Kissell, Robert E., Jr.

Tappe, Philip A.

UARK (University of Arkansas )

Journal of the Arkansas Academy of Science Volume 59 Article 28 2005 Response of an Arkansas White-Tailed Deer Population to Harvest Robert E. Kissell Jr. University of Arkansas at Monticello, kissell@uamont.edu Philip A. Tappe University of Arkansas at Monticello Follow this and additional works at: https://scholarworks.uark.edu/jaas  Part of the Zoology Commons Recommended Citation Kissell, Robert E. Jr. and Tappe, Philip A. (2005) "Response of an Arkansas White-Tailed Deer Population to Harvest," Journal of the Arkansas Academy of Science: Vol. 59 , Article 28. Available at: https://scholarworks.uark.edu/jaas/vol59/iss1/28 This article is available for use under the Creative Commons license: Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0). Users are able to read, download, copy, print, distribute, search, link to the full texts of these articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author. This General Note is brought to you for free and open access by ScholarWorks@UARK. It has been accepted for inclusion in Journal of the Arkansas Academy of Science by an authorized editor of ScholarWorks@UARK. For more information, please contact scholar@uark.edu. 199Response of an Arkansas White-tailed Deer Population to HarvestRobert E. Kissell,Jr. and PhilipA.TappeArkansas Forest Resources Center, School ofForest Resources, University ofArkansas-Monticello, Monticello, AR 71656' Correspondent: kissell@uamont.eduHarvest management of game species for the purpose<»f maintaining or manipulating populations requiresestimation of at least 3 population parameters: populationsize (density), recruitment, and mortality. Knowledge ofthese parameters is important because hunters, as well asanti-hunters, and the general public call for managers beable to defend their management activities (Lancia et al.,2000). Managers most often use indices, such as number ofdeer observed per unit distance driven during a spot-lightsurvey, inplace of population parameters. Indoing so, theassumption is made that a constant, linear relationship existsbetween the index and the population parameter of interest(Lancia et al., 1996). Use of such indices is based ontradition, simplicity, and low cost. However, few indiceshave been validated (Rotella and Ratti, 1986), and noneserve as a perfect substitute for population parameterestimation.Different approaches are available to estimate density,"ecruitment, and mortality (Johnson, 1996; Lancia et al.,1996). Density estimation has been conducted using mark-recapture techniques (Peterson, 1896; Lincoln, 1930;Bartmann et al., 1987), distance sampling (Buckland et al.,1993), area sampling (Seber, 2002), and removal techniquesZippin, 1958; Lancia et al., 1988). For white-tailed deer inhe southeastern U.S., density estimates are most oftenderived using mark-recapture approaches, but distancesampling is becoming more widely used (Langdon, 2001;L,opez et al., 2004). Area sampling, which is most commonlylsed for large ungulates in the western U.S., is not veryipplicable in the southeastern U.S. due to limited visibilityising traditional techniques (e.g., helicopter surveys).however, advances in the use and technology of thermalnfrared imagery are changing the ability to employ areaampling during leaf-off conditions in deciduous hardwoodireas of the Southeast.Recruitment is typically estimated using a sex/age ratiotpproach (Downing, 1980; Ginnett and Butch-Young, 2000).Jopulation size is estimated and an independent estimate ofhe number of young per adult female (e.g., fawns/100 does)s applied to the population estimate. The manner in whichhe ratio is obtained varies depending upon location.Spotlighting is most commonly used to obtain ratios in theoutheastern U.S., whereas visual aerial surveys are used inhe western U.S.Estimation of mortality is directly provided by radio-elemetry (Lancia et al., 2000). Mortality estimation usingadio-telemetry, however, requires a great amount of timeand is financially expensive. Most mortality of white-taileddeer is due to harvest (Dusek et al., 1989), and harvest isusually used as an index to mortality.Population-parameter estimation has not been usedoften by managers for white-tailed deer in Arkansas. Withimplementation of new management strategies for white-tailed deer or acquisition of new properties, baseline datathat includes population parameters are useful to determinethe efficacy of the management strategies employed. TheArkansas Game and Fish Commission (AGFC) purchased anew property, the Choctaw Island Wildlife ManagementArea (CIWMA),inOctober 2001. The deer population wasnot hunted for 2 seasons following the purchase. The firsthunting season under the direction of the AGFC was duringfall 2003. Because the CIWMA was a newly acquiredwildlife management area, AGFC desired baseline data forwhite-tailed deer management. Our objectives were to 1)estimate winter deer density on Choctaw Island WildlifeManagement Area, and 2) determine ifthe population wasreduced based on harvest.The study was conducted on the CIWMA locatedin Desha County, Arkansas (Lat. 33°35' 47" N, Long.91°ll'2O' W). The CIWMA was approximately 3268 ha insize and lies within the levee of the Mississippi River. Thearea was divided into two parts, the mainland (2361 ha) andan island (907 ha) in the Mississippi River, but was managedas one property and one population. Topography was flatand elevation ranged from 33.5 to 46.0 m. The entire areawas subject to seasonal (winter-spring) flooding. Cover typeswere bottomland hardwood forests, cottonwood {Populusdeltoides) plantations, open fields, and food plots. Dominanttree species were oaks (Quercus spp.), pecan (Caryaillinoensis), and cottonwood. Mean total precipitation forFebruary and March was 13.34 cm and 13.46 cm,respectively. The mean minimum temperature duringFebruary and March was 2°C and 6.5°C, respectively(Dermott, AR, Station 031962).Non-overlapping, parallel transects were establishedand surveyed from a Cessna 182 fixed-wing aircraft.Transects were approximately 400 m apart. The site wassurveyed once each night on 8 and 9March 2003 and on 20,21, 22, and 27 February 2004. Flights were conducted atapproximately 457 m above ground level (AGL),and heightAGL was maintained using an on-board altimeter; resultingstrip transects were approximately 110 m wide. Flights wereconducted between 2000 and 2300 hrs in 2003 and between2300 hrs and 0600 hrs in 2004. Flights were conducted atJournal of the Arkansas Academy of Science, Vol. 59, 2005199Journal of the Arkansas Academy of Science, Vol. 59 [2005], Art. 28Published by Arkansas Academy of Science, 2005200Response of an Arkansas White-tailed Deer Population to Harvestdifferent times the second year in an attempt to maximizethe detection of thermal signatures. Flight paths (lat, long.,WGS84), altitude (ft), speed (mph), date and time werecollected by an onboard Global Positioning System (GPS)unit. The GPS signal was routed through a video encoder-decoder (VED). Locations of the plane obtained from theGPS unit were recorded on the audio portion of the videotape. The VED continuously labeled the video tape withposition, time, date, speed, and altitude information.Surveys were conducted using an IR-M700 thermalinfrared imager (Mitsubishi, Inc., Ontario, Canada) with a50 mm lens mounted in the belly of the plane in a fixed,vertical position. Wavelengths ranging from 1.2 to 5.9 _mwere used. The detector array size was 801 x 512 pixels witha sensitivity of 0.08 oC. Output was conducted through anRS170, 75 _ connection to a digital video camera (SonyDCR-TRV1000). Video was reviewed using a 33 cm, 1000line resolution, black and white monitor (Sony PVM-137).We used area sampling to estimate deer density in theCIWMA. The assumption made when using area samplingis that all animals are detected within the area surveyed. Ahigh rate ofdetection (94%) was reported for thermal targetsin associated research (Kissell and Tappe, 2004). Thenumber of deer observed in each strip transect wasrecorded. Double counting was prevented by use of GPSlocations integrated with videography and spacing oftransects (Naugle et al., 1996). GPS data were transferredinto a geographic information system (GIS). Length andwidth of transects were used to compute the area sampledduring each survey. We assumed an average altitude of 457m AGL for the purpose of calculating the area surveyed.Density was calculated as the number of deer recorded perunit area, and nights were used as replicates.A comparison of density estimates between years for themainland and the island was conducted using t-tests adjustedfor unequal variance when necessary (SAS Institute, Inc.,Cary, N.C.). Allanalyses were conducted with _ = 0.05.Recruitment was assessed using spotlight surveysconducted from the back of a pickup truck moving < 8km/hr. Surveys were conducted during January 2004following the hunting season. Both sides of the road werescanned using a 750,000 candle power spotlight. Upondetection of animals, the age (adult or juvenile), sex, time,and group number were recorded. Surveys began at least 1hr after sundown and continued until a pre-determinedroute was completed. Surveys were conducted nightly until100 does were observed. The number of fawns per 100 doeswas calculated to represent recruitment. Harvest data wereprovided by the AGFC. During 2003, 33 transects on themainland and 18 transects on the island were surveyed, andin 2004, 84 transects on the mainland and 47 transects onthe island were surveyed. The strip transect area coveredduring the surveys in 2003 varied from 434 ac (175.6 ha) to1248 ac (505.1 ha), and from 621 ac (251.3 ha) to 1344 ac(.543.9 ha) in 2004 (Table 1). The mean density was 1 deeper 7.4 ac (3.0 ha) and 1 deer per 8.8 ac (3.6 ha) on thmainland in 2003 and 2004, respectively. The meaipopulation sizes on the mainland during the winters of 200.and 2004 were estimated to be ~ 788 and ~ 659 deeirespectively.No significant differences were found between years fothe densities on the mainland (p = 0.300, t = 1.19) or th<island (p = 0.397, t =1.38). Only two replicate flights wenobtained during 2003 and this resulted in more variancecompared to that obtained from 4 replicates in 2004. Adifference between densities on the island and mainlandduring 2004 (p = 0.003, t = 4.96) existed but was notdetected in 2003 (p = 0.205, t = 1.86) due to the variance.Though conditions were good during both nights thattransects were flown in 2003, slightly poorer conditionswere experienced the second night. Daytime heatingtranslated into greater thermal loading of vegetation andwater. This may partially explain why density estimatesfrom the second flight were slightly lower than those fromthe first flight. We flew after sunset and prior to 0100 hrs. Tominimize the effects of thermal loading, flights wereconducted later in the night in 2004. Variability of detectionwas much higher on the island compared to the mainland.We believe this may have been due to either the poorerconditions experienced during the second flight, a change indeer behavior (e.g., animals moving off the island or beingbedded under vegetation), or a combination of these factors.While there was no difference in deer density betweenyears, more deer were observed on the island in2004 (Table1), the year following the first deer harvest season. Deer areknown to increase movements, increase home range size,and even shift activity centers in response to huntingpressure (Root et al., 1988). Itis possible that deer moved tothe island in response to hunting pressure on the mainlandand remained there at least through February when theflights were conducted. Assuming that the increase innumbers observed on the island was due to movement, it isnot known whether the movements were permanentbecause no active radio-telemetry work was under way atthe time. Another possible explanation is that the deerpopulation on the island increased from one year to thenext. We believe this is very unlikely, however, due to therelatively poor habitat on the island.In addition to the density data, spotlighting surveysindicated 32.2 fawns: 100 does (recruitment) and 15.7 bucksper 100 does. The level of recruitment suggested apopulation above carrying capacity. Poor recruitment is afunction of population density (Gilbert and Raedeke, 2004)and nutrition (Fryxell et al., 1991; McCullough, 2001).Nutrition most likely has a time-lag effect on recruitment(Fryxell et al., 1991), and managers should expect a slowrecovery due to nutrition-mediated recruitment whendensities have been high for a prolonged period of time.Journal of the Arkansas Academy of Science, Vol.59, 2005200Journal of the Arkansas Academy of Science, Vol. 59 [2005], Art. 28https://scholarworks.uark.edu/jaas/vol59/iss1/28201Robert E. Kissell,Jr. and Philip A. Tapperhe CIWMA deer population is an exemplary model ofhese conditions.The AGFC reported a harvest of 181 deer during the2003-2004 season, of which 157 were does (C. Gray,Arkansas Deer Program Coordinator, pers. coram.). Inresponse to the failure of harvest to initially reduce thepopulation, AGFC changed their harvest strategy toencourage the harvest of more does. During the 2004-2005deer season, a total of 269 deer was harvested, of which 189were does (C. Gray, pers. comm.). While a density estimatewas not provided during winter 2005, it is believed that asufficient number of animals were harvested to begindecreasing the population.We recommend further estimation of populationparameters annually because harvest is skewed toward does,a sizeable proportion of the population is being harvested,and the duration of a nutrition-mediated time-lag inrecruitment is unknown. This work serves as a model forwhite-tailed deer management in Arkansas and encouragesmanagers and biologists to make decisions based onpopulation parameter estimation and not indices.Acknowledgments.— The authors wish to thank L.Davisfor providing valuable information, assistance,and professionalism in flying. We also thank C. Gray andother personnel of the Arkansas Game and FishCommission (AGFC) Southeast Regional Office forproviding in-kind support of this and associated research.Funding was provided by AGFC and the Arkansas ForestResources Center.Table 1. Density estimates (number of deer per acre; ha are inparentheses) of white-tailed deer on Choctaw Island WildlifeManagement Area, Desha County, Arkansas, calculated from aerial thermal infrared videography during 8-9 March 2003 and20-27 February 2004. See text for description of Island and Mainland.Date Acres Number of Density EstimatedSite flown sampled (ha) deer observed #deer/acre Mean(ha) S.E.(ha) number ofdeerIsland 8 March 2003 434(176) 20 0.046(0.114)9 March 2003 660 (267) 12 0.018 (0.045) 0.026 (0.065) 0.014 (0.035) 58Mainland 8 March 2003 1163(471) 194 0.167(0.417)9 March 2003 1248(501) 144 0.115(0.286) 0.135(0.333) 0.026(0.066) 788Island 20 February 2004 621 (251) 50 0.081 (0.200)21 February 2004 642(260) 44 0.068(0.169)22 February 2004 676(274) 40 0.059(0.147)27 February 2004 673 (272) 39 0.058 (0.143) 0.065 (0.161) 0.005 (0.013) 147nland20 February 2004 1332(539) 148 0.111(0.278)21 February 2004 1328(537) 149 0.112(0.278)22 February 2004 1333 (540) 185 0.139 (0.345)27 February 2004 1344(544) 131 0.097(0.238) 0.114(0.278) 0.009(0.022) 659Journal of the Arkansas Academy of Science, Vol. 59, 2005201Journal of the Arkansas Academy of Science, Vol. 59 [2005], Art. 28Published by Arkansas Academy of Science, 2005202Response of an Arkansas White-tailed Deer Population to HarvestLiterature CitedBartmann, RM, GC White, LHCarpenter, and RAGarrott. 1987. Aerial mark-recapture estimates of confinedmule deer inpinyon-juniper woodland. Journal of WildlifeManagement 51:41-46.Buckland, ST, DR Anderson, KP Burnham, and JLLaake. 1993. Distance sampling: estimating abundance ofbiological populations. Chapman and Hall, London,reprinted 1999 by RUWPA, University St. Andrews,Scotland, 446 p.Downing, RL. 1980. Vital statistics of animalpopulations. Pp. 247-267 In Wildlife managementtechniques manual. Fourth ed., rev. (S. D. Schemnitz, ed.).The WildlifeSociety, Washington, DC.Dusek, GL, RJ Mackie, JD Herriges, Jr., and BBCompton. 1989. Population ecology of white-tailed deeralong the lower Yellowstone River. Wildlife Monograph.104:1-68.Fryxell, JM, DJ Hussell, AB Lambert, and PCSmith. 1991. Time lags and population fluctuations in white-tailed deer. Journal of Wildlife Management 55:377-385.Gilbert, BA, and KJ Raedeke. 2004. Recruitmentdynamics of black-tailed deer in the western Cascades.Journal of Wildlife Management 68:120-128.Ginnett, TF, and EL Butch-Young. 2000. Stochasticrecruitment in white-tailed deer along an environmentalgradient. Journal of Wildlife Management 64:713-720.Johnson, DH. 1996. Population analysis. Pp. 419-444,InResearch and management techniques for wildlife andhabitats. Fifth ed., rev. (T. A.Bookhout, ed.). The WildlifeSociety, Bethesda, MD.Kissell,Jr, RE, and PA Tappe. 2004. An assessmentof thermal infrared detection rates using white-tailed deersurrogates. Journal of the Arkansas Academy of Science58:70-73.Lancia, R A, JD Nichols, and KH Pollock. 1996.Estimating the number of animals in wildlife populations.Pp. 215-253, In Research and management techniques forwildlife and habitats. Fifth ed., rev. (T. A.Bookhout, ed.).The WildlifeSociety, Bethesda, MD.Lancia, RA, KH Pollock, JW Bishir, and MCConner. 1988. A white-tailed deer harvesting strategy.Journal of Wildlife Management 52:589-595.Lancia, RA, CS Rosenberry, and MC Conner.2000. Population parameters and their estimation. Pp. 64-83, InEcology and management of large animals in NorthAmerica (S. Demarais and P. R. Krausman, eds.). PrenticeHall,Upper Saddle River, New Jersey.Langdon, CA.2001. A comparison of white-tailed deerpopulation estimation methods in West Virginia.Unpublished MS thesis, West Virginia University,Morgantown, West Virginia. 119 pp.Lincoln, FC. 1930. Calculating waterfowl abundanceon the basis of banding returns. U.S. Department ofAgriculture, Circular No. 118.Lopez, RR, NJ Silvy, BL Pierce, PA Frank, MTWilson, and KMBurke. 2004. Population density of theendangered Florida Key deer. Journal of WildlifeManagement 68:570-575.McCullough, DR. 2001. The George Reserve deerherd. Blackburn Press, Caldwell, New Jersey. 271 pp.Naugle, DE,JA Jenks, and BJ Kernohan. 1996. Useof thermal infrared sensing to estimate density of white-tailed deer. Wildlife Society Bulletin 24:37-43.Peterson, CGJ. 1896. The yearly immigration of youngplaice into Limfjord from the German Sea. DanishBiological Station Report 6:1-48.Root, BG, EK Fritzell, and NF Giessman. 1988.Effects of intensive hunting on white-tailed deer movement.Wildlife Society Bulletin 16:145-151.Rotella,JJ, and JT Ratti. 1986. Test ofa critical densityindex assumption: a case study with gray partridge. Journalof Wildlife Management 50:532-539.Seber, GAF. 2002. The estimation of animalabundance and related parameters. Second ed. BlackburnPress, Caldwell, New Jersey 654 pp.Zippin, C. 1958. The removal method of populationestimation. Journal of WildlifeManagement 22:82-90.Journal of the Arkansas Academy of Science, Vol.59, 2005202Journal of the Arkansas Academy of Science, Vol. 59 [2005], Art. 28https://scholarworks.uark.edu/jaas/vol59/iss1/28

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Response of an Arkansas White-Tailed Deer Population to Harvest

ScholarWorks@UARK

Journal of the Arkansas Academy of ScienceVolume 59 Article 282005Response of an Arkansas White-Tailed DeerPopulation to HarvestRobert E. Kissell Jr.University of Arkansas at Monticello, kissell@uamont.eduPhilip A. TappeUniversity of Arkansas at MonticelloFollow this and additional works at: http://scholarworks.uark.edu/jaasPart of the Zoology CommonsThis article is available for use under the Creative Commons license: Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0). Users are able toread, download, copy, print, distribute, search, link to the full texts of these articles, or use them for any other lawful purpose, without asking priorpermission from the publisher or the author.This General Note is brought to you for free and open access by ScholarWorks@UARK. It has been accepted for inclusion in Journal of the ArkansasAcademy of Science by an authorized editor of ScholarWorks@UARK. For more information, please contact scholar@uark.edu.Recommended CitationKissell, Robert E. Jr. and Tappe, Philip A. (2005) "Response of an Arkansas White-Tailed Deer Population to Harvest," Journal of theArkansas Academy of Science: Vol. 59 , Article 28.Available at: http://scholarworks.uark.edu/jaas/vol59/iss1/28199Response of an Arkansas White-tailed Deer Population to HarvestRobert E. Kissell,Jr. and PhilipA.TappeArkansas Forest Resources Center, School ofForest Resources, University ofArkansas-Monticello, Monticello, AR 71656' Correspondent: kissell@uamont.eduHarvest management of game species for the purpose<»f maintaining or manipulating populations requiresestimation of at least 3 population parameters: populationsize (density), recruitment, and mortality. Knowledge ofthese parameters is important because hunters, as well asanti-hunters, and the general public call for managers beable to defend their management activities (Lancia et al.,2000). Managers most often use indices, such as number ofdeer observed per unit distance driven during a spot-lightsurvey, inplace of population parameters. Indoing so, theassumption is made that a constant, linear relationship existsbetween the index and the population parameter of interest(Lancia et al., 1996). Use of such indices is based ontradition, simplicity, and low cost. However, few indiceshave been validated (Rotella and Ratti, 1986), and noneserve as a perfect substitute for population parameterestimation.Different approaches are available to estimate density,"ecruitment, and mortality (Johnson, 1996; Lancia et al.,1996). Density estimation has been conducted using mark-recapture techniques (Peterson, 1896; Lincoln, 1930;Bartmann et al., 1987), distance sampling (Buckland et al.,1993), area sampling (Seber, 2002), and removal techniquesZippin, 1958; Lancia et al., 1988). For white-tailed deer inhe southeastern U.S., density estimates are most oftenderived using mark-recapture approaches, but distancesampling is becoming more widely used (Langdon, 2001;L,opez et al., 2004). Area sampling, which is most commonlylsed for large ungulates in the western U.S., is not veryipplicable in the southeastern U.S. due to limited visibilityising traditional techniques (e.g., helicopter surveys).however, advances in the use and technology of thermalnfrared imagery are changing the ability to employ areaampling during leaf-off conditions in deciduous hardwoodireas of the Southeast.Recruitment is typically estimated using a sex/age ratiotpproach (Downing, 1980; Ginnett and Butch-Young, 2000).Jopulation size is estimated and an independent estimate ofhe number of young per adult female (e.g., fawns/100 does)s applied to the population estimate. The manner in whichhe ratio is obtained varies depending upon location.Spotlighting is most commonly used to obtain ratios in theoutheastern U.S., whereas visual aerial surveys are used inhe western U.S.Estimation of mortality is directly provided by radio-elemetry (Lancia et al., 2000). Mortality estimation usingadio-telemetry, however, requires a great amount of timeand is financially expensive. Most mortality of white-taileddeer is due to harvest (Dusek et al., 1989), and harvest isusually used as an index to mortality.Population-parameter estimation has not been usedoften by managers for white-tailed deer in Arkansas. Withimplementation of new management strategies for white-tailed deer or acquisition of new properties, baseline datathat includes population parameters are useful to determinethe efficacy of the management strategies employed. TheArkansas Game and Fish Commission (AGFC) purchased anew property, the Choctaw Island Wildlife ManagementArea (CIWMA),inOctober 2001. The deer population wasnot hunted for 2 seasons following the purchase. The firsthunting season under the direction of the AGFC was duringfall 2003. Because the CIWMA was a newly acquiredwildlife management area, AGFC desired baseline data forwhite-tailed deer management. Our objectives were to 1)estimate winter deer density on Choctaw Island WildlifeManagement Area, and 2) determine ifthe population wasreduced based on harvest.The study was conducted on the CIWMA locatedin Desha County, Arkansas (Lat. 33°35' 47" N, Long.91°ll'2O' W). The CIWMA was approximately 3268 ha insize and lies within the levee of the Mississippi River. Thearea was divided into two parts, the mainland (2361 ha) andan island (907 ha) in the Mississippi River, but was managedas one property and one population. Topography was flatand elevation ranged from 33.5 to 46.0 m. The entire areawas subject to seasonal (winter-spring) flooding. Cover typeswere bottomland hardwood forests, cottonwood {Populusdeltoides) plantations, open fields, and food plots. Dominanttree species were oaks (Quercus spp.), pecan (Caryaillinoensis), and cottonwood. Mean total precipitation forFebruary and March was 13.34 cm and 13.46 cm,respectively. The mean minimum temperature duringFebruary and March was 2°C and 6.5°C, respectively(Dermott, AR, Station 031962).Non-overlapping, parallel transects were establishedand surveyed from a Cessna 182 fixed-wing aircraft.Transects were approximately 400 m apart. The site wassurveyed once each night on 8 and 9March 2003 and on 20,21, 22, and 27 February 2004. Flights were conducted atapproximately 457 m above ground level (AGL),and heightAGL was maintained using an on-board altimeter; resultingstrip transects were approximately 110 m wide. Flights wereconducted between 2000 and 2300 hrs in 2003 and between2300 hrs and 0600 hrs in 2004. Flights were conducted atJournal of the Arkansas Academy of Science, Vol. 59, 2005199Journal of the Arkansas Academy of Science, Vol. 59 [2005], Art. 28Published by Arkansas Academy of Science, 2005200Response of an Arkansas White-tailed Deer Population to Harvestdifferent times the second year in an attempt to maximizethe detection of thermal signatures. Flight paths (lat, long.,WGS84), altitude (ft), speed (mph), date and time werecollected by an onboard Global Positioning System (GPS)unit. The GPS signal was routed through a video encoder-decoder (VED). Locations of the plane obtained from theGPS unit were recorded on the audio portion of the videotape. The VED continuously labeled the video tape withposition, time, date, speed, and altitude information.Surveys were conducted using an IR-M700 thermalinfrared imager (Mitsubishi, Inc., Ontario, Canada) with a50 mm lens mounted in the belly of the plane in a fixed,vertical position. Wavelengths ranging from 1.2 to 5.9 _mwere used. The detector array size was 801 x 512 pixels witha sensitivity of 0.08 oC. Output was conducted through anRS170, 75 _ connection to a digital video camera (SonyDCR-TRV1000). Video was reviewed using a 33 cm, 1000line resolution, black and white monitor (Sony PVM-137).We used area sampling to estimate deer density in theCIWMA. The assumption made when using area samplingis that all animals are detected within the area surveyed. Ahigh rate ofdetection (94%) was reported for thermal targetsin associated research (Kissell and Tappe, 2004). Thenumber of deer observed in each strip transect wasrecorded. Double counting was prevented by use of GPSlocations integrated with videography and spacing oftransects (Naugle et al., 1996). GPS data were transferredinto a geographic information system (GIS). Length andwidth of transects were used to compute the area sampledduring each survey. We assumed an average altitude of 457m AGL for the purpose of calculating the area surveyed.Density was calculated as the number of deer recorded perunit area, and nights were used as replicates.A comparison of density estimates between years for themainland and the island was conducted using t-tests adjustedfor unequal variance when necessary (SAS Institute, Inc.,Cary, N.C.). Allanalyses were conducted with _ = 0.05.Recruitment was assessed using spotlight surveysconducted from the back of a pickup truck moving < 8km/hr. Surveys were conducted during January 2004following the hunting season. Both sides of the road werescanned using a 750,000 candle power spotlight. Upondetection of animals, the age (adult or juvenile), sex, time,and group number were recorded. Surveys began at least 1hr after sundown and continued until a pre-determinedroute was completed. Surveys were conducted nightly until100 does were observed. The number of fawns per 100 doeswas calculated to represent recruitment. Harvest data wereprovided by the AGFC. During 2003, 33 transects on themainland and 18 transects on the island were surveyed, andin 2004, 84 transects on the mainland and 47 transects onthe island were surveyed. The strip transect area coveredduring the surveys in 2003 varied from 434 ac (175.6 ha) to1248 ac (505.1 ha), and from 621 ac (251.3 ha) to 1344 ac(.543.9 ha) in 2004 (Table 1). The mean density was 1 deeper 7.4 ac (3.0 ha) and 1 deer per 8.8 ac (3.6 ha) on thmainland in 2003 and 2004, respectively. The meaipopulation sizes on the mainland during the winters of 200.and 2004 were estimated to be ~ 788 and ~ 659 deeirespectively.No significant differences were found between years fothe densities on the mainland (p = 0.300, t = 1.19) or th<island (p = 0.397, t =1.38). Only two replicate flights wenobtained during 2003 and this resulted in more variancecompared to that obtained from 4 replicates in 2004. Adifference between densities on the island and mainlandduring 2004 (p = 0.003, t = 4.96) existed but was notdetected in 2003 (p = 0.205, t = 1.86) due to the variance.Though conditions were good during both nights thattransects were flown in 2003, slightly poorer conditionswere experienced the second night. Daytime heatingtranslated into greater thermal loading of vegetation andwater. This may partially explain why density estimatesfrom the second flight were slightly lower than those fromthe first flight. We flew after sunset and prior to 0100 hrs. Tominimize the effects of thermal loading, flights wereconducted later in the night in 2004. Variability of detectionwas much higher on the island compared to the mainland.We believe this may have been due to either the poorerconditions experienced during the second flight, a change indeer behavior (e.g., animals moving off the island or beingbedded under vegetation), or a combination of these factors.While there was no difference in deer density betweenyears, more deer were observed on the island in2004 (Table1), the year following the first deer harvest season. Deer areknown to increase movements, increase home range size,and even shift activity centers in response to huntingpressure (Root et al., 1988). Itis possible that deer moved tothe island in response to hunting pressure on the mainlandand remained there at least through February when theflights were conducted. Assuming that the increase innumbers observed on the island was due to movement, it isnot known whether the movements were permanentbecause no active radio-telemetry work was under way atthe time. Another possible explanation is that the deerpopulation on the island increased from one year to thenext. We believe this is very unlikely, however, due to therelatively poor habitat on the island.In addition to the density data, spotlighting surveysindicated 32.2 fawns: 100 does (recruitment) and 15.7 bucksper 100 does. The level of recruitment suggested apopulation above carrying capacity. Poor recruitment is afunction of population density (Gilbert and Raedeke, 2004)and nutrition (Fryxell et al., 1991; McCullough, 2001).Nutrition most likely has a time-lag effect on recruitment(Fryxell et al., 1991), and managers should expect a slowrecovery due to nutrition-mediated recruitment whendensities have been high for a prolonged period of time.Journal of the Arkansas Academy of Science, Vol.59, 2005200Journal of the Arkansas Academy of Science, Vol. 59 [2005], Art. 28http://scholarworks.uark.edu/jaas/vol59/iss1/28201Robert E. Kissell,Jr. and Philip A. Tapperhe CIWMA deer population is an exemplary model ofhese conditions.The AGFC reported a harvest of 181 deer during the2003-2004 season, of which 157 were does (C. Gray,Arkansas Deer Program Coordinator, pers. coram.). Inresponse to the failure of harvest to initially reduce thepopulation, AGFC changed their harvest strategy toencourage the harvest of more does. During the 2004-2005deer season, a total of 269 deer was harvested, of which 189were does (C. Gray, pers. comm.). While a density estimatewas not provided during winter 2005, it is believed that asufficient number of animals were harvested to begindecreasing the population.We recommend further estimation of populationparameters annually because harvest is skewed toward does,a sizeable proportion of the population is being harvested,and the duration of a nutrition-mediated time-lag inrecruitment is unknown. This work serves as a model forwhite-tailed deer management in Arkansas and encouragesmanagers and biologists to make decisions based onpopulation parameter estimation and not indices.Acknowledgments.— The authors wish to thank L.Davisfor providing valuable information, assistance,and professionalism in flying. We also thank C. Gray andother personnel of the Arkansas Game and FishCommission (AGFC) Southeast Regional Office forproviding in-kind support of this and associated research.Funding was provided by AGFC and the Arkansas ForestResources Center.Table 1. Density estimates (number of deer per acre; ha are inparentheses) of white-tailed deer on Choctaw Island WildlifeManagement Area, Desha County, Arkansas, calculated from aerial thermal infrared videography during 8-9 March 2003 and20-27 February 2004. See text for description of Island and Mainland.Date Acres Number of Density EstimatedSite flown sampled (ha) deer observed #deer/acre Mean(ha) S.E.(ha) number ofdeerIsland 8 March 2003 434(176) 20 0.046(0.114)9 March 2003 660 (267) 12 0.018 (0.045) 0.026 (0.065) 0.014 (0.035) 58Mainland 8 March 2003 1163(471) 194 0.167(0.417)9 March 2003 1248(501) 144 0.115(0.286) 0.135(0.333) 0.026(0.066) 788Island 20 February 2004 621 (251) 50 0.081 (0.200)21 February 2004 642(260) 44 0.068(0.169)22 February 2004 676(274) 40 0.059(0.147)27 February 2004 673 (272) 39 0.058 (0.143) 0.065 (0.161) 0.005 (0.013) 147nland20 February 2004 1332(539) 148 0.111(0.278)21 February 2004 1328(537) 149 0.112(0.278)22 February 2004 1333 (540) 185 0.139 (0.345)27 February 2004 1344(544) 131 0.097(0.238) 0.114(0.278) 0.009(0.022) 659Journal of the Arkansas Academy of Science, Vol. 59, 2005201Journal of the Arkansas Academy of Science, Vol. 59 [2005], Art. 28Published by Arkansas Academy of Science, 2005202Response of an Arkansas White-tailed Deer Population to HarvestLiterature CitedBartmann, RM, GC White, LHCarpenter, and RAGarrott. 1987. 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Response of an Arkansas White-Tailed Deer Population to Harvest

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