       Peromyscusleucopus....
Korslund L and Steen H. 2006. Small Rodent Survival: Snow Conditions Limit Access to Food       Resources. Journal of Anim...
Ostfeld RS, Jones CG, Wolff JO. 1996. Of Mice and Mast. Bioscience. 46, 323–330.Ostfeld, R. S. Canham, C. D., Oggenfuss, K...
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Population Dynamics Of Small Mammals In Virginia Forests

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Population Dynamics of Small Mammals in Virginia Forests: Testing the Impacts of Weather, Deer, Acorns, and Shrub Cover.

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T. Bernheim, M. Fu, S. Rowland, and A. Tsai

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Population Dynamics Of Small Mammals In Virginia Forests

  1. 1. Population Dynamics of Small Mammals in Virginia Forests: Testing the Impacts of Weather, Deer, Acorns, and Shrub Cover By: Taylor Bernheim, Menghan Fu, Sebastian Rowland, and Andrew TsaiAbstract Small rodent communities play an important role in forest ecosystems as consumers ofvegetation and as prey for birds and larger mammals. Several biotic factors have been found toinfluence population size. The presence of deer, production of food such as acorns, seasonaltemperature and precipitation, and shrub cover all play a role in controlling the size of smallmammal populations. We analyzed small mammal trappings in forests surrounding Fort Royal,Virginia in order to test for relationships with these variables. Peromyscus leucopus andMicrotus pennsylvanicus were the most frequently trapped species. Acorn density was positivelycorrelated with small mammal populations. Winter precipitation, the presence of deer, and shrubcover were negatively correlated with small mammal populations. Greater acorn density likelyprovided small mammals with more nutrition. Deer may have forced greater competition forshrub space or competed for acorns. Winter precipitation was primarily snow, which likelyreduced access to vegetation. The negative impact of shrub was most likely due to the smallsample size of the shrub data. Our data suggests that these environmental factors are importantfor small mammals. However, there are other untested variables that may help explain thevariation found. 1
  2. 2. Introduction Small mammal populations have been the subject of intense study for several reasons. Onan ecological level, they are crucial contributors to forest ecosystems across North Americabecause they consume vegetation and seeds, and serve as prey for larger animals such as owls,weasels, and snakes (Hansson 1987). Woodland rodents have also been noted to negativelyinfluence the survival of fledglings (Schmidt 2008). Small mammal populations are also ofhuman concern. Knowing which factors influence small mammal populations and how areimportant academic questions that ecologists have struggled with for many years (Wang 2007).This class of animals, particularly M. pennsylvanicus are carriers of the human lung pathogenhantavirus (Mills 2009). One of the more common species, P. leucopus, is a known host forIxodes scapularis, the black legged tick that can carry Lyme disease (Ostfeld 1996). Thusunderstanding small mammal populations is of epidemiological importance as well.Vegetation Several studies performed in the field have observed a positive correlation between low-lying vegetation and small mammal populations. Navigation studies have shown that rocks,shrubs, and other navigable landmarks encourage colonization, especially by P. leucopus, amongothers (Barry and Francq 1980). Comparison studies of different habitats, including introducedartificial cover, have indicated that increased food and cover levels are preferred in habitatselection (Wirtz and Pearson 1960), though each small mammal species has its own preferences.A study on the reclamation of a Kentucky mine (Larkin 2008) revealed that low-level, diversevegetative growth under 2 cm diameter at breast height (DBH) coupled with high litter, rock, and 2
  3. 3. forb levels is directly associated with re-colonization by small mammal populations. Finally,specific vegetation comparisons between habitats in Ontario, Canada have indicated that morethan three-fourths of total population variation is explained by low-level vegetation growth(M’Closkey and Lajoie 1975).Climate Studies have demonstrated that climatic variables have an effect on small mammalpopulations, although which relationship is observed is dependent on the time span of the study.A 20-year study carried out by Deitloff, et al. in Minnesota indicated that the population of M.pennsylvanicus is positively correlated to summer precipitation. The study, while acknowledgingdifferent conclusions drawn from shorter-term analyses, assumed that long-term results werepreferable to short-term results. The positive correlation of small mammal populations withsummer precipitation was also found in a study based in Ohio focusing on P. leucopus byLewellen and Vessey. Among other things, the study found a 2-3 month lag of the effect ofextreme summer temperatures on population size and a 3-month lag of extreme wintertemperatures. This lag was more firmly established in their 1998 study (Lewellen and Vessey)that emphasized the usefulness of short-term analysis in explaining population variation ascompared to long-term analysis, which was cited as an “inappropriate time scale” for this type ofstudy. Accordingly, an 11-year study conducted in Alberta focusing on Peromyscus maniculatusfound little relation between weather conditions and annual population growth (Kalcounis-Reuppell 2002). It was found that P. maniculatus has adapted compensatory responses toextreme temperatures, though climate still limited their seasonal breeding. 3
  4. 4. Food Populations of small mammals have also been correlated to mast crops and factorsaffecting their production. A study in Maine focusing on P. leucopus population fluctuations asrelated to acorn mast found an oscillatory period of four years (Elias 2004). Allowing forpredation and intrinsic competition within the small mammal population, large acorn (Quercussp.) crops were generally associated with a rise in P. leucopus population. This result waslikewise observed by a study conducted in Virginia, where populations of P. leucopus and othersmall mammals were significantly correlated with acorn mast production (McShea 2000). Acontrol for interspecific interactions found a relative increase in small mammal populations inareas of lower competition. Nixon also identified that lower competition for resources led to anincrease in survival of gray and fox squirrels (Sciurus carolinensis and Sciurus niger,respectively) suggesting that the trend is not unique to P. leucopus (1975). Also observed werelower emigration rates and increased female fecundity. In addition to these, a study in Illinoisfound that increased food supplies anticipated unusually early breeding for P. leucopus (Hansen1979) and, when provided during periods of normally low food supplies (e.g. overwintering), ledto an increase in population in following years. A conflicting trend was observed by Vessey(1987) in Ohio, where populations of P. leucopus declined in summer despite a plethora of food,suggesting that complex interactions between food sources and animal behavior, such as nest andmate guarding, contribute to population fluctuations. The objective of this study was to identify the influence of food availability, severity ofthe seasonality, and impact of shrubs and low-lying vegetation on small mammal populations. Inorder to test these relationships we analyzed trapping and environmental data from twelve sitesin Eastern Virginia forests. 4
  5. 5. Methods and MaterialsStudy sites (McShea 1992,McShea 2000) Twelve study sites total were investigated within the context of this study. Three studysites were located near Front Royal, Virginia, USA (38°54’ N, 78°09’ W) on the premises of theConservation and Research Center (CRC), five study sites were located within ShenandoahNational Park (SNP), and four sites were located in the George Washington National Forest. TheCRC is a 1,200-ha research facility located 2 km SE of the town of Front Royal. SNP is acomponent of the national park system that stretches along the Appalachian Mountain chainfrom Front Royal south almost to Waynesboro, Virginia, a distance of approximately 160 km.All sites were composed primarily of mature oak, hickory (Carya sp.), white ash (Fraxinusamericana), and yellow poplar (Liriodendron tulipifera) with understory shrubs of Cornusflorida, Lindera benzoin, and Cercis canadensis (Eyre 1980). All sites were 4ha, either 200 x 200 m, or 160 x 250 m in shape, and separated by at least1 km. Deer exclusion fences were erected in 1991 around the Posey site within the CRC. The 3-m tall fence, composed of farm fencing and high tensile wire, did not exclude medium and smallvertebrates (Leimgruber et al. 1994). Five other deer exclosures were similarly erected andplaced at the Keyser, Dump, and Hillstop sites within Shenandoah National Park and at theForest 1 and Forest 2 sites within the George Washington National Forest. The six remainingsites, North and Bear within the CRC and Forest 3, Forest 4, Forest 5, and Forest 6 sites withinthe George Washington National Forest, were open to deer and served as controls. Small mammal data were collected from 1992 to 1998. Acorn data were collected at twosites since 1986, eight sites since 1990, all sites from 1992-1998. DBH data was measured at 8 5
  6. 6. sites (3 CRC sites and 5 SNP sites) in 1990. Shrub cover data was collected in 1990, 1992, 1994,1996, and 1997 at four sites. In addition, several environmental measures were taken at eachsampling unit. Slope and elevation were determined using a clinometer. Aspect was determinedwith a compass by estimating the direction water would flow from the center of the unit.Small mammal trapping Small mammal data were collected from 1992 to 1998. Trapping occurred during lateMarch/early April and during August. The spring trapping coincided with the emergence ofgreen vegetation, while the August trapping concluded before the maturation of the annual mastcrop (McShea and Schwede 1993). At each 4 ha site, 100 trap stations were evenly placed at 20m intervals and permanently marked with stakes. 2 Sherman traps (Sherman Trap Company,Tallahassee, Florida, 23cm) were placed at each station, for a total of 200 traps at each site.Sherman live traps were baited with sunflower seeds. Live traps were pre-baited for two daysand then opened for 3-4 consecutive days. All traps were checked every 12 hours, and allcaptured animals were uniquely marked with a No. 1 monel eartag (National Band and TagCompany, Lexington, Kentucky, USA). Species, sex, age, weight, and evaluation of reproductivecondition were recorded before release. Although nine species were captured at least 10 times during the study, the onlygranivorous mammals with sufficient sample size for analysis were P. leucopus, Tamias striatus,and S. carolinensis. 6
  7. 7. Measuring Shrub Surface Area Shrub data was collected twice at each site over the period of our study. Shrub surfacearea was measured using a cover board. The cover board was divided into 25 squares and shrubsurface area was recorded as the number of squares occupied by vegetation when observed froma distance of 16 meters.Quantifying Weather Data Weather data was collected from a local weather station. Following the methods ofMerritt et al. (2003), annual maximum and minimum mean temperatures in the year pre-trapping(i.e. the year leading up to March for minimum mean temperature and leading up to August formaximum mean temperature) were used in analysis. The annual maximum mean temperature inthe year leading up to August was used for analysis in lieu of extreme summer temperatures. It isexpected that this will yield a clearer measure of the response of populations to temperatureeffects. Precipitation was measured as the accumulated precipitation during the winter prior toMarch trapping, and during the growing season prior to August trapping.Measuring Acorn Production Acorn counts were collected annually from all sites from 1992 to 1998. Mast production(kg/ha) was estimated by establishing a grid of mast collectors in each of two oak-history stands(Posey Hollow and Bear Hollow) that were 2 km apart. Each grid was composed of 100collectors in a 10 by 10 configuration at 20 m intervals. Mast collectors were wire funnels(collecting surface = 2,910 cm2) attached to tin cans and fastened to 1 m stakes, making collected 7
  8. 8. acorns inaccessible to foraging animals. The cumulative count of acorn density per site per yearfor was used for analysis, though mast production in 1986 was obtained from only 18 of thesecollectors at each of the two sites. All species were pooled for analyses because no significantdifference in response was observed of deer to acorns of the three common oak species. Hickory(Carya sp.) nuts were excluded from analyses because deer do not consume them. Medium-sized mammals captured at the nearby Posey Hollow grid include gray andfox squirrels (S. carolinensis, S. niger), southern flying squirrels (Glaucomys volans), easternchipmunks (T. striatus), raccoons (Procyon lotor), and eastern woodrats (Netotoma floridana).White-footed mice (P. leucopus) were the only mast-consuming small mammals captured in thePosey Hollow grid.Statistical Analysis A cumulative count of untagged small mammals during March trapping was comparedagainst acorn count, minimum winter temperature, and accumulated winter precipitation, inaccordance with the observed 3-month lag of the effect of winter temperatures on populations(Lewellen and Vessey 1997). A cumulative count of untagged small mammals during Augusttrapping was compared against shrub density, max precipitation, and accumulated summerprecipitation. While the August trapping would not reflect the 2-month lag of the effect ofextreme summer temperatures on populations (Lewellen and Vessey 1997), it measures theeffect of other summer factors on the population sans effects from acorns, which are typicallyharvested in the fall. In particular, the effect of summer precipitation on breeding will berepresented in these data, as August is toward the end of the P. leucopus breeding season(Cornish and Bradshaw 1978). 8
  9. 9. Statistical analysis was performed using JMP®(SAS Software). Small mammals, acorndensity, and shrub density variables were log transformed to reduce heterogeneity of variances.The presence of deer was defined as a nominal binary variable. Analysis for shrub and deer werefirst run as analysis of variance (ANOVA) with deer and the variable in question. Wheninteraction was not significant, then analysis of covariance (ANCOVA) was run. Linearregression was utilized to measure the response of populations to deer after ANCOVA showeddeer was not significant. Stepwise regression using the Akaikes Information Criterion (AIC)stepping rule was utilized on population and weather variables to determine which variablesproduced a significant response in populations. In particular, stepwise regression was run withmultiple variables for August trapping, including maximum and minimum temperatures, winterand growing season precipitation, and acorn density. August trapping did not respondsignificantly to any of these variables, which were discounted as per AIC. 9
  10. 10. ResultsShrub and deer Figure 1: ANCOVA of response of ln summer small mammal population to total shrub cover and deer/no deer plots. ANOVA revealed no significance in the interaction between shrub and deer (t=.01;df=1,18; p=.9935). ANCOVA tested for the effect of deer exclusive correcting for thedifferences in shrub density. Analysis revealed that deer negatively impacts summer smallmammal populations (t=-2.19; df=1,19; p=.0408). Plots with deer tended to have 13% less smallmammals than plots where deer were excluded. Contrary to expectations, the ANCOVA alsorevealed summer small mammal population significantly decreases with increasing shrub cover(t=-3.20; df=1,19; p=.0047). Therefore, the effect of deer on small mammal population size is often masked sinceplots with deer also tend to have lower shrub cover. However it is possible the limited shrub dataset can potentially impact the relationships noted by the analysis. 10
  11. 11. Acorn Density and Deer Figure 2: Linear Response of ln winter small mammal population ln Acorn density from the previous year. ANCOVA of deer and acorn density revealed that deer had no significance alone onsmall mammal population (t=0.24; df=1,76; p=.8106). Linear regression revealed that wintersmall mammal populations responded positively to acorn the previous year (t=6.61; df=1,78;p<.0001; Figure 2). Small mammal populations increased by .2404 with every unit increase inacorn density from the previous year, despite the variability in acorn density from year to year(Figure 3). Additionally ANCOVA analysis revealed no significant impact of deer enclosure onacorn density (t=-0.67; df=1,82; p=.5052; Figure 4). 11
  12. 12. 4000 3500 3000 Total Acorns 2500 2000 Figure 3: Total acorn density 1500 in no deer and deer plots. 1000 500 0 1991 1992 1993 1994 1995 1996 1997 1998 160 140 120 100 Figure 4: Response of acornTotal Acorns density to the presence of deer. 80 60 40 20 0 Type of Plot 12
  13. 13. Climate variables on small mammal population Figure 5: Response of March small mammal population to accumulated winter precipitation. Stepwise regression analysis revealed no significant impact on summer small mammalpopulations from climate variables. Winter populations can be explained by both acorn densityas well as winter precipitation. Regression revealed the following result: ln (TSM) = 5.3495+ .00067973(acorn) -.0979612(winter precip). Accumulated winter precipitation had a negativeeffect on populations (t=-6.60; df=1,82; p<.0001, figure 5). Winter precipitation was able toexplain 48.2% of the response in March population size.Additionally ANCOVA showed no significant effect of weather variables on acorn count (t=0.13;df=1,82; p=.8966, figure 6). 13
  14. 14. Figure 6: Lack of response of acorn density to winter precipitation.Discussion The results indicate that the presence of a deer population negatively impacted theautumn small mammal populations. One possible mechanism for this relationship is interspecificcompetition between small mammals and deer for acorns. McShea (2000) observed thisrelationship, though the competition only had a noticeable impact during seasons of low mast.The deer may have also eaten shrub and thus reduced an important habitat for the rodents(Flowerdew 2001). While our data does not support such a relationship between deer and shrubsurface area, the shrub dataset was small and may have been insufficient to reveal a relationship.Deer may have influenced how small mammals used the shrub. Muñoz (Muñoz2007) observedthat the environmental disturbances cause by deer presence would cause mice to spend moretime in the shrub. This behavioral change in turn reduced the use of shrubs as caching sitesbecause the risk of discovery was greater. In this way the presence of deer may limit a criticaloverwintering survival strategy. Although our limited dataset did not show it, deer may have 14
  15. 15. reduced vegetative understory that would have provided rodents with a habitat in which to hoard,as deer have been found to decrease acorn predation (Bokdam 2001). It is also possible that thedifferences between exclosure and non-exclosure plots may be due to other biotic or abioticdifferences. The negative correlation between shrub surface area and small mammal data iscontradictory to many findings that found a positive correlation (M’Closkey and Lajoie 1975,Larkin 2006). One possible mechanism is that M. pensylvanicus would outcompete P. leucopusin the shrub space (Wirtz 1960) and thus P. leucopus, which was the most populous species, wasnot able to inhabit much of the plot, which was covered in shrubbery. The metric of shrubsurface area may have been insufficient to account for all preferred microhabitats of rodents.Logs and stumps also encourage small mammal populations. In one study they had a greaterimpact on rodents than shrubs because they offered more isolation (Barry and Francq 1980). Themice and voles may have spent more time in the shrubs if they cover more of the plot – since fewof the traps were set in shrubs this would bias the findings against shrub density. Although thesemechanistic explanations are possible, the most probable cause of the negative correlation is thatthe sample size of shrub data was too small to reveal an accurate relationship. Our analysis found that acorns had a highly significant positive relationship with smallmammal populations. Consumption of acorns by small mammals has been well documented(Whitaker 1966); thus in our plots the mice and voles likely took advantage of acorn dispersal asan additional food source. Acorns only had a significant effect on spring populations. Theyprovided nutrients necessary for small mammals to overwinter (Wolff 1996), but did not persistlong enough to influence the summer population. 15
  16. 16. Summer weather and winter precipitation did not explain any of the variety in the smallmammal populations. It is unsurprising that summer temperature had little effect becausesummer temperatures did not vary significantly. Similar results in other studies suggest thatbehavioral and physiological responses to the weather mitigated their influence (Deitloff 2010).The amount of winter precipitation, snow, was found to have a negative impact on smallmammal populations. While snow cover may protect rodents from predation by some predatorspecies, weasels have specially adapted to hunt small mammals in the subnivean space (Hansson1987). Thus, greater snow cover may encourage predation by weasels. Winter precipitation mayalso limit access to food by covering it in ice (Korslund 2006). Therefore, the greaterprecipitation may have limited nutrient availability for rodents, which could have led toemigration or death. The snow cover may have impacted the trapping if it persisted until theMarch trapping session.Conclusion Our analysis revealed some influences that are consistent with the literature in referenceto winter precipitation and acorns. The observed negative influence of shrub surface area may beconfounded by a small dataset. It is likely that the duration of our study influenced the relationships and impacts wefound. The relative influence of each variable may change over time and depends on the state ofthe system (McMilan 2005). Analysis may be strengthened by considering points at which theconditions are most variable in order to ignore times when that factor does not have a largeinfluence. During the period of the experiment other variables may have been more importantthan those we studied (McMilan 2005). Factors such as predation, parasites, other food sources, 16
  17. 17. and logs may have played a larger role in controlling the population. The weather data couldhave been more precise in order to develop different metrics of weather and seasonality. It ispossible that rodent populations respond more strongly to other measurements of weather such ascloud cover at night or average minimum temperature, or a metric that combines temperature andprecipitation. Other measurements of the small mammal population, such as reproduction andsurvival, could be analyzed to identify other influences of the environment. This research will be strengthened by further studying the intrinsic features of smallmammal populations. The importance of abiotic and biotic factors may depend on the density ofthe small mammal populations, as has been observed in other studies (Lewellen and Vessey 1998,Wang et al. 2009). Some rodent species including P. leucopus (Wang et al. 2008) express multi-annual population cycles not considered in the study. The context of such intrinsic factors shouldbe considered in further questions on how extrinsic factors affect population size.Acknowledgements We would like to thank Bill McShea for the use of his data and his useful criticisms.Many thanks go to Vinayak Mathur and Erin Wiley for their advice in the analysis. We wouldalso like to thank Luke, Jenny, and Lorien for their help and for hosting us during the course. 17
  18. 18. Work CitedBarry RE and Francq EN. 1980. Orientation to Landmarks within the Preferred Habitat by Peromyscusleucopus. Journal of Mammalog.y 61, 292-303.Bokdam SR, den Ouden J Olff H, Schot-Opschoor H and Schrijvers M. 2001. Effects of introduction and exclusion of large herbivores on small rodent communities. Plant Ecology. 155, 119-127.Cornish LM, and Bradshaw WM. 1978. Patterns in Twelve Reproductive Parameters for the White-Footed Mouse (PeromyscusLeucopus). Journal of Mammology. 59, 731-739.Deitloff, J, Falcy, M, Krenz, JD and McMillan, BR. 2010. Correlating Small Mammal Abundance to Climatic Variation over Twenty Years. Journal of Mammalogy. 91, 193- 1999.Elias SP, Witham, JW, and Hunter ML. 2004. PeromysucleucopusAbundance and Acorn Mast: Population Fluctuation Patterns Over 20 years. Journal of Mammalogy. 85, 743-747.Flowerdew, J. R. and Ellwood, S. A. 2001. Impacts of Woodland Deer on Small Mammal Ecology.Forestry. 74, 277-287.Hansen LP and Batzli GO. 1979. Influence of Supplemental Food on Local Populations of Peromyscusleucopus. Journal of Mammalogy. 60, 335-342.Hansson, L. 1987. An Interpretation of Rodent Dynamics as due to Trophic Interaction. Oikos. 50:308–318.Kalcounis-Rueppell MC, Millar JS and Herdman EJ. 2002. Beating the Odds – Effects of Weather on a Short-Season Population of Deer Mice. Canadian Journal of Zoology. 80, 1594-1601. 18
  19. 19. Korslund L and Steen H. 2006. Small Rodent Survival: Snow Conditions Limit Access to Food Resources. Journal of Animal Ecology. 75, 156-166.Larkin JL, Maehr DS, Krupa JJ, Cox JJ, Alxy K, Unger DE, and Barton C. 2008. Small Mammal Response to Vegetation and Spoil Conditions on a Reclaimed Surface Mine in Easter Kentucky. Southeastern Naturalist. 7, 401-412.Lewellen RH and Vessey SH. 1998. Modeling Biotic and Abiotic Influences in Small Mammals. Oecologia. 113, 210-218.McMillan, B. R., G. A. Kaufman, and D. W. Kaufman. 2005. Factors influencing persistence of white-footed mice (Peromyscusleucopus). Prairie Naturalist. 37, 29–40.M’CloskeyRt and Lajoie DT. 1975. Determinants of Local Distribution and Abundance in White-Footed Mice. Ecology. 56, 467-472.McShea WJ. 2000. The Influence of Acorn Crops on Annual Variation in Rodent and Bird Populations. Ecology. 81, 228-238.McShea WJ and Gilles AB. 1992. A Comparison of Traps and Fluorescent Powder to Describe Foraging for Mast by Peromyscus-leucopus. Journal of Mammalogy. 73, 218-222.McShea WK and Schwede G. 1993. Variable Acorn Crops – Responses of White-Tailed Deer and Other Mast Consumers.Journal of Mammalogy. 74, 999-1006.Merritt, JF, Lima, M and Bozinovic, F. 2001. Seasonal Regulation in Fluctuating Small Mammal Populations: Feedback Structure and Climate. Oikos. 94, 505–514.Mills JN, Anman BR, and Glass, GE. 2009. Ecology of Hantavirus and Their Hosts in North America. Vector-Borne and Zoonotic Disease.s 9, 563-574.Muñoz, A and Bonal R. 2007.Rodents Change Acorn Dispersal Behavior in Response to Ungulate Presence. Oikos. 116, 1631-1638. 19
  20. 20. Ostfeld RS, Jones CG, Wolff JO. 1996. Of Mice and Mast. Bioscience. 46, 323–330.Ostfeld, R. S. Canham, C. D., Oggenfuss, K., Winchcombe, R. J. and Keesing, F. 2006. Climate, Deer, Rodents, and Acorns as Determinants of Variation in Lyme-Disease Risk.PLoS Biology. 4, 145.Schmidt KA, Rush SA, and Ostfeld RS. Wood Thrush Nest Success and Post-Fledging Survival Across a Temporal Pulse of Small Mammal Abundance in an Oak Forest. Journal of Animal Ecology. 77, 830-837.Wang, G, Wolff JO, Vessey SH, Slade NA, Witham JW, Merritt JF, Hunter ML, and Elias SP. 2008. Comparative Population Dynamics of PeromyscusLeucopus North America: Influences of Climate, Food, and Density Dependence. Population Ecology. 51, 133-142.Whitaker J0, JR. 1966. Food of Musmusculus, Peromyscusmaniculatusbairdi, and P. leucopus in Vigo County, Indiana. Journal of Mammalogy. 47, 473-486.Wirtz WO and Pearson PG. 1960. A Preliminary Analysis of Habitat Orientation in Microtus and Peromyscus. American Midland Naturalist. 63, 131-142.Wolff JO. 1996. Population Fluctuations of Mast-Eating Rodents are Correlated with Production of Acorns. Journal of Mammalogy. 77 850-856. 20

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