National Park Service 

U.S. Department of the Interior 

Natural Resource Program Center 

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

Natural Resource Report NPS/HTLN/NRR—2007/014 

protecting the habitat of our heritage 

A Heartland Network Monitoring Protocol 
ON THE COVER 

Herbert Hoover birthplace cottage at Herbert Hoover NHS, prescribed fire at Tallgrass Prairie NPres, aquatic invertebrate 

monitoring at George Washington Carver NM, the Mississippi River at Effigy Mounds NM. 
White-tailed Deer Monitoring Protocol for the Heartland Network Inventory and 

Monitoring Program 

Natural Resource Report NPS/HTLN/NRR—2007/014 

David G. Peitz, J. Tyler Cribbs, Jennifer L. Haack, Gareth A. Rowell, Lloyd W. Morrison, and 

Mike D. DeBacker 

National Park Service 

Heartland I&M Network 

Wilson’s Creek National Battlefield 

6424 West Farm Road 182 

Republic, MO 65738 

August 2007 

U.S. Department of the Interior 

National Park Service 

Natural Resource Program Center 

Fort Collins, Colorado 
ii

The Natural Resource Publication series addresses natural resource topics that are of interest and 

applicability to a broad readership in the National Park Service and to others in the management 

of natural resources, including the scientific community, the public, and the NPS conservation 

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and is designed and published in a professional manner. 

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natural resource management information with managerial application. The series targets a 

general, diverse audience, and may contain NPS policy considerations or address sensitive issues 

of management applicability. Examples of the diverse array of reports published in this series 

include vital signs monitoring plans; monitoring protocols; "how to" resource management 

papers; proceedings of resource management workshops or conferences; annual reports of 

resource programs or divisions of the Natural Resource Program Center; resource action plans; 

fact sheets; and regularly-published newsletters. 

Views, statements, findings, conclusions, recommendations and data in this report are solely 

those of the author(s) and do not necessarily reflect views and policies of the U.S. Department of 

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endorsement or recommendation for use by the National Park Service. 

Printed copies of reports in these series may be produced in a limited quantity and they are only 

available as long as the supply lasts. This report is also available from the Heartland I&M 

Network website (http://www.nature.nps.gov/im/units/HTLN) on the internet, or by sending a 

request to the address on the back cover. 

Please cite this publication as: 

Peitz, D. G., J. T. Cribbs, J. L. Haack, G. A. Rowell, L. W. Morrison, and M. D. DeBacker. 

2007. White-tailed Deer Monitoring Protocol for the Heartland Network Inventory and 

Monitoring Program. Natural Resource Report NPS/HTLN/NRR—2007/014. National Park 

Service, Fort Collins, Colorado. 

NPS D-70, August 2007
iii

Acknowledgements 

The National Park Service’s Inventory and Monitoring Program provided funding for the 

development of this white-tailed deer monitoring protocol, and continue to fund monitoring of 

the resource in network parks. Numerous NPS personnel have contributed in-kind support to the 

development of this protocol, and continue to assist with annual surveys. We acknowledge 

important input from resource managers during a breakout session of the 2005 Heartland 

Network annual meeting to help refine the monitoring objectives. This protocol has benefited 

from comments by Dr Paul Lukacs on an earlier version. Peer review by Dr. Lynn Robbins, Dr. 

Jonathan Jenks, and Dr. David Leslie greatly improved the final protocol. 
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Contents 

Page 

Contents ........................................................................................................................................ iiv 

List of Figures............................................................................................................................... vii 

List of Tables ................................................................................................................................ vii 

1.0 Background and Objectives ......................................................................................................1 

1.1 Issue Being Addressed and Rationale for Monitoring White-tailed Deer Populations .... 1 

1.2 Historical Development of White-Tailed Deer Monitoring in Network Parks................. 2 

1.3 Measurable Objectives...................................................................................................... 3 

2.0 Sampling Design........................................................................................................................3 

2.1 Population being Monitored ............................................................................................. 3 

2.2 Spatial Design ................................................................................................................... 4 

2.3 Revisit Design................................................................................................................... 8 

2.4 Response Design............................................................................................................... 8 

2.5 Rationale for Selecting this Sampling Design over Others .............................................. 8 

3.0 Field Methods ..........................................................................................................................10 

3.1 Field Season Preparations, Field Schedule and Equipment Setup.................................. 10 

3.2 Sampling Methods .......................................................................................................... 10 

3.3 Conducting the Spotlight Survey.................................................................................... 11 

3.4 Establishing Visibility during Surveys ........................................................................... 11 

4.0 Data Management ....................................................................................................................12 

4.1 Overview of Database Design ........................................................................................ 12 

4.2 Metadata Procedures....................................................................................................... 12 

4.3 Data Archival Procedures ............................................................................................... 13 
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Contents 

Page

5.0 Analysis and Reporting............................................................................................................13 

5.1 Recommendations for Routine Data Summaries and Analyses ..................................... 13 

5.2 Recommendations for Long-term Trend Analyses......................................................... 14 

5.3 Recommendations for Reporting Results ....................................................................... 14 

6.0 Personnel Requirements and Training.....................................................................................14 

6.1 Roles and Responsibilities .............................................................................................. 14 

6.2 Qualifications and Training ............................................................................................ 15 

7.0 Operational Requirements .......................................................................................................15 

7.1 Annual Workload and Field Schedule ............................................................................ 15 

7.2 Facility and Equipment Needs........................................................................................ 15 

7.3 Startup Costs and Budget Considerations....................................................................... 15 

7.4 Procedure for Revising the Protocol and Archiving Previous Versions......................... 16 

8.0 References................................................................................................................................16 

9.0 Supplemental Documents ........................................................................................................19 

9.1 Supplemental Document 1: Options available for white-tailed deer monitoring ........... 19 

9.2 Supplemental Document 2: Notes from the white-tailed deer breakout session, 3 August 

2005, Hopewell Culture HNP............................................................................................... 22 

9.3 Supplemental Document 3: Recommendations for conducting white-tailed deer surveys

............................................................................................................................................... 25 

9.4 Supplemental Document 4: 2005 White-tailed deer counts by time after official sunset

............................................................................................................................................... 27 

10.0 Standard Operating Procedures..............................................................................................28 

 
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Contents 

Page 

10.1 Standard Operating Procedure 1: Before the Field Season........................................28 

10.2 Standard Operating Procedure 2: Training Observers...............................................31 

10.3 Standard Operating Procedure 3: Using the Global Positioning System...................33 

10.4 Standard Operating Procedure 4: Establishing Survey Routes..................................34 

10.5 Standard Operating Procedure 5: Conducting the Spotlight Survey .........................36 

10.6 Standard Operating Procedure 6: Establishing Visibility during Surveys.................46 

10.7 Standard Operating Procedure 7: Geospatial Data Management ..............................52 

10.8 Standard Operating Procedure 8: Data Management.................................................60 

10.9 Standard Operating Procedure 9: Data Summary and Analysis ................................65 

10.10 Standard Operating Procedure 10: Reporting..........................................................69 

10.11 Standard Operating Procedure 11: Procedures and Equipment Storage after the 

Field Season.......................................................................................................................72 

10.12 Standard Operating Procedure 12: Revising the Protocol .......................................74 
vii

List of Figures 

 Page 

Figure 1. White-tailed deer survey route at Arkansas Post National Memorial, Arkansas.......5

Figure 2. White-tailed deer survey route at Pea Ridge National Military Park, Arkansas........6

Figure 3. White-tailed deer survey route at Wilson’s Creek National Battlefield, Missouri......7

List of Tables 

 Page

Table 1. Startup and annual costs, for monitoring white-tailed deer populations in Heartland 

Network Inventory and Monitoring Program parks....................................................16 
1

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

1.0 Background and Objectives 

1.1 Issue Being Addressed and Rationale for Monitoring White-tailed Deer 

Populations 

Since European settlement, white-tailed deer (Odocoileus virginianus) populations in North 

America have experienced enormous changes in size and distribution. Once abundant, deer 

numbers declined to near extinction by the early 1900s. Clearing of forested lands and 

unrestricted hunting contributed heavily to the decline of this species (Stoll and Donohoe 1973, 

Dennis 1983). Declines in deer numbers were especially prevalent in the East and Midwest 

sections of the country where much of the land was converted for row-crop farming. 

Regulated white-tailed deer hunting and extermination of most of their natural predators has led 

to unprecedented population growth throughout their range. With natural deer habitat severely 

reduced, row-crop agriculture and other agriculture practices provide artificial food sources that 

deer utilize. The ability of white-tailed deer to adapt to human disturbance has also aided in the 

recovery of this species. Urban sprawl benefits deer by fragmenting continuous blocks of 

forested lands into small sections with increased edge habitat favored by deer and rarely 

available for hunting. Therefore, deer experience high rates of population growth as long as food 

is available in these small blocks of patchy habitat. Grass and forb production is greater in these 

areas, as is mast production by oaks, hickories, and other trees when compared to larger blocks 

of forested land (Peitz et al. 2001). Urban sprawl also redistributes deer by eliminating habitat in 

one area, thereby concentrating deer in available habitat in another (Shafer-Nolan 1997). 

Deer become vulnerable to overpopulation, disease, and starvation in the absence of natural 

predators and hunting. When deer occur in high densities, diseases are transmitted more readily. 

In years when forage or mast production is restricted due to climatic conditions, starvation or 

poor herd health can occur. High deer populations also contribute to over-browsing of 

vegetation, which leads to plant mortality, decreased plant reproduction, and may favor less 

preferred exotic species (McShea and Rappole 1997). This shift in species assemblages can 

reduce plant diversity at a local level and cause changes in the functioning of prairie and 

woodland communities. Rare and sensitive plant species may be influenced negatively by deer 

foraging, although the influence of deer on the status of most rare and sensitive plant species is 

largely unknown. Many studies have shown that deer can have a negative effect on developing 

forestland (Crouch and Paulson 1968, Horsely and Marquis 1983, Marquis 1981). Browsing on 

young tree seedlings causes stunted growth as well as mortality (Michael 1992, Mladenoff and 

Stearns 1993). Research has shown that in some situations damage from deer, as well as mice 

and rabbits, may be a key impediment to forest restoration (Crouch and Paulson 1968, Strole and 

Anderson 1992). 

White-tailed deer are often viewed as an important component of park ecosystems. Deer have a 

tremendous following among the public and many parks provide information on the status of 
2

deer through their interpretive programs. This information is generally anecdotal in nature, 

however. White-tailed deer can present a safety hazard to motorist and park visitors when 

populations are high. High deer numbers increase the number of vehicle-deer collisions and the 

resulting property damage and personal injuries. In some cases, vehicle-deer collisions can 

result in the loss of human life. Deer also disperse ticks that may carry Lyme disease (Connelly 

et al. 1987), a debilitating immune system illness transmitted to humans by the bite of ticks. 

Ticks carrying other diseases transmittable to humans, such as Rocky Mountain Spotted Fever 

and Ehrlichiosis, may be spread by deer as well. Information on the status and trends in deer 

population size helps park managers determine if control measures are necessary in order to 

protect other park resources and improve visitor safety. 

Against a backdrop of urban sprawl, altered ecosystems, and concerns over visitor safety on 

National Park Service lands, we proposed monitoring white-tailed deer populations. Long-term 

trends in deer abundance provide one measure of assessing their potential as a problem for a 

park. Documenting long-term patterns in deer numbers allows one to evaluate correlations with 

changes in vegetation (e.g., through restoration of the cultural landscape). With this information 

resource managers can more effectively identify and potentially mitigate damage caused to 

vegetation communities and endangered plant populations by deer. Monitoring data also helps 

managers assess safety risks from collisions and disease transmission. Long-term monitoring of 

deer numbers is critical in evaluating any population control measures a park may implement. 

1.2 Historical Development of White-Tailed Deer Monitoring in Network Parks 

Monitoring trends in the composition and abundance of white-tailed deer populations is critical 

to understanding herd health over the long-term (Gee et al. 1994). The impacts of deer on 

vegetation, disease transmission, and vehicle-deer collisions can only be thoroughly assessed 

with a good knowledge of trends in population size. Monitoring deer populations may help 

protect ecosystem integrity, which is defined as the capability of an environment to support and 

maintain a balanced, integrated, adaptive community of organisms having a species composition, 

diversity, and functional organization comparable to that of natural habitat of the region (Karr 

and Dudley 1981). Information on deer population trends is vital when mitigating visitor health 

concerns and the incidents of vehicle-deer collisions. 

Deer surveys have been conducted sporadically in several network parks. Homestead National 

Monument of America, Nebraska, for example, has used rushing surveys to assess deer numbers. 

While this method is effective in small parks, it is of little value on large acreages (>100 

hectares). Cuyahoga Valley National Recreation Area, Ohio, has an ongoing monitoring 

program that has been in effect since 1988. Spotlight surveys taken from a train and along 

roadways located within the park are utilized to assess deer numbers. Spotlight counts have also 

been used by graduate students from the University of Arkansas-Monticello to assess deer 

numbers at Arkansas Post National Memorial, Arkansas. During 2003, Wilson’s Creek National 

Battlefield staff assisted students from Missouri State University in surveying deer numbers as 

part of a class project. This protocol serves to formalize and standardize deer surveying 

techniques across the Heartland Network Inventory and Monitoring Program (HTLN). 
3

During initial protocol development, “Distance” sampling techniques where examined. 

However, assumptions critical to the use of “Distance” sampling methods could not be met and 

this method of surveying deer was dropped. At an annual meeting of the HTLN in August 2005, 

many aspects of deer monitoring were discussed with natural resource managers from various 

network parks. Issues such as the impact of deer on vegetation, disease transmission, concern 

over vehicle-deer collisions in and around parks, and the impacts of deer on neighboring private 

lands were examined. In the end, resource managers felt tracking an index of deer numbers 

through time was the most efficient and sustainable use of resources. The impacts of deer on 

vegetation, disease transmission, and vehicle-deer collisions can only be thoroughly assessed 

with a good knowledge of trends in population size. Resource managers, using trend data, will 

secure funding to research and mitigate the impacts of deer as needed. 

Measurable Objectives 

1. Document annual changes in white-tailed deer numbers. Justification: Significant 

annual changes in deer numbers may signal the presence of illegal deer harvest, disease, 

or other acute factors of concern for park management.

2. Determine long-term trends in white-tailed deer numbers. Justification: Understanding 

decadal trends in deer number will help park management determine if measures need to 

be taken to maintain herd health, minimize vegetation damage within a park, or alleviate 

visitor health concerns.

3. Annually map locations of white-tailed deer observed. Justification: Mapping deer 

locations allows park management to assess the influences of management actions on 

deer usage of an area, habitat type, etc.

2.0 Sampling Design 

2.1 Population being Monitored

The populations of interest are the white-tailed deer herds within each park. For safety reasons, 

sampling will be done along existing park roads rather than random transects. Because the 

habitat types encountered along park roads are not necessarily in proportion to the distribution of 

habitat types in the overall parks, and the location of park roads may affect the distribution of 

deer, resulting density estimates may not be representative of absolute densities within the 

overall park. Thus, our density estimates are considered to be an index of relative population 

density, which is positively correlated with absolute population density, but to an unknown 

degree. 

Sampling is limited to winter months, before spring green up (January through mid March). The 

deer present at this time will be impacting herd size and park resources through the next year. In 

many situations, a knowledge of the buck:doe and fawn:doe ratios would be desirable. But most 

bucks will have shed their antlers by this time and fawns will be of sufficient size to be mistaken 

as older does. Therefore, buck:doe and fawn:doe ratios may not be calculated. Overall herd 

density is best estimated during winter months, however, as declines in deer numbers through 

fawn mortality and hunting around park lands have stabilized. It is more desirable to have an 

estimate of herd densities on National Park Service lands than having information on herd ratios. 
4

If these same lands were to be hunted, then ratios would assume more importance and more 

intense sampling to estimate each would be justified. 

Although it is not possible to determine the absolute number of deer in a park at any time from 

these methods, such information on relative abundance is of value in detecting trends. In a 

meeting regarding white-tailed deer monitoring held in 2005, resource managers from the 

representative parks indicated that determining absolute deer density in the parks was not a 

priority. Resource managers did desire information on changes in deer populations over time, so 

that if white-tailed deer ever became an important management issue, data would be available 

indicating population trends. More in-depth (and expensive) surveys aimed at estimating 

absolute abundances could then be implemented (see Supplemental Document #2). 

2.2 Spatial Design 

Sampling locations or ‘routes’ are selected as described in SOP #4, “Establishing Survey 

Routes”. Maps showing the survey routes at Arkansas Post National Monument, Arkansas; Pea 

Ridge National Military Park, Arkansas; and Wilson’s Creek National Battlefield, Missouri are 

given in Figures 1 – 3. 
5

Figure 1. White-tailed deer survey route at Arkansas Post National Memorial, Arkansas. 
6

Figure 2. White-tailed deer survey route at Pea Ridge National Military Park, Arkansas. 
7

Figure 3. White-tailed deer survey route at Wilson’s Creek National Battlefield, Missouri. 
8

2.3 Revisit Design 

All survey routes within each HTLN park unit monitored for white-tailed deer will be sampled 

annually. To obtain a measure of variability, a minimum of three density estimates from three 

different nights are needed. Ideally, six density estimates from six different nights will be 

obtained annually. The maximum count from three consecutive surveys conducted each night 

will be used as the density estimate for that date. Visibility assessments will be recorded on the 

first night a survey is conducted to get an annual estimate of the area over which deer can be 

seen. Changing vegetation in each HTLN park requires that visibility estimates be made each 

year and that the area sampled is not predetermined from aerial photos or maps. Visibility 

assessments begin as soon as the last spotlight survey is completed. 

2.4 Response Design 

Surveys commence one hour after official sunset and follow predetermined survey routes. 

An index of relative density is obtained by counting the number of deer observed with a spotlight 

along the monitoring route. Deer positions are recorded as distance and azimuth from the 

observation vehicle, and later converted to UTM coordinates using GIS. The observable area is 

defined by taking measurements perpendicular to the sample route out to a distance beyond 

which deer are not visible. This area is determined at 0.16 km (1/10th mile) intervals along the 

survey route, immediately following deer counts on the first survey day. 

2.5 Rationale for Selecting this Sampling Design over Others 

Dozens of different monitoring programs utilizing a multitude of sampling approaches are 

currently in place throughout North America to determine local white-tailed deer population 

densities. Most common survey methods allow for population estimates, but no single method 

will adequately sample the complete population. The spotlight survey is widely accepted as a 

practical method for estimating trends in the density of a deer population in an area. Sampling 

involves spotlighting deer at night to obtain some estimate of the number of deer present in an 

area and then determining the total area visible during the survey. Deer density is simply the 

number of deer observed divided by the area visible during the survey. In practice, the method 

documented in this protocol is basically a line transect estimate of deer numbers with the total 

area visible during a survey determined. 

Aerial surveys, mark and recapture surveys, fecal pellet counts, the use of infrared triggered 

cameras, ‘rushing’, and distance sampling are different types of deer survey methods that have 

been considered for use in estimating population densities and size of white-tailed deer herds in 

HTLN parks. Camouflaging ground cover and limited visibility from the air inhibit accurate 

aerial surveys; furthermore aerial surveys are expensive to implement and require experienced 

observers to conduct (Bates 2004; Haroldson et al. 2003). Aerial surveys are difficult to arrange 

and generally require snow on the ground during a survey to aid in locating and seeing deer, 

especially if deer are visually sighted. Infrared imaging does not require visually spotting deer. 

However, skilled operators are required to effectively use the equipment and to differentiate 

between deer observations and those of other animals. Since HTLN parks are spread across the 
9

Midwest Region, numerous contracts with different agencies would have to be made in order to 

carry out such surveys. 

The accuracy of a mark and recapture survey is dependent upon the number of deer marked and 

the number of deer re-sighted. Kilpatrick et al. (1997) calculated that it takes a minimum of 4.4 

hours to capture and mark each deer. If just 10% of a herd as small as 100 individuals were 

marked, it would require at least 44 hours or one week to capture and mark deer. Herd sizes in 

HTLN parks are much larger than 100 individuals; thus the field hours to capture enough deer 

would be cost-prohibitive. The number of surveys required to obtain an adequate number of resighted individuals for an accurate estimate of the population could be cost-prohibitive as well. 

Fecal pellet counts along transect lines is a survey type that has been used for many years. These 

counts require many field hours to complete, however, and the cost associated with field hours 

required to complete a survey would be prohibitive. Another factor to consider with fecal pellet 

counts is that of logistics. A minimum of two multi-day trips would be required to each HTLN 

park unit to conduct a survey. The first trip is needed to clear areas of deer feces so an accurate 

time interval for pellet deposition can be determined. During the second trip, fecal pellet groups 

deposited since the first trip are counted. Fecal pellet counts are generally limiting with regards 

to the amount of area that can be covered because of the labor involved. 

Remote cameras have been used to census white-tailed deer (Jacobson et al. 1997). This method 

is cost prohibitive as well. Initial camera cost and the annual cost for film development and 

camera replacements would limit the scope of our deer monitoring to only the smallest HTLN 

parks. One camera per 20 ha (48 acres) was recommended for the National Capital Region 

Network (Bates 2004), for example. Using infrared cameras also requires a considerable amount 

of time be devoted to processing pictures, identifying each deer, and determining accurate 

estimates of the population. 

‘Rushing’ involves placing observers in hidden locations along a line on one end of a park. 

Another group starts on the opposite end of the park in an attempt to scare the deer so they run 

by the hidden observers who in turn count their numbers. This type of survey is not possible 

given the size of most HTLN park units. Also, it may not be the best way to acquire accurate 

numbers of the deer population as individuals can be counted multiple times by different 

observers. 

The distance method of sampling takes into account decreasing detection probabilities as 

distance from an observer increases. Densities of the target organism are calculated based on the 

shape of an empirically determined detection function (Buckland et al. 2001). This method 

cannot be employed because several main assumptions are violated (e.g., placement of transects 

is not random, locations of transects [roads] affect the distribution of deer, etc.). See the critical 

comments of Dr. Paul Lukacs, an expert on distance sampling, in Supplemental Document #1 

regarding this, and other sampling options. 
10

3.0 Field Methods 

3.1 Field Season Preparations, Field Schedule, and Equipment Setup 

Prior to the field season each year, usually beginning the previous November or December, all 

observers should review this entire protocol, including all standard operating procedures (SOPs). 

Observers should pay special attention to the tasks described in SOP #1 “Before the Field 

Season” and SOP #2 “Training Observers”. A review on estimating distance is particularly 

important each year to assure quality data is collected (see SOP #2). All of the equipment and 

supplies listed in SOP #1 should be organized and made ready for the field season; copies of the 

field data forms in Appendix A should be made. Twenty-five percent of all field data sheets 

should be copied to write-in-the-rain paper. 

Staff workloads and unpredictable weather (e.g., the onset of extremely cold weather, periods of 

rain or snow, extreme icy conditions) necessitate maintaining some flexibility in scheduling the 

sequence and duration of sampling trips. Sampling dates should be scheduled and logistics 

organized prior to the start of each field season, however. Alternative sampling dates should be 

identified as well. Three replicated deer surveys should be scheduled for completion each field 

day at a park. Visibility estimates should be scheduled for the first day at a park, after deer 

surveys are complete. One field day at a park should be scheduled weekly starting the first of 

January. An effort should be made to complete six field days at a park, three being the 

minimum. 

Influences of weather on deer activity and detectability need to be considered during counts. 

During periods of high wind, deer move from open to closed areas (Linsdale and Tomich 1953, 

Loveless 1964, Ozoga and Gysel 1972, Beier and McCullough 1990). Therefore, counts are 

restricted to periods without high winds (i.e., sustained winds >30 km/hr; 18.6 m/hr) to optimize 

seeing deer in open habitats with greater visibility. Although heavy rain does not influence deer 

activities (Zagata and Haugen 1974, Michael 1970, Beier and McCullough 1990), periods of 

heavy rain will influence visibility, and thus should be avoided. Likewise, snow fall greater than 

moderate will influence visibility, and thus should be avoided. Snow on the ground limits food 

availability, thus affecting patterns of deer movement as they seek out areas of higher food 

availability. Therefore, deer should not be surveyed during periods of significant snow 

accumulations as this will add unnecessary variability into count data across years. Weather 

criteria for conducting deer counts are outlined in SOP #1. 

3.2 Sampling Methods 

Permanent sampling routes, selected from existing all-weather roads within a park, are used to 

survey deer. Due to the nature and purpose of most parks, and for safety reasons, it is not 

recommended to drive off road to complete surveys. Once arriving at the park, park maps are 

used to familiarize each observer with the park, and determine the starting point, direction and 

sequence each section will be surveyed. A global positioning system (GPS) is used to mark the 

beginning and ending points along each survey route. 

Each day the project manager splits the observation team into a pair of deer observers, a data 
11

recorder, and a driver. The data recorder is responsible for ensuring all data fields listed on the 

data dictionary of the GPS unit are filled in and the location of each deer or deer group is 

recorded. The data recorder also fills out a paper copy of all data observations. Deer observers 

are responsible for locating deer and accurately taking distance measures from the survey vehicle 

to the deer or deer group. Observers are also responsible for recording the angle of the deer or 

deer group from the survey vehicle. Along with the obvious chore of driving, the driver is 

responsible for measuring all weather parameters and assisting with data recording if needed. 

For safety reasons the driver should not be involved with recording data if the survey vehicle is 

moving. 

Each member of the sampling team is responsible for keeping track of their equipment and/or 

data sheets. Before leaving the field each night, all equipment is accounted for and data sheets 

are checked for completeness and passed on to the project manager. The project manager is 

responsible for the safekeeping and organization of the data sheets and ensuring data entry. The 

data recorder is responsible for downloading all data from the GPS unit. At the end of each 

year’s sampling, a trip report including weather conditions, logistical problems, any subsequent 

departure from the protocol, etc. should be written by the project manager. 

3.3 Conducting the Spotlight Survey 

Spotlight surveys will establish a relative index of white-tailed deer population density at each 

HTLN park unit. Methods for conducting the spotlight survey are given in SOP #5 “Conducting 

the Spotlight Survey” and are summarized here. Surveys are conducted from a survey vehicle 

moving no more then 16 km/hr (10 mi/hr) using two 1,000,000 candlepower spotlights. All deer 

seen along the survey route are counted and their location recorded using GPS technologies. 

Deer counts are made by two observers, one seated on the left and one on the right side of the 

vehicle. Distances from the stopped survey vehicle to all deer are determined with a rangefinder 

or, for deer < 20 m from the vehicle, by visual estimates. Deer are usually observed in groups, in 

which case distance is taken or estimated to the center-most deer in the group. In order to map 

locations of deer, the direction and angle of all deer or deer groups from the survey vehicle are 

recorded as well. From pilot data, it was observed that the highest number of deer counted each 

night generally occurred within the first couple of hours following official sunset (See 

Supplemental Document #4). However, on occasion the maximum number of deer counted 

occurred in the second or third replicate. Therefore, three surveys commencing one hour after 

official sunset will be used to count deer numbers each night. Jester and Dillard (2001) and 

Shult and Armstrong (1983) recommend starting surveys one hour after official sunset to 

maximize deer observed. 

3.4 Establishing Visibility during Surveys 

Determining the area surveyed for white-tailed deer is critical for obtaining an accurate estimate 

of deer density in the survey area. SOP #6 “Establishing Visibility during Surveys” gives a 

detailed description of how the area visible during surveys is determined; a brief summary is 

presented here. Visibility estimates are taken on the first night after the surveys are completed 

by recording the perpendicular distances from the survey vehicle to a point beyond which deer 

would not be visible. Visibility is monitored every 0.16 km (1/10th mile) along the survey route. 
12

The location each perpendicular measure is taken is marked using GPS technologies. In an 

attempt to get a more robust picture of how much area is being surveyed along the route, the 

location of the survey vehicle should be adjusted slightly if objects are encountered that block 

the true area observed during a survey. For example, if the view of an open field is blocked by a 

single cedar tree in the ditch next to the survey vehicle, move the vehicle forward or backward to 

see the field. Using GIS technologies, perpendicular distances are plotted on a map, a polygon is 

created, and the survey area is determined. 

4.0 Data Management 

4.1 Overview of Database Design 

The design of the deer monitoring database is centered on GPS locations. Each GPS location is 

associated with deer observed during spotlight surveys. Unlike most monitoring databases, 

location is the primary field in the database. Furthermore, locations of observations are not 

predetermined. In the Natural Resource Data Template, these locations are called 

“Data_Locations” rather than simply “Locations” (National Park Service, 2006). There is a oneto-one relationship between data locations and field data, in contrast to planned locations which 

have a one-to-many relationship with field data. Data locations are typically required in 

monitoring databases for linear transect surveys, where exact locations of target features are not 

known. In addition to GPS location data, the deer monitoring database includes a field table for 

deer observations. As previously mentioned, it is this table that corresponds one-to-one with the 

GPS data. This attribute table includes number of deer, distance from viewer, vegetation type 

(upland forest, upland scrub, grass/prairie), date and time of observation, GPS related 

information (Max_PDOP, Correction Type, Receiver Type, and other technical information), 

DeerID (unique integer) and EventID. The EventID field links the field data many-to-one to the 

SamplingEvents table. The SamplingEvents table contains weather and physical conditions 

including: moon illumination and beginning and ending values for temperature, humidity, wind, 

wind direction, and precipitation. 

4.2 Metadata Procedures 

National Park Service natural resource databases are required to include FGDC standard 

metadata. Wide distribution of metadata enables potential users to identify exactly what 

monitoring data is available. It also provides instructions regarding how to contact data 

stewards. Creation of metadata has been greatly facilitated by ESRI ArcGIS utilities that 

automatically generate spatial metadata. The ArcGIS utilities do not provide similar automation 

for attributes. Currently, these have to be entered by hand. Certain Access metadata generators 

are being developed “in-house” by WASO I&M developers. These are currently in beta form 

and have not been widely distributed. Once metadata has been created, it should be saved in 

XML format. It can be converted to text or html at a later date using the FGDC “mp” utility. 

Metadata is archived in the geodatabase and by WASO I&M. Currently the WASO copy is 

submitted using the NR-GIS metadata clearinghouse. XML format is required for WASO 

metadata. Metadata is archived with WASO with the submission of the monitoring protocol. It 

should be updated with each protocol revision. 
13

4.3 Data Archival Procedures 

Data archive is the most important part of data management activity. Servers go down and don’t 

come back. The data manager needs to be able to restore data to alternate servers or 

workstations. In this sense, a reliable tape backup device is more critical than the server itself. 

For the deer database and other monitoring databases, we run complete backups (no incremental 

backups) each Monday, Wednesday, and Friday. Monday tapes are held for a month. Archive 

tapes are made quarterly and stored for 18 months. Back-up logs are reviewed on every job and 

file restores are run once per month just to be sure the system is working. 

Like other monitoring databases, the white-tailed deer monitoring database is also secured by file 

archives stored on the server. The database is maintained under a directory called DeerSurveys 

under the production drive called “L”. The database immediately below this directory is the 

production copy of the database. Under DeerSurveys is also a subdirectory called “dev” that is 

short for “development”. All backups and earlier versions are stored under this directory. 

5.0 Analysis and Reporting 

A critical component of any long-term monitoring protocol is a consistent and systematic way of 

analyzing and reporting on information (data) collected. The information must serve two 

purposes: (1) describe the current condition or status of a deer population and (2) detect changes 

in a population through time. The variable selected for data summary purposes is an index of 

relative population density. This annual index of relative population density provides 

information to park managers on trends in park deer populations and may provide feedback on 

the effects of implemented management efforts (e.g., population control or vegetation restoration 

efforts). As additional data are collected, trend analysis using time-series analysis or repeated 

measures will be explored as tools to detect temporal trends in deer density data. 

SOP #9 “Data Summary and Analysis” gives step-by-step details on how to: 1) determine annual 

deer population densities, 2) calculate annual density means and standard deviations and 3) 

determine percent annual change in deer densities. Deer population densities should be analyzed 

and compared against previous estimates every year surveys are completed. 

5.1 Recommendations for Routine Data Summaries and Analyses 

Population density, defined as the number of individuals/km2

 of sample area, provides an index 

with which annual change or long-term trends can be measured. To calculate this index, two 

pieces of information are needed: (1) the maximum number of individuals within the sample area 

and (2) the size of the area sampled. Daily maximum numbers of deer are obtained from count 

data collected each night during spotlight surveys. The size of the area sampled for deer is 

determined annually, during the first survey night, by measuring at 0.16 km (1/10th mile) 

intervals along the survey route the perpendicular distances from the survey vehicle to a point 

beyond which deer would not be visible. The point perpendicular distances are measured using 

GPS technologies. Using GIS technologies, perpendicular distances from the first survey nights 

are plotted on a map, a polygon is created, and the annual survey area determined (see SOP #9 

“Data Summary and Analysis”). Annual survey areas, by definition, include all deer 
14

observations. An estimate of the average annual population density and standard deviation is 

determined from replicate maximum deer counts for that year. The range in population densities 

each year is determined from replicate maximum values as well. The percent change in annual 

deer densities within the survey area should be calculated and reported annually. 

5.2 Recommendations for Long-term Trend Analyses 

An underlying purpose of the HTLN is to design and implement long-term ecological monitoring 

to evaluate the integrity of park ecosystems and contribute to the understanding of ecosystem 

processes. The approach towards long-term analysis of monitoring data is therefore critical to 

meet this goal. HTLN is currently planning and implementing several techniques to address 

long-term data analysis for monitoring projects. The simplest, yet, perhaps, most important 

method of long-term monitoring data analysis is simply graphing data through time with an 

estimate of variability. Trend is easily inferred from a graphical presentation. Furthermore, the 

likelihood that an observed trend is significant can be determined from the range of the standard 

deviation, and its overlap among sample periods. Graphs are easily interpretable, and, as such, 

serve as useful tools for interpreting monitoring results to managers. 

5.3 Recommendations for Reporting Results 

To facilitate timely dissemination of monitoring results, annual status reports should be 

completed by September 1st of the year data is collected. More extensive summary reports, 

including trend analysis, should be completed every five to ten years depending on the rate of 

change in the deer community and the need for summary information to guide resource 

management. Summary reports may be used in place of annual reports for that year. All reports 

must follow National Park Service Natural Resource Technical Report formatting style. Refer to 

SOP #10 “Reporting” for details on report structure and style.

Tables and figures (including pictures) in a report should be placed within the text or 

immediately following the literature cited section. Tables and figures should be numbered in 

sequence regardless of where they are located. Table captions are placed at the top of a table, 

while figure captions are placed below the figure. Horizontal lines are used to separate the table 

caption from column headings, column headings from the table, and to signify the end of the 

table. Vertical lines should not be used in tables. Tables and figures should contain information 

not presented in the body of the text, thereby minimizing redundancy. 

6.0 Personnel Requirements and Training 

6.1 Roles and Responsibilities 

The project manager is the lead ecologist for implementing this monitoring protocol, and is 

supervised by the Program Coordinator for HTLN. The data management aspect of the 

monitoring effort is the shared responsibility of the project manager, the GIS specialist, and the 

data manager. Typically, the project manager and GIS specialist are responsible for data 

collection. The project manager is responsible for data entry, data verification, and validation, as 

well as data summary, analysis, and reporting. The data manager is responsible for data 
15

archiving, data security, dissemination, and database design. The data manager, in collaboration 

with the project manager and GIS specialist, develops data entry forms and other database 

features as part of quality assurance, and automates report generation. The data manager is 

ultimately responsible that adequate QA/QC procedures are built into the database management 

system and appropriate data handling procedures are followed.

6.2 Qualifications and Training 

The most essential component for the collection of credible, high-quality data is competent 

observers. Good night vision is critical. Many deer are seen at a distance and only visible 

because of the reflection of light from the tapetum lucidum in their eyes. As well as being able 

to visually identify deer, observers should be tested frequently on their ability to estimate 

distances or measure them using a laser rangefinder. Time should also be invested in training 

personnel to estimate the distance from themselves to deer within different habitats. This will 

require training in the field (see SOP #2, “Training Observers”) to become proficient with the 

use of a laser rangefinder and to gain experience with estimating distances in different habitat 

types. The quality of the observer will determine the quality of the data. 

7.0 Operational Requirements 

7.1 Annual Workload and Field Schedule 

White-tailed deer surveys will begin no sooner than the first week of January and end no later 

then the second full week of March, a period that coincides with peak visibility through brush 

and trees. Inclement weather and personnel workloads will preclude the scheduling of sampling 

events to specific annual dates. Deer surveys may be scheduled for the third week of March if 

winter storms are unusually late. Monitoring efforts will require a four person crew. 

Approximately six field days for each park are required to complete deer sampling. One 

additional day of travel should be planned for each field day at Arkansas Post National 

Memorial. 

7.2 Facility and Equipment Needs 

The nature of deer survey work does not require special facilities beyond normal office space 

and equipment storage needs. Table 1.01 list the field equipment needs for one crew. If two or 

more crews work simultaneously, equipment requirements will increase accordingly. 

7.3 Startup Costs and Budget Considerations

Personnel expenses for field work are based on a crew of four people: an ecologist, a GIS 

specialist, and two subject to furlough biological science technicians. Six field days should be 

planned for both Wilson’s Creek National Battlefield, Missouri, and Pea Ridge National Military 

Park, Arkansas, and 12 field days for Arkansas Post National Memorial, Arkansas. Field costs 

will vary from year to year depending on the skill level and size of the crew. Data 

management/reporting expenses include staff time of biological science technicians, a GIS 

specialist, project manager, and data manager. Startup costs include the purchase of equipment 
16

and supplies listed in Table 1.01 as well as maintenance or replacement of equipment shared 

among multiple projects (e.g. GPS units, cameras, vehicles). 

Table 1. Startup and annual costs, for monitoring white-tailed deer populations in Heartland 

Network Inventory and Monitoring Program parks. 

Category 

Startup 

Cost 

Annual 

Cost 

Field work (salary) 7,150.00 14,750.00 

Travel 2,140.00 3,400.00 

Data management/reporting 11,490.00 11,490.00 

Startup equipment costs 9,860.00 -- 

Annual equipment/supplies -- 1,500.00 

Administrative support and overhead 7,660.00 5,570.00 

TOTAL 38,300.00 36,710.00 

7.4 Procedure for Revising the Protocol and Archiving Previous Versions 

Over time, revisions to both the protocol narrative and to specific SOPs are to be expected. 

Careful documentation of changes to the protocol, and a library of previous protocol versions are 

essential for maintaining consistency in data collection and for appropriate treatment of the data 

during data summary and analysis. The MS Access database for each monitoring component 

contains a field that identifies which version of the protocol was being used when the data was 

collected. The rationale for dividing a sampling protocol into a protocol narrative with 

supporting SOPs is based on the following: 

• The protocol narrative is a general overview of the protocol that gives the history and 

justification for doing the work and an overview of the sampling methods, but does not 

provide all of the methodological details. The protocol narrative will only be revised if major 

changes are made to the protocol. 

• The SOPs, in contrast, are very specific step-by-step instructions for performing a given task. 

They are expected to be revised more frequently than the protocol narrative. 

• When an SOP is revised, in most cases, it is not necessary to revise the protocol narrative to 

reflect the specific changes made to the SOP. 

• All versions of the protocol narrative and SOPs will be archived in a protocol library. 

The steps for changing the protocol (either the protocol narrative or the SOPs) are outlined in 

SOP #12, “Revising the Protocol”. Each SOP contains a revision history log that should be filled 

out each time an SOP is revised to explain why the change was made and to assign a new version 

number to the revised SOP. The new version of the SOP or protocol narrative should then be 

archived in the HTLN protocol library under the appropriate folder. 

8.0 References 

Bates, S. 2004. White-tailed deer density monitoring protocol version 1.0: distance and pellet 

group surveys. National Capital Region Network Inventory and Monitoring Program, 

Washington, D.C., USA. 
17

Beier P. and D.R. McCullough. 1990. Factors influencing white-tailed deer activity patterns and 

habitat use. Wildlife Monographs 109:1-51. 

Buckland, S.T., D.R. Anderson, K.P. Burnham, J.L. Laake, D.L. Borchers and L. Thomas. 2001. 

Introduction to distance sampling: estimating abundance of biological populations. Oxford 

University Press Inc. New York, NY, USA. 

Connelly, N. A., D. J. Decker and S. Wear. 1987. Public tolerance of deer in a suburban 

environment: implications for management and control. Eastern Wildlife Damage Control 

Conference 3:207-217. 

Crouch, G.L. and N. R. Paulson. 1968. Effects of protection from deer on survival and growth 

of Douglas-fir seedlings. USDA Forest Service, Pacific Northwest Forest Range Experiment 

Station Reserve, Research Note 94. 

Dennis, D. F. 1983. An analysis of Ohio’s forest resources. USDA Forest Service, Northeast 

Research Station, Research Bulletin NE-75. 

Gee, K.L., M.D. Porter, S. Demarais, F.C. Bryant and G. VanVreede. 1994. White-tailed deer: 

their foods and management in the cross timbers (second edition). The Samuel Roberts 

Noble Foundation, Inc. Ardmore, OK, USA. 

Haroldson, B.S., E.P. Wiggers, J. Beringer, L.P. Hansen and J.B. McAninch. 2003. Evaluation 

of aerial thermal imaging for detecting white-tailed deer in a deciduous forest environment. 

Wildlife Society Bulletin 31:1188-1197. 

Horsely, S.B. and D.A. Marquis. 1983. Interference by weeds and deer with Allegheny 

hardwood reproduction. Canadian Journal of Forest Research 13:61-69. 

Jacobson, H.A. J.C. Kroll, R.W. Browning, B.H. Koerth and M.H. Conway. 1997. Infraredtriggered cameras for censusing white-tailed deer. Wildlife Society Bulletin 25:547-556. 

Jester S. and J. Dillard. 2001. Conducting white-tailed deer spotlight surveys in the crosstimbers and prairie region of north and central Texas. 

http://www.tpwd.state.tx.us/publications/pwdpubs/media/pwd_rp_w7000_1126.pdf. 

Karr, J.R. and D.R. Dudley. 1981. Ecological perspective on water quality goals. 

Environmental Management 5:55-68. 

Kilpatrick, H.J., S.M. Spohr and A.J. DeNicola. 1997. Darting urban deer: techniques and 

technology. Wildlife Society Bulletin 25:542-546. 

Lindsdale, J.M. and P.Q. Tomich. 1953. A herd of mule deer. University of California Press, 

Berkeley, CA, USA. 
18

Loveless, C.M. 1964. Some relationships between wintering mule deer and the physical 

environment. Transactions of the North American Wildlife and Natural Resources 

Conference. 29:415-531. 

Marquis, D.A. 1981. Effect of deer browsing on timber production in Allegheny hardwood 

forests of northwestern Pennsylvania. USDA Forest Service Research Paper NE-475. 

McShea, W.J. and J.H. Rappole. 1997. The science and politics of managing deer within a 

protected area. Wildlife Society Bulletin 25:443-446. 

Michael, E.D. 1970. Activity pattern of white-tailed deer in south Texas. Texas Journal of 

Science 21:417-438. 

Michael, E.D. 1992. Impact of deer browsing on regeneration of balsam fir in Canaan Valley, 

West Virginia. Northeastern Journal of Applied Forestry 9:89-90. 

Mladenoff, D.J. and F. Stearns. 1993. Eastern hemlock regeneration and deer browsing in the 

Northern Great Lakes region: a re-examination and model simulation. Conservation Biology 

7:889-900. 

National Park Service. 2006. Natural Resource Database Template Version 3.1 documentation. 

Natural Resource Program Center, Office of Inventory, Monitoring, and Evaluation, Fort 

Collins, CO, USA. 

Ozoga, J.J. and L.W. Gysel. 1972. Response of white-tailed deer to winter weather. Journal of 

Wildlife Management 36:892-896. 

Peitz, D.G., M.G. Shelton and P.A. Tappe. 2001. Forage production after thinning a natural 

loblolly pine-hardwood stand to different basal areas. Wildlife Society Bulletin 29:687-705. 

Shafer-Nolan, A. L. 1997. The science and politics of deer overabundance at Cuyahoga Valley 

National Recreation Area, Ohio. Wildlife Society Bulletin 25:457-461. 

Shult, M.J. and B. Armstrong. 1983. Deer census techniques. 

http://www.tpwd.state.tx.us/publications/pwdpubs/media/pwd_bk_w700_0083.pdf 

Stoll, R. J., Jr. and R.W. Donohoe. 1973. White-tailed deer harvest management in Ohio. Ohio 

Department of Natural Resources, Division of Wildlife, In Service Document 73. 

Strole, T.A. and R.C. Anderson. 1992. White-tailed deer browsing: species preferences and 

implications for central Illinois forests. Natural Areas Journal 12:139-144. 

Zagata, M.D. and A.O. Haugen. 1974. Influence of light and weather on observability of Iowa 

deer. Journal of Wildlife Management 38:220-228. 
19

9.0 Supplemental Documents 

9.1 Supplemental Document 1: Options available for white-tailed deer monitoring 

To: Heartland Network Inventory and Monitoring Program 

From: Paul M. Lukacs 

Re: Options available for white-tailed deer monitoring 

Date: May 2, 2005

 Several options exist for ways to monitoring white-tailed deer abundance on National 

Park Service land within the Heartland Network. I will outline the pros and cons of four 

potential options for monitoring deer. I have listed the options we discussed during our April 26-

28 meeting below. 

1. Discontinue deer abundance monitoring and reallocate money elsewhere. 

2. Use remote cameras as a means of collecting point transect distance sampling data. 

3. Use mark-resight methods to estimate abundance. 

4. Continue with the current road-based distance sampling surveys with minor 

modifications. 

The first option is to discontinue the white-tailed deer surveys and use the money spent 

on these surveys elsewhere. The rationale for this option is based on the value of an estimate of 

deer abundance for the management of NPS lands given the small size of the properties in 

consideration. If we assume that the exact number of deer on a property is known at a point in 

time, how would we use that information for the management of deer? The management 

questions at hand include 1) how frequently do deer move off the park and onto neighboring 

private property and 2) is the deer population over-abundant and causing impacts on rare plants 

from feeding or trampling? Even if we knew the abundance of deer on a park exactly, that does 

not tell us how often deer are moving off the park nor what the deer do while they are off of the 

NPS property. It would require a telemetry study to obtain the information needed to answer that 

management question. On the same note, if we knew exactly how many deer were on a park; 

that would not provide information about how they are impacting rare plants. A study directly 

examining deer-plant interactions would be needed to answer that question. Therefore, it seems 

that monitoring deer abundance is not going to address the management issues at hand. This 

does not suggest that all studies of deer are not useful; I am merely suggesting that deer 

abundance is not the parameter that will help answer these questions. Based on this reasoning, I 

recommend discontinuing the deer abundance monitoring. 

The second option is to use remote digital cameras to obtain distance sampling data. For 

this option, digital cameras would be set out at random locations throughout a park. A timer 

would be set to take a picture at set intervals throughout dawn and dusk. Flagging would mark 

distance bands out from each camera. The pictures would be reviewed and deer detected and 

there distances would be recorded. The data would be analyzed in a distance sampling 

framework to estimate deer density and abundance. This is a statistically valid method for 

obtaining a park-wide estimate of abundance. Potential problems with this method are 1) the 

initial cost of purchasing cameras which may be high; 2) image resolution may not be high 

enough to effectively detect deer; and 3) it is not known what the encounter rate will be at each 
20

camera. Approximately 60-80 detections of deer would be needed to obtain a reliable estimate 

of detection probability. An additional advantage of using remote cameras is the cameras could 

be used for more than just the deer surveys, thus defraying the initial investment. 

The third option uses mark-resight techniques to estimate abundance of deer on each NPS 

property. This option requires that some deer be marked at each park. Deer would be captured 

by drop net and uniquely marked with a tag that could be read with binoculars or spotting scope. 

Marked deer are released. Surveys are conducted and the numbers of marked and unmarked deer 

are recorded along with the identification of marks if possible. The bulk of the surveys would be 

done from the tour road and a lesser effort would be done by walking through the unroaded 

portions of the park. 

The amount of effort required and expected precision of the abundance estimate varies by 

the proportion of the deer population marked and the number of resighting surveys conducted. I 

will develop some estimates of effort and precision based on past deer surveys. At WICR, the 

estimated deer abundance is 312 individuals (SE=142). I will base the exploration of effort on 

the estimate of 312 deer. During a single night of the deer surveys approximately 100 deer or 30 

percent of the population are seen each night. Therefore, I will define a resighting occasion as 

equal to the effort put into 3 trips around the tour road. I estimated the expected standard error 

from resighting effort ranging from 3-9 nights and number of marks in the population ranging 

from 30-90, representing marking between 10 and 30% of the population. The results of the 

exploration are given in Table 1. 

Table 1. Expected standard errors for estimated abundance from a mark-resight survey at 

WICR. 

 

Number Resighting Occasions 

marked 3 5 7 9 

30 52 38 32 28 

60 32 25 20 18 

90 24 18 15 14 

As expected, standard error decreases with increasing effort. Standard error decreases 

more rapidly as the number of individuals marked increases, but the cost of marking individuals 

is likely to be greater than the cost of adding more resighting occasions. It should be noted that a 

standard error of 52 with an estimate of abundance of 312 yields a coefficient of variation of 

17%. This is likely to be sufficiently precise to obtain a good estimate of trend in abundance 

after several years of data have been collected. 

Several potential problems exist for mark-resight surveys. First, if movement rates of 

deer are relatively high, it is possible that many of the marked deer could leave the park and be 

unavailable for sampling. If this is the case, some deer would need to be fit with radio-collars to 

estimate the rate at which deer are moving. Second, marking deer is invasive. It is possible for 

deer to be injured or killed during tagging. Moreover, tags will be visible to park visitors and 

employees. Finally, marking deer is an expensive endeavor. Thus, while mark-resight methods 

can produce good estimates of abundance, it is not without its limitations. 

It has been suggested to maintain the road-based distance sampling surveys during the 

resighting occasions. I do not recommend this for reasons beyond the inadequacy of road-based 

distance sampling. When searching for deer for a mark-resight survey, you want to maximize 
21

the number of deer detected regardless of their location. When surveying with distance sampling 

you want to be absolutely sure to see all deer along the transect prior to any movement. Thus, 

observers may be more likely to spend additional time search for deer away from the especially 

as they try to read tag numbers and therefore miss deer along the road or not see them until after 

they moved. Combining the mark-resight and distance sampling surveys would likely detract 

from both methods. 

The fourth option is to continue the current road-based distance sampling with slight 

modifications to improve detection prior to movement. This method has only one advantage, 

namely it is cheap. There are numerous problems with road-based distance sampling. First, 

using roads as the sampling frame limits inference to the roads, so any inference to the entire 

park is by strong assumption only. Second, roads follow patterns in the geography of the park. 

This induces a correlation between the distribution of the transect and the distribution of the deer. 

This can cause the detection function to be invalid. When transects are not randomly placed, one 

must assume the deer are uniformly distributed with respect to the transect. We know this 

assumption will be false. Third, deer are rarely exactly on the road, therefore too few detections 

occur at zero distance. This makes fitting a detection function particularly difficult. We saw 

these problems expressed in the overview of the HTLN deer data at WICR and PERI. For these 

reasons, I simply cannot recommend continuing road-based distance sampling. While the roadbased distance sampling is cheap, it is not useful. 
22

9.2 Supplemental Document 2: Notes from the white-tailed deer breakout session, 

3 August 2005, Hopewell Culture HNP 

Notes from white-tailed deer breakout session 

3 August 2005 

Hopewell Culture NHP

Attendees: David Peitz (WICR), Gary Sullivan (WICR), Kevin Eads (PERI), Lisa Petit 

(CUVA), Kevin Skerl (CUVA), Jesse Bolli (HOME), Tim Breen (OZAR), Lloyd Morrison 

(WICR). 

At HTLN parks where white-tailed deer have been designated as vital signs, the following 

issues associated with white-tailed deer were identified as important to park managers: 

(1) General herd health and appearance. 

(2) Collisions with vehicles on roads within and adjacent to park boundaries. 

(3) Impacts on neighboring private lands (e.g., browsing in gardens, etc.), particularly as 

development increases in areas near parks. 

(4) Impacts on park resources. 

 Discussion of these issues yielded the following insights: 

(1) Lisa Petit, who is actively involved with deer management attempts at CUVA, stated that 

maintenance of herd health is not a sufficient reason for lethal removal of deer. 

Exceptions would be if deer exhibit signs of chronic wasting disease, high tick loads that 

could represent an increased threat of tick-borne diseases to humans, etc. 

(2) Similarly, activities of deer on adjacent lands outside the parks are not sufficient reasons 

for managing deer populations within the parks. 

(3) In general, there was low interest in obtaining data on movement of deer across park 

boundaries, or studying effects of deer outside the parks. Some limited radio-collar data 

has indicated that the majority of deer observed did not leave the park. 

(4) No park manager was concerned about the current impact of deer on specific park 

resources. 

(5) All park managers, however, were concerned that deer may have substantial impacts on 

park resources in the future, especially if they become more abundant, and that data on 

population trends over time would be very useful. Lisa Petit and Kevin Skerl suggested 

that the deer abundance issue at western parks in the network is analogous to the 

situation at CUVA (where deer are now a major problem) 25 years ago. 

The possibility of dropping deer as a vital sign was raised, but there was little support for 

this. Most were of the opinion that vital signs should not be changed at this point. 

There was a discussion of the different methods of estimating deer abundance, the problems 

associated with the distance method, and what methods other state and federal agencies were 

using. It was explained that a variety of methods may be used to estimate deer abundance, and 

some are more accurate than others; the more accurate methods require greater expenditures of 
23

time and effort. There was a discussion of what sort of burden of proof would be required in 

different types of circumstances, and an explanation of how the I&M program was attempting to 

“raise the bar” on the caliber of scientific work done in the parks. Lisa Petit and Kevin Skerl 

noted that if data are ever to be presented in a court of law, these data should be derived from 

widely used and accepted methods. It was pointed out that some methodologies currently in use 

are much more accurate than others. 

The issue of how much our network could afford to invest in deer monitoring was raised, but 

no one present could definitively answer this question. The consensus of the managers was 

basically that we should give them the best data we could with the resources available. 

There was a discussion of how to monitor impacts, and it was decided that conducting 

exclosure experiments was the best way to do this, although no one desired such information 

immediately. It was disclosed that ARPO and PERI have existing deer exclosures, and such 

exclosures also exist at the Springfield Nature Center, near WICR. It was pointed out that our 

network may not be able to increase the time and money spent on deer monitoring to conduct 

such experiments in the future. The managers seemed to think they could obtain resources from 

other sources or attract outside cooperators to conduct enclosure experiments, if necessary, 

although they deemed it very important to have background data on deer abundance trends to 

document any increases in the deer population. 

 The most important conclusions from this session were: 

(1) Park managers are not so much concerned with absolute deer abundance in the parks as 

they are with changes in the relative abundance over time. 

(2) Park managers, although concerned with the impacts of deer outside the park, felt such 

impacts were not the park’s problem nor were such impacts sufficient for management 

of deer populations by lethal removal within the park. 

(3) Park managers are more concerned about future potential impacts of white-tailed deer 

on park resources then any current impacts. 

The following recommendations follow from this discussion: 

(1) Continue monitoring white-tailed deer with similar methods as were employed last 

winter/spring (i.e., visual spotlighting surveys from the road at night). Do not use the distance 

method to estimate abundance or density. Rather, use simple counts of deer seen from the road 

as an index of deer abundance. 

 The perpendicular distance to individuals or herds can be recorded with GPS in order to 

map the location of deer. The map data will also be useful for defining the observable area. 

Further definition of the observable area can be accomplished with GIS using aerial 

photography, digital elevation maps, etc. By quantifying the area over which deer may generally 

be seen from the road, this will provide an index of density. 

 These measures would not be thought of as estimates of the actual deer abundance or 

density per se (as would be the case if one were using the distance method), but simple indices of 

these variables. These indices, however, would vary in direct proportion to the variables of 

interest, and would indicate whether deer populations were changing, and the general magnitude 
24

of the change. This would represent the minimum information deemed necessary by park 

managers for which deer were designated as vital signs. 

(2) Infrequently (every 3-5 years, depending upon budget or other considerations), markrecapture or other methods could be employed to obtain more accurate estimates of deer 

abundance or density. This double sampling approach would allow us to determine correlations 

between the annual index of deer populations with the more accurate abundance data determined 

from other methods. Ultimately, it should be possible to estimate deer abundances with 

relatively good accuracy in years when only index data from visual surveys are available. 
25

9.3 Supplemental Document 3: Recommendations for conducting white-tailed 

deer surveys 

Recommendations for conducting white-tailed deer surveys 

by Dr. Lloyd Morrison, HTLN Quantitative Ecologist 

The suggested approach to white-tailed deer monitoring, resulting from a discussion with 

resource managers of the appropriate parks at the 2005 annual meeting, was to count deer visible 

from park roads in drive-through surveys. 1 This will yield an index of the relative abundance of 

deer, which should be correlated to some unknown degree with the absolute abundance, but will 

allow detection of general increases or decreases in the actual population over time. Because the 

number of deer observed in such surveys is strongly dependent upon their activity, and deer 

activity is influenced by many factors, it is critical to conduct the surveys in such a way as to 

minimize as much of this variability as possible. The greater the variability inherent in the data 

set, the less likely we will be to detect any real trends in population density, particularly using 

this index of relative abundance. 

In pilot work at WICR, three surveys were conducted back-to-back in a ~3 hour period 

(~1 hr per survey), and this was repeated on three consecutive days (or nights), for a total of 9 

surveys. (Surveys could be conducted during the day or at night; it doesn’t matter which, but 

whatever is decided should be used for all parks, and throughout the monitoring program.) The 

problem with conducting multiple, back-to-back surveys within several hours of each other is 

that one is likely to see the same deer, in the same place, doing the same thing in two or more 

surveys. Thus, back-to-back surveys do not represent true replicates, but rather 

pseudoreplicates, because they are not independent. 

Thus, in the example of three back-to-back surveys per day, on three different days, only 

three of the nine surveys would be independent (one from each day). For any data analyses 

requiring independent observations, the sample size would have to be 3 rather than 9. It would 

be problematic to use all 9 surveys even for descriptive statistics such as calculating mean and 

variance. The variance would likely be underestimated if all 9 were used, because the counts 

taken on the same day are likely to be more similar than counts taken on different days. 

My recommendation is to conduct only one survey in a 24-hour period. One could then 

make the reasonable assumption that the counts are independent. The total number of replicate 

counts that should be done for each park in each year will depend upon funding and logistics. 

Three counts should be regarded as minimum, but the more counts that are made, the greater the 

reduction in sample variance, and the more powerful our surveys will be to detect any trends. 

To minimize variability due to deer activity or behavior in relation to environmental 

variables, surveys should always be done during the same time of day (or night). An acceptable 

range of climatic conditions should be defined, and surveys should not be conducted outside 

these conditions. For example, a range of acceptable temperatures should be decided upon, and 

surveys should not be conducted in unusually warm or cold weather. Likewise, surveys should 

not be conducted during ‘inclement’ weather, such as rain, snow, high winds, etc. If surveys are 

to be conducted at night, they should be standardized by the phase of the moon (e.g., always 

conducted during the full moon). If surveys are to be conducted during moonlit nights, cloud 

 

1 Notes from white-tailed deer breakout session, 3 August 2005, Hopewell Culture NHP 
26

cover would also have to be taken into effect. When any environmental variables exceed the 

acceptable ranges or thresholds previously decided upon, the survey for that particular day (or 

night) should be aborted, and rescheduled for the following day (or night). 

To minimize inter-observer bias, the same observers should be used for the surveys on 

each occasion, in each park, in each year, and in succeeding years to the extent possible, given 

the unavoidable turnover in NPS personnel over time. If distances from the road to the deer are 

to be determined with rangefinders for the purpose of constructing maps, observers should be 

properly trained in the use of the rangefinders prior to conducting the actual surveys. This could 

be done by setting up targets at known distances and training observers until their accuracy is 

within a reasonable, predetermined interval. 
27

9.4 Supplemental Document 4: 2005 White-tailed deer counts by time after official 

sunset 

2005 White-tailed deer counts by time after official sunset.

Park 1-hr 2-hr 3-hr 

Arkansas Post National Memorial 

 Day 1 22 19 31 

 Day 2 28 25 30 

 Day 3 24 26 28 

 

Pea Ridge National Military Park 

 Day 1 35 22 21 

 Day 2 46 41 29 

 Day 3 64 50 52 

 

Wilson’s Creek National Battlefield 

 Day 1 55 33 32 

 Day 2 32 34 N/A 

 Day 3 43 24 15 
28

10.0 Standard Operating Procedures 

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.1 Standard Operating Procedure 1: Before the Field Season 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. Version 

# 

Revision 

Date 

Author Changes Made Reason for 

Change 

New Version 

# 

 

This Standard Operating Procedure (SOP) gives step-by-step instructions on how to prepare for 

white-tailed deer monitoring on National Park Service lands within the Heartland Network 

Inventory and Monitoring Program. Prior to each field season, usually beginning in November 

or December of the preceding year, all field crew personnel should review this entire protocol, 

including SOPs. 

I. General Preparation and Review 

Procedures: 

1. Refreshing deer identification skills is particularly important, as is reviewing all standard 

surveying procedures. Deer identification skills are best honed at night with the aid of a 

spotlight. Locating an object such as a deer eye at night with a spotlight can be difficult, with 

proficiency gained through practice and experience. State game and fish laws, however, 

prohibit spotlighting deer without approval from law enforcement officials with jurisdiction 

over the area. Get approval from law enforcement before practicing any spotlighting of deer. 

2. The use of a rangefinder to measure distances to deer can be particularly difficult at night and 

should be practiced before the start of the field season. Observer skills with the rangefinder 

should be checked periodically during surveys with reflectors set at predetermined distances 

from the survey vehicle. 

3. Observers should also practice estimating distances to objects, especially those less than 20 

m, a distance too close for most rangefinders to take a reading. 

4. Maps of the survey routes in each park should be printed and each crew member should 

become familiar with the routes and habitat types to be encountered prior to entering the 

field. 
29

5. A field notebook for the survey year should be prepared with pages for entry of sampling 

schedules, observer names, field hours, and unique happenings that may influence how data 

is reported. Information included in trip reports is based on what is recorded in field 

notebooks, so it is imperative that they are clearly organized for ease of field note entry. 

II. Scheduling Field Work 

Procedures: 

1. White-tailed deer surveys should begin no sooner than the first week of January and extend 

no later than the second full week of March, unless inclement weather delays surveys and 

field conditions allow for a later sampling date. Inclement weather and personnel workloads 

will preclude the scheduling of sampling events to specific annual dates. Sampling dates 

should be scheduled and logistics arranged prior to the start of the field season. 

2. Surveys should be scheduled for nights with wind speeds less than 30 km/hr (18.6 m/hr), rain 

less than heavy (visibility and hearing impaired), snow fall less than moderate (visibility 

impaired), and visibility greater than 3.2 km (two miles) (Bates 2004). Visibility can be 

obtained at: http://www.wunderground.com/. 

3. Monitoring efforts at Arkansas Post National Monument, Arkansas (ARPO), Pea Ridge 

National Military Park, Arkansas (PERI) and Wilson’s Creek National Battlefield, Missouri 

(WICR) require at minimum three field days at each to complete. However, six field days at 

each park should be scheduled. One field day at each park should be scheduled each week 

during the sampling window, January – March. 

4. Three deer surveys, the first starting one hour after official sunset and the remaining two each 

consecutive hour thereafter, should be scheduled each night. 

5. Visibility estimates should be taken on the first survey day as soon as the last deer survey has 

been completed. 

III. Organizing Supplies and Equipment 

Procedures: 

1. An equipment list should be compiled and equipment organized and made ready several 

weeks in advance of the field season. This allows time to make needed repairs and order 

equipment. The following is a list of field equipment needed for one survey crew. 
30

Table 1.01. Field equipment list for conducting white-tailed deer surveys on National Park 

Service lands within the Heartland Network Inventory and Monitoring Program. 

Number 

Required 

Description 

4 1,000,000 candlelight spotlight (two are held in reserve as spares) 

1 Clipboard 

2 Yardage Pro 1000 Rangefinder 

3 Pencil 

1 Jeep 

1 Kestrel 4000 pocket weather tracker 

2 Land measure compass mounted on poster board 

1 Global Positioning System with data entry forms loaded into the data dictionary 

1 Pin flag for determining wind direction 

1 Spotlight splitter cable 

1 Compass 

6 Illuminated reflectors on 36 in. rods 

1 First Aid Kit 

2. Copies of field data sheets should be made prior to entering the field. Approximately 25 % of 

all field data forms should be made on write-in-the-rain paper. See Appendix A for data 

entry forms. 

IV. References 

Bates, S. 2004. White-tailed deer density monitoring protocol version 1.0: distance and pellet 

group surveys. National Capital Region Network Inventory and Monitoring Program, 

Washington, D.C., USA. 
31

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.2 Standard Operating Procedure 2: Training Observers 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. Version 

# 

Revision 

Date 

Author Changes Made Reason for 

Change 

New Version 

# 

 

This Standard Operating Procedure (SOP) gives step-by-step instructions on how to train 

observers for white-tailed deer monitoring on National Park Service lands within the Heartland 

Network Inventory and Monitoring Program. All observers must learn to (1) identify deer in the 

field at night; (2) estimate or measure (using a rangefinder) distances to deer at night; and (3) 

estimate visibility during surveys. Special skills required to operate and record data using a 

Global Positioning System (GPS) are covered in SOP #3 “Using the Global Positioning System“, 

SOP #5 “Conducting the Spotlight Survey” and SOP #6 “Establishing Visibility during Surveys” 

and should be practiced before entering the field. 

I. Conducting the Spotlight Survey 

The most essential component for the collection of credible, high-quality deer data is welltrained and experienced observers. This cannot be overemphasized. Proficient observers will 

identify and count all but the most difficult to see deer within a survey area.

Procedures: 

1. Beginning several months prior to the field season, practice deer identification skills, 

especially at night using a 1,000,000 candle power spotlight. 

2. In the absence of actual deer, blue-green reflectors placed in various habitat types can be 

used to hone identification skills. Observers should be able to locate and ID more than 90% 

of deer or reflectors spotted by the observer group as a whole. All but the most difficult to 

observe deer or reflectors should be spotted. 

3. Working as a group of two or more observers, determine the number of deer in a defined area 

of observation and the number of deer each observer saw. All observers should practice 

together until all observers report seeing more than 90 % of the group’s total deer count. 

4. A working knowledge of the reflective characteristics of all animal eyes likely to be 

encountered during a survey should be gained prior to the start of surveys to avoid 

misidentifying other animals as deer. 
32

5. Regardless of skill level, observers should spend time in the field identifying deer at night 

prior to starting a survey. Deer identification skills should be practiced during different light 

conditions (i.e., full moon, new moon, cloud cover, etc.) and weather if possible. 

II. Measuring Distance with a Rangefinder 

A necessary element for accurately mapping the location of deer is skill in measuring the 

distance from the survey vehicle to each deer or deer group. The distance and angle from the 

observation point recorded in the GPS (i.e., the vehicle) to the deer is used to map deer locations. 

Procedures: 

1. Beginning several months prior to the field-season, practice measuring distances to various 

objects with a rangefinder, especially at night with illumination from a 1,000,000 candle 

power spotlight. Proper positioning of the spotlight when obtaining measures with a 

rangefinder is critical. 

2. Reflectors placed at known distances in various habitats to be encountered during surveys 

aids in training observers to distinguish if they have gotten an accurate measurement or not. 

Erroneous measures can occur at night if the laser from the rangefinder hits an unnoticed 

object between the observer and a deer or deer group. Therefore a general ability to estimate 

distances serves as a check for actual measured distances. 

3. Maps of the parks to be surveyed need to be reviewed for observers to familiarize themselves 

with each park and give them a general idea of distances to land features found along the 

survey route. 

III. Establishing Visibility during Surveys 

Determining the area surveyed for white-tailed deer is critical for obtaining an accurate estimate 

of deer density in the survey area. Therefore, each observer spotlighting deer must be equally 

skilled in determining the distance at which they can no longer effectively spot a deer. 

Procedures: 

1. While practicing both spotlighting and distance measuring skills, each observer should also 

spend time taking distance measures out to a point were visibility with a spotlight has 

diminished to a level were deer can no longer be effectively spotted. This distance varies 

with habitat type. Visibility distances are generally much closer in wooded areas than open 

fields. 

2. The maximum distance measured in open areas should be no greater than 250 m. Therefore, 

observers should practice taking measurements at distances less than 250 m. 
33

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.3 Standard Operating Procedure 3: Using the Global Positioning System 

Please see: http://www1.nature.nps.gov/im/units/htln/datamanagement.cfm. 
34

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.4 Standard Operating Procedure 4: Establishing Survey Routes 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. Version 

# 

Revision 

Date 

Author Changes Made Reason for 

Change 

New 

Version # 

 

This Standard Operating Procedure (SOP) gives step-by-step instructions on how to 

establish survey routes for white-tailed deer monitoring on National Park Service lands 

within the Heartland Network Inventory and Monitoring Program. Survey routes have 

already been established at Wilson’s Creek National Battlefield, Missouri, Pea Ridge 

National Military Park, Arkansas, and Arkansas Post National Memorial, Arkansas (see 

section 2.2, spatial design), and will not change over time. Thus this SOP is primarily 

relevant to other parks at which deer monitoring may be initiated. 

I. Selecting Survey Routes 

It is desirable for survey routes to pass through as many habitat types within a park as 

exist to obtain a relatively accurate estimate of deer numbers in the park. If possible, the 

amount of each habitat surveyed should be in proportion to their presence within a park. 

It is also important to select survey routes from existing all-weather roads for safety 

reasons and so that inclement weather will not prevent sampling for extended periods of 

time. It will be the program leader’s responsibility to select and plan survey routes. 

Procedure: 

1. Using the latest imagery of a park, select all hard service roads for consideration as 

potential survey routes. 

2. If possible, select survey routes that traverse a park in one continuous survey. Try to 

minimize the need to backtrack over areas already surveyed. While segmented 

survey routes will work, they are not as efficient as continuous survey routes for 

sampling deer and extra care needs to be taken during surveys to ensure an accurate 

measure of the survey route length is obtained. 

3. Because of the small size of most parks to be monitored, every all-weather road 

should be included in the survey as long as no area is sampled multiple times during 

the same survey. The area covered from the survey route should represent at least 10 
35

% of the total area of a park if possible. In many cases more than 10 % of a park is 

covered. (In a park such as Pea Ridge National Military Park, however, this is not the 

case; approximately 6.5 % of the main unit of the park is covered annually.) 

4. Select survey routes that can be closed to the public during spotlight surveys. Usually 

this will not be an issue as park operational hours keep visitors out of the park during 

the nighttime survey period. 

5. Once survey routes have been determined, maps need to be made and taken to the 

field to guide crews surveying deer. Survey routes should be overlaid on the most 

current imagery of a park to aid surveyors in familiarizing themselves with a park and 

in identifying areas more likely to hold deer. 

 
36

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.5 Standard Operating Procedure 5: Conducting the Spotlight Survey 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. Version 

# 

Revision 

Date 

Author Changes Made Reason for 

Change 

New 

Version # 

 

This Standard Operating Procedure (SOP) gives step-by-step instructions on how to 

conduct white-tailed deer surveys on National Park Service lands within the Heartland 

Network Inventory and Monitoring Program (HTLN). The procedures for: 1) collecting 

data, 2) logging data on a Global Positioning System unit, and 3) filling out paper data 

forms are covered in this SOP. 

I. Conducting the Spotlight Survey 

Spotlight deer counts are used to establish an index of white-tailed deer population 

density for the area surveyed on each HTLN park unit. From pilot data, it was observed 

that the highest number of deer counted each night at Wilson’s Creek National Battlefield 

and Pea Ridge National Military Park generally occurred in the first hour following 

official sunset (See Supplemental Document #4). At Arkansas Post National Memorial, 

however, the maximum number of deer counted occurred in the third replicate. 

Therefore, three surveys commencing one hour after official sunset will be used to count 

deer numbers each night. Jester and Dillard (2001) and Shult and Armstrong (1983) 

recommend starting surveys one hour after official sunset to maximize deer observed. 

One deer survey should be conducted each week for six consecutive weeks on each 

HTLN park unit if possible. A four person crew is needed to survey deer: a driver, a 

person to record and log data, and two people to spot deer and measure angles and 

distances. 

Procedures: 

1. Prior to the start of a survey, determine the route to be surveyed and start time (see 

SOP #4 “Establishing Survey Routes” for details on establishing a survey route). 

Surveys should start one hour after official sunset. 
37

2. Surveys are conducted from a survey vehicle moving no more then 16 km/hr (10 

m/hr) using two 1,000,000 candlepower spotlights. One observer with a spotlight 

needs to be positioned on each side of the survey vehicle and count deer on their 

respective side of the vehicle. Stop the survey vehicle as soon as a deer or deer group 

is spotted. The vehicle should remain stopped until all data is logged and a count of 

the number of deer at that location is made. Deer are counted with the vehicle 

stopped so that deer in close proximity to the group being counted are not included in 

that group but in their own group count. Use visual cues such as deer repeatedly 

looking at each other or by nearest neighbor criterion to partition deer into their 

respective groups. If a deer is less than half the distance from the closest deer or deer 

group than it is from the next closest deer or deer group, then it should be grouped 

with the first deer or deer group. 

3. All deer seen along the survey route are counted and their location recorded using 

GPS technologies. Distances from the stopped survey vehicle to all deer or deer 

groups are determined with a rangefinder or, for deer < 20 m from the vehicle, by 

visual estimates. Deer are usually observed in groups, in which case distance is taken 

or estimated to the center-most deer in the group. 

4. In order to map locations of deer, the direction (i.e., left front, left back, right front, 

right back) and angle (measured with a land measure compass) of all deer or deer 

groups from the survey vehicle are recorded. 

5. Navigate the survey route slowly trying to maintain a constant speed during the 

survey. Adjust speed of the survey vehicle only slightly as the terrain dictates. Slow 

down if observers are unable to effectively sample their assigned survey area. 

6. If during a count, high wind or heavy rains occur, cease the count and wait until the 

weather improves or else cancel sampling for that day and try again on a later date. 

These conditions inhibit deer activity and impair one’s ability to detect deer. Counts 

should not be conducted if sustained wind speeds increase to greater than 30 km/hr 

(18.6 m/hr), if it is raining hard (visibility and hearing is impaired) or snowing. 

II. Entering data on a Global Positioning System (GPS) unit 

Procedures: 

1. Prior to the first day in the field, load the DeerSurveyVer3.ddf data dictionary onto 

the GPS unit. Steps on how to download data onto the GPS unit can be found in SOP 

#3 “Using the Global Positioning System”. 

2. One half hour before the count begins, install the GPS unit inside the jeep. Do this by 

first assembling the magnetic mount, poles, and Hurricane antenna together and then 

place it in the center of the jeep. Next attach the cable that runs from the Hurricane 

antenna to the GPS unit (Trimble GeoXT). Make sure the GPS unit is on before 

plugging the cable in. 
38

Figure 5.01. Diagram of antenna assembly. 

 

3. On the GPS unit open the program TerraSync. Check the GPS unit settings, such as 

coordinate system, antenna options, and Max. PDOP which should be set to 6 (see 

SOP #3 pages 20 – 25 on how to do this). 

4. Once TerraSync is setup, create a new file by opening the data window and selecting 

new. In the field choices select the following: 

File Type: Rover 

Location: Default 

Dictionary Name: DeerSurveyVer3 

File Name: The file name must match the file name recorded on the paper data form 

and include the Park Code (4 digits), year (4 digits), “deer” to identify the project and 

the survey number (#) 1, 2 or 3 (ex. wicr2007deer1). 

After the fields are filled out click Create. 

5. A new window is now open. Click on the Options drop down menu and select Log 

Later. Now highlight the Deer Location choice and click Create. This opens the 

DeerSurveyVer3 data dictionary. Notice that the pause icon is flashing at the top of 

the screen; this means it is not collecting feature positions. When it is time to collect 

a deer location click the Log button. Notice that the pause icon turns into a pencil 

with a number to the right of it. The number indicates the amount of feature positions 

being collected for each deer location. Fifty (50) feature positions should be captured 

for each deer location. The data dictionary fields get filled out with the same 

attributes as the field sheet. The fields in the data dictionary are either pull down 

menus (▼) or numeric fields. When you click in a menu field a list will open. 

Choose the correct term from this list. To populate the numeric fields click the 

keyboard icon at the bottom of the screen, this will open a numeric keyboard. After 

all fields are filled out and at least 50 feature positions collected click OK. Repeat 

procedure 5 until all deer observations for the count are completed. 
39

Figure 5.02. Screen capture of the deer survey data dictionary. 

6. After the survey is complete click Close and then Yes to the question: Close this file. 

Are you sure? If no more surveys are to be done in the same evening close TerraSync 

and turn off the GPS unit. 

7. Once all counts are completed for a park see SOP #3 for transferring, correcting and 

exporting data, SOP #7 “Geospatial Data Management”, and SOP #8 “Data 

Management” on managing the data. 

III. Filling out the Paper Data Form 

When observers are conducting a deer survey they should fill out a copy of the field data 

form “Spotlight Survey Form” (an example is located at the end of this SOP) as a check 

for data logged on the GPS unit. The paper data form also serves as the only record for 

general survey information (recorded at the top of the data form), as this is not logged 

with the GPS unit. The paper form is filled out simultaneously with the logging of deer 

location data, so additional field time is not required to accomplish this task. 

Procedures: 

1. Fill out the general information prior to starting the survey. 

2. While recording the start time, record the starting weather conditions, cloud cover, 

and moon illumination. 

3. Once a survey has begun, record all deer seen and the angle and distance to each 

individual deer or deer group. 

4. At the end of each survey record the ending time, weather conditions, and cloud 

cover. 

5. The following is a complete list with descriptors for each variable that needs to be 

filled out: 
40

GPS File Name (aaaaYYYYdeer#): Write in the Park Code (4 digits), year (4 

digits), “deer” to identify the project, and Count # (1, 2 or 3). The GPS File Name 

recorded on a data sheet must correspond to its associated file name on the GPS unit. 

Date (mm/dd/yyyy): Write in the month (2 digits), day (2 digits), and year (4 digits) 

in the format shown for the day a count is being conducted. Include the forward 

slash. Example 07/19/2003 

Park: Write the appropriate Park Code (ARPO, PERI or WICR). 

Route: Write a short descriptor identifying the survey route for which a count is 

being taken within a park (i.e., Tour Road). 

Observer Initials: Fill in the three initials of each person conducting the count using 

capital letters. If someone does not have a middle name, put an underscore for their 

middle initial. Examples would be DGP for David G. Peitz or JTC for J. Tyler 

Cribbs. In the database, these initials will correspond to the full name and contact 

information for that person (the 3-character initials in the database must be unique, 

and if two people have the same initials, one should be given an honorary middle 

name). 

Starting time (hhmm): Write in the time to the nearest minute when the deer count 

begins, using the hour and minute format shown. Use military time (add 12 to the 

hour beginning with 1 pm through 11 pm). Fill in all four digits. Examples are 1630 

(4:30 pm) and 1900 (7:00 pm). 

End time (hhmm): Write in the time to the nearest minute when the deer count 

ends, using the hour and minute format shown. Use military time. 

Beginning and Ending: 

Temperature (oC): Record the ambient temperature during the start and end of a 

count in degrees Celsius, to one decimal place or rounded off to the nearest 

degree. Use a Kestrel 4000 pocket weather tracker to record ambient 

temperatures. 

Humidity (%): Record the percent (%) relative humidity during the start and end 

of a count using a Kestrel 4000 pocket weather tracker. 

Wind Speed (m/s): Record the wind speed in meters/second during the start and 

end of a count using a Kestrel 4000 pocket weather tracker. 

 

Wind Direction (o

): Using a pin flag and compass, determine the direction in 

degrees (0-359o

) the wind is moving, and record this direction. The direction the 

wind is moving is recorded at the start and end of each count. 
41

Precipitation: Record the Rain Code (0 - 5) from the following Table 5.01 as it 

applies to precipitation observed during the start and end of a count. 

Table 5.01. Codes used to record precipitation type during deer surveys. 

Rain Code Explanation 

0 no rain 

1 mist or light fog 

2 light drizzle 

3 light rain 

4 heavy rain; difficult to hear, visibility impaired (discontinue survey) 

5 snow or heavy fog (discontinue survey) 

Moon Illumination: Determine percent moon illumination at the time a survey will 

begin. Percent moon illumination can be found at: 

http://imagiware.com/astro/moon.cgi. 

Starting and Ending Cloud Cover (0 - 7): Estimate the percent cover of clouds 

during the start and end of the deer survey. Cover is estimated within modified 

Daubenmire cover classes (Table 5.02). If there are patches of clouds in different 

areas of the sky, try to imagine gathering them together in one part of the sky and 

recording what cover class that would represent. 

Table 5.02. Cloud cover estimates within modified Daubenmire cover classes. 

Cover class Explanation 

0 None present 

1 0 – 1 % cloud coverage 

2 1 – 5 % cloud coverage 

3 5 – 25 % cloud coverage 

4 25 – 50 % cloud coverage 

5 50 – 75 % cloud coverage 

6 75 – 95 % cloud coverage 

7 95 – 100 % cloud coverage 

 

Group # Assigned: Record sequentially, a unique number identifying each deer or 

deer group observed during a count. Generally, numbering begins with one (1) and 

increases as needed for each deer or deer group observed. 

Side of Vehicle: Using a side of vehicle code, record on which side of the road each 

deer or deer group is observed (i.e., “L” for left, “R” for right, “OR” for on road). 

Distance (m): Using a rangefinder, measure and record the distance from the 

observer to the deer or deer group. If a group of deer are spotted, take one distance 

measure to the center-most individual in the group. 
42

Angle (o): Using a land measure compass, record the angle of each deer or deer 

group from the survey vehicle. Angles are measured from 0 to 90o

 in each quadrant 

of the vehicle. Deer located on the transect line will have an angle of 0o and should 

be placed in the quadrant they moved from if known or can be reasonably assumed. 

Deer located at an angle of 90o from the survey vehicle should be placed in the 

quadrant they moved from if known or can be reasonably assumed.

Quadrant: Using quadrant codes, record the quadrant each deer or deer group is 

located in relation to the survey vehicle (i.e., “LF” for left front, “LB” for left back, 

“RF” for right front, “RB” for right back).

Figures 5.03. Deer shown would be recorded with an angle of 0o and a quadrant code 

of “RF” because it can be reasonably assumed that the deer is moving from the right 

front quadrant of the vehicle into the left front quadrant. 

Number of Deer: Record the number of deer seen every time a deer (1 individual) or 

deer group (2 or more individuals) is observed. 

Habitat Type: Using habitat type codes, record the habitat type in which each deer 

or deer group is observed. Table 5.03 list habitat type codes. 

Table 5.03. Codes used to record habitat type during deer surveys. 

Habitat Type Code Explanation

SAV Savanna 

GRP Grassland/Prairie 

UPS Upland scrub 

UPF Upland forest 

RIG Riparian grassland 

RIS Riparian scrub 

RIF Riparian forest 

MOL Mowed lawn 

OTH Other 
43

IV. References 

Jester S. and J. Dillard. 2001. Conducting white-tailed deer spotlight surveys in the 

cross-timbers and prairie region of north and central Texas. 

http://www.tpwd.state.tx.us/publications/pwdpubs/media/pwd_rp_w7000_1126.pdf. 

Shult, M.J. and B. Armstrong. 1983. Deer census techniques. 

http://www.tpwd.state.tx.us/publications/pwdpubs/media/pwd_bk_w700_0083.pdf 
44

Spotlight Survey Form 

Field Data Form – White-tailed deer spotlight survey data form 

 GPS File Name

 Date:___/___/_______ Park: _________ Route:_____________ Observers:___________________________________ Start Time: ___

Beginning: Temperature: ______oC Humidity: _______% Wind: _______m/s Wind Direction: ______O Precipitation: 0 1 2 3 4 

Ending: Temperature: ______oC Humidity: _______% Wind: _______m/s Wind Direction: ______ O Precipitation: 0 1 2 3 4 

 Starting Cloud Cover: 0 1 2 3 4 5 6 7 Ending C

Group # 

assigned 

Side of 

vehicle 

Distance 

(m) 

Angle 

(O) 

Quadrant Number 

of deer 

Habitat 

type 

Comm
45

 Spotlight Survey Form: Categories, Definitions and Descriptions. Codes used to record precipitation and cloud cover, as well as side of vehicle, quadrant and habitat type a deer is observed in during whi

Rain 

Code 

 Explanation Cloud Cover 

Code 

Explanation Side of 

Vehicle Code 

Explanation Quadrant 

Code 

Explanation 

0 No rain 0 None present L Left side of vehicle LF Left Front 1 Mist or light fog 1 Trace – 1 % R Right side of vehicle LB Left Back 2 Light drizzle 2 1 – 5 % OR On Road RF Right Front 3 Light rain 3 5 – 25 % RB Right Back 4 Heavy rain; difficult to hear 4 25 – 50 % 5 Snow or heavy fog 5 50 – 75 % 

6 75 – 95 % 7 95 – 100 % 
46

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.6 Standard Operating Procedure 6: Establishing Visibility during 

Surveys 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. 

Version # 

Revision 

Date 

Author Changes Made Reason for 

Change 

New 

Version # 

 

 

This Standard Operating Procedure (SOP) gives step-by-step instructions on how to 

establish visibility, i.e., the area in which a deer might be seen during surveys. The 

procedures for: 1) collecting data, 2) logging data on a Global Positioning System unit, 

and 3) filling out paper data forms are covered in this SOP. 

I. Establishing Visibility during Surveys 

Determining the area surveyed for white-tailed deer is critical for obtaining an accurate 

estimate of deer density in the survey area. The following procedures describe how to 

estimate the amount of area surveyed across habitats using visibility measures taken with 

a spotlight and rangefinder. Visibility measures are taken on the first survey night after 

the deer counts are completed by recording the perpendicular distances from the survey 

vehicle to a point beyond which deer would not be visible. A four person crew is needed 

to measure visibility: a driver, a person to record and log data, and two people to measure 

perpendicular distances. Observers measuring perpendicular distances must be the same 

two individuals who conducted the deer count that night. 

Procedures: 

1. As soon as deer counts are completed, starting at the beginning of the survey route, 

measure visibility on each side of the survey vehicle every 0.16 km (1/10th mile). In 

an attempt to get a more robust picture of how much area is being surveyed along the 

route, the location of the survey vehicle should be adjusted slightly if objects are 

encountered that block the true area observed during a survey. For example, if the 

view of an open field is blocked by a single cedar tree in the ditch next to the survey 

vehicle, move the vehicle forward or backward to see the field. 
47

2. At each 0.16 km (1/10th mile) stopping point, use a rangefinder to measure the 

perpendicular distance at which an observer can no longer discern what they are 

seeing with a spotlight, especially if it is a deer. Estimate the distance if it is less than 

20 m. In areas were visibility is good, such as an open field, record visibility 

measures out to 250 m but no further. Deer are rarely discernible at this distance 

even under ideal field conditions. 

3. The location each perpendicular measure is taken is marked with a GPS unit. 

4. Using GIS technologies, perpendicular distances are plotted on a map, a polygon is 

created, and the survey area determined. SOP #7 “Geospatial Data Management” 

details how to determine the size of a survey area. 

II. Entering data on a Global Positioning System (GPS) unit 

Procedures: 

1. Prior to the first day in the field, load the DeerVisibility.ddf data dictionary onto the 

GPS unit. Steps on how to download data onto the GPS can be found in SOP #3 

“Using the Global Positioning System”. 

2. Before the visibility estimate begins, install the GPS unit inside the jeep. Do this by 

first assembling the magnetic mount, poles, and Hurricane antenna together and then 

place them in the center of the jeep. Next attach the cable that runs from the 

Hurricane antenna to the GPS unit (Trimble GeoXT). Make sure the GPS unit is on 

before plugging the cable in. 

Figure 6.01. Diagram of antenna assembly. 

 

3. On the GPS unit open the program TerraSync. Check the GPS unit settings, such as 

coordinate system, antenna options, and Max. PDOP which should be set to 6 (see 

SOP #3 pages 20 – 25 on how to do this). 

4. Once TerraSync is setup, create a new file by opening the data window and selecting 

new. In the field choices select the following: 

File Type: Rover 

Location: Default 

Dictionary Name: DeerVisibility 
48

File Name: The file name must match the file name recorded on the paper data form 

and include the Park Code (4 digits), year (4 digits), “deer” to identify the project, the 

survey number (#) 1, 2 or 3 and “vis” to identify this file as containing visibility 

measures (ex. wicr2007deer1vis). 

After the fields are filled out click Create. 

5. A new window is now open. Click on the Options drop down menu and select Log 

Now. Now highlight the VisibilityDeer choice and click Create. This opens the 

DeerVisibility data dictionary. Notice that the pencil icon is flashing at the top of the 

screen; this means it is collecting feature positions. The number indicates the amount 

of feature positions being collected for each visibility location. Fifty (50) feature 

positions should be captured for each visibility location. The data dictionary fields 

get filled out with the same attributes as the field sheet. The “Mile tenth” field 

populates itself, increasing a tenth for each new visibility point collected. The Right 

Distance and Left Distance fields are numeric. To populate the numeric fields click 

the keyboard icon at the bottom of the screen this will open a numeric keyboard. 

Input the distance that the observers tell you. After all fields are filled out and at least 

50 feature positions collected click OK. Repeat this step until all visibility 

observations are complete. 

Figure 6.02. Screen capture of the deer visibility data dictionary. 

6. After the visibility estimate is complete click Close and then Yes to the question: 

Close this file. Are you sure? If no more visibility estimates are to be done in the 

same evening close TerraSync and turn off the GPS unit. If another visibility 

estimate is to be done create a new file and repeat steps 4 – 6. 
49

7. Once all visibility estimates are completed for a park see SOP #3 for transferring, 

correcting, and exporting data, and SOP #7 “Geospatial Data Management” on 

managing the data. 

III. Filling out the Paper Data Form 

Procedures: 

1. When observers are determining visibility in the survey area, they should fill out a 

copy of the field data form “Visibility Estimates for Spotlight Survey” (an example is 

located at the end of this SOP) as a check for data logged on the GPS unit. The paper 

form also serves as the only record for general survey information (recorded at the top 

of the data form), as this information this is not logged with the GPS unit. The paper 

form is filled out simultaneously with the logging of GPS point data, so additional 

field time is not required to accomplish this task. 

2. Fill out the general information prior to starting the survey. 

3. Record the start time, starting odometer reading, date, observers, route and GPS file 

name. 

4. Record the left and right perpendicular distances at each 0.16 km (1/10th mile) 

interval as they are being logged with the GPS unit. 

5. At the end of each survey, record the ending time and ending odometer reading. 

6. The following is a complete list with descriptors for each variable that needs to be 

filled out when observers are determining visibility along a survey route. 

Date (mm/dd/yyyy): Write in the month (2 digits), day (2 digits), and year (4 digits) 

in the format shown for the day a visibility survey is being conducted. Include 

forward slashes. Example 07/19/2003 

Park: Write the appropriate Park Code (ARPO, PERI, or WICR). 

Route: Write a short descriptor identifying the survey route visibility is being 

measured along within a park (i.e., Tour Road).

Observers: Fill in the three initials of each crew member conducting the visibility 

measures using capital letters. Examples would be DGP for David G. Peitz or JTC 

for J. Tyler Cribbs. If someone does not have a middle name put an underscore for 

their middle initial. In the database, these initials will correspond to the full name and 

contact information for that person (the 3-character initials in the database must be 

unique, and if two people have the same initials, one should be given an honorary 

middle name). 

Beginning Odometer Reading (miles): Record the vehicle’s odometer reading to 

the 1/10th mile (0.16 km) at the beginning of the visibility survey. 

Ending Odometer Reading (miles): Record the vehicle’s odometer reading to the 

1/10th mile (0.16 km) at the end of the visibility survey. 
50

Start Time (hhmm): Write in the time to the nearest minute when observers start 

taking visibility measures, using the hour and minute format shown. Use military 

time (add 12 to the hour beginning with 1 pm through 11 pm). Fill in all four digits. 

Examples are 0630 (6:30 am), 0802 (8:02 am). Most sampling will occur during the 

evenings, therefore you would record 1:30 pm as 1330 and 8:00 pm would be 2000. 

End Time (hhmm): Write in the time to the nearest minute when observers stop 

taking visibility measures, using the hour and minute format shown. Use military 

time. 

GPS File Name (aaaaYYYYdeer#vis): Write in the Park Code (4 digits), year (4 

digits), “deer” to identify the project, the survey number (#) 1, 2, or 3, and “vis” to 

identify this file as containing visibility measures. In most years, the only survey 

number needed is 1. The GPS File Name recorded on a data sheet must correspond to 

its associated file name on the GPS unit. 

Left Distance (m): On the left side of the vehicle, record the horizontal distance in 

meters between the observer and a perpendicular point at which they can no longer 

discern what they are seeing with a spotlight, especially if it is a deer. Use a laser 

range-finder whenever possible to get as accurate a distance as possible. Do not 

round off numbers to the nearest 10 meters (i.e. 70, 80, 90 and so on); estimate the 

distance to the nearest meter. Perpendicular measures are taken at each 0.16 km 

(1/10th mile) stop along the survey route. In areas were visibility is good, such as an 

open field, record visibility measures out to 250 m but no further. 

Right Distance (m): On the right side of the vehicle, record the horizontal distance 

in meters between the observer and a perpendicular point at which they can no longer 

discern what they are seeing with a spotlight, as described above for Left Distance.

Comments: Record any comments that seem appropriate and that might help 

someone interpret and analyze the data correctly.
51

Visibility Estimates for Spotlight Survey 

Field Data Form – White-tailed deer spotlight survey data form 

Date:___/___/_______ Park: _________ Route:_____________ Observers:_____________________ 

Beginning Odometer Reading:_________________ Ending Odometer Reading:_________________ 

Start Time:__________ End Time:__________ GPS File Name:_________________________ 

1/10 

mile 

Left 

distance 

Right 

distance 

Comment 1/10 

mile 

Left 

distance 

Right 

distance 

Comment 

0.0 3.6 

0.1 3.7 

0.2 3.8 

0.3 3.9 

0.4 4.0 

0.5 4.1 

0.6 4.2 

0.7 4.3 

0.8 4.4 

0.9 4.5 

1.0 4.6 

1.1 4.7 

1.2 4.8 

1.3 4.9 

1.4 5.0 

1.5 5.1 

1.6 5.2 

1.7 5.3 

1.8 5.4 

1.9 5.5 

2.0 5.6 

2.1 5.7 

2.2 5.8 

2.3 5.9 

2.4 6.0 

2.5 6.1 

2.6 6.2 

2.7 6.3 

2.8 6.4 

2.9 6.5 

3.0 6.6 

3.1 6.7 

3.2 6.8 

3.3 6.9 

3.4 7.0 

3.5 7.1 
52

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.7 Standard Operating Procedure 7: Geospatial Data Management 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. Version 

# 

Revision 

Date 

Author Changes Made Reason for 

Change 

New 

Version # 

 

This Standard Operating Procedure (SOP) gives step-by-step instructions on: 1) creating 

a geodatabase, 2) entering GIS data, 3) working with tables and queries, 4) creating 

offsets, and 5) creating habitat GIS layers for white-tailed deer surveys on National Park 

Service lands within the Heartland Network Inventory and Monitoring Program. To 

complete this SOP, the software Microsoft Access and ArcGIS must be loaded on the 

computer. 

I. Geodatabase Creation 

Procedures: 

1. Open ArcCatalog and create a new geodatabase. 

2. For each UTM (Universal Transverse Mercator) zone that you will be collecting data 

in, create a feature dataset inside the geodatabase. The name given to the feature 

dataset should include the UTM zone and the label fds to distinguish it as a feature 

dataset (Ex. fds_Deer_nad83zone15). Set the coordinate system for the feature 

dataset. For Heartland Network parks the coordinate system used is UTM NAD83 

(Conus) and depending on what park zone 14N – 17N (see SOP #3 page 5 for park 

zone). Also set the X/Y Domain to the fullest possible extent that data may be 

collected in. 
53

II. Entering Spatial Data into the Geodatabase 

Procedures: 

1. Download, differentially correct, and export all Global Positioning System (GPS) 

rover files from the deer and visibility surveys into shapefiles (see SOP #3).

2. In ArcMap open all the deer location shapefiles for one park for the current year. Use 

ArcToolbox to merge these files together and save as a single feature class inside the 

correct feature dataset inside the geodatabase. The new file name should include fcl 

(to identify it as a feature class), park code, project name, year, and the letter “t” (to 

identify it as a point layer) (Ex. fclWicrDeerSurveyData2007t). 

3. Error check the deer location feature class attribute table fields against the field sheets 

and clean up any errors. 

4. In the attribute table add the field ‘DeerID’. This field is a numeric integer. The 

DeerID field is a unique identification used for all deer observations through all parks 

and all years. Add this field in ArcMap using the AlaskaPak extension. Highlight the 

file the field is to be added to. Then select AlaskaPak, click on Add Unique ID. 

When the unique ID window opens change Field Name to DeerID, and in the 

Starting Value type in what the highest DeerID value in the tbl_SurveyData_Master 

(located in the deer geodatabase) with a 1 added to it. 

5. In ArcMap open all the visibility survey location shapefiles for one park for the 

current year. Use ArcToolbox to merge these files together and save as a single 

feature class inside the correct feature dataset inside the geodatabase. The new file 

name should include fcl, park code, Visibility, year, and the letter “t” (to identify it as 

a point layer) (Ex: fclWicrVisibility2007t).

6. Error check the visibility location feature class attribute table fields against the field 

sheets and clean up any errors. 

 

III. Geodatabase Tables and Queries

Procedures: 

1. First add new deer survey data to the tbl_SurveyData_Master table. This is done by 

exporting a temporary copy of the new GIS deer locations attribute table (Ex. 

Copy_fclParkDeerSurveyData20XXt). The temporary table should be saved in the 

highest level of the geodatabase. Next using an append query (Query1 in 

geodatabase) add data from Copy_fclParkDeerSurveyData20XXt to 

tbl_SurveyData_Master. Once the new data is appended to the master table, delete 

the temporary table file. 

2. The second step is to calculate the perpendicular and parallel distances for the deer 

location data (see Figure 7.01), which will be used to create the GIS offset layers in 

section IV. This is done by creating a select query in Microsoft Access. In the query 

design view add the tbl_DeerSurvey_Master table. Next add the following fields to 

the select query: DeerID, EventID, Replicate, Distance_m, Angle, and Quadrant_C. 

The final two fields are calculated. The first calculated field will be perpendicular 

distance and the second will be parallel distance (see Figure 7.02). The equations for 
54

these calculations are below. Once this select query is created it will update 

automatically each time new data is added to the tbl_DeerSurvey_Master table. 

Distance Equations: 

y = Sin (u * π/180) * r 

x = Cos (u * π/180) * r 

u = angle the vehicle is to the deer (Angle field from tbl_SurveyData_Master in 

database) 

r = rangefinder distance (Distance_m field in the tbl_SurveyData_Master in database) 

x = parallel distance 

y = perpendicular distance 

π = pi (3.14159265358979) 

Figure 7.01. Distance equation diagrams. 
55

Figure 7.02. Snapshot of the perpendicular and parallel distance select query. 

IV. Creation of GIS Offset Layers of Deer Locations

Procedures: 

1. Identify distance tables: Inside the geodatabase there is a query named 

qry_PerpendicularParallelDistance. This query calculates the perpendicular 

distance, which is the distance between the deer and the road at a 90 degree angle and 

the parallel distance, which is the distance along the road between the GPS point on 

the road and the start of the perpendicular distance. This table will be referenced 

multiple times in the steps below, so have a copy or a printed version for the park and 

the year you are working on handy. 

2. Create two new GIS files: This can be done in ArcCatalog by right mouse clicking, 

selecting New, and then choosing the correct file type. The first file will be a feature 

class located within the correct feature dataset in the geodatabase. This feature class 

will become the offset data for the current year. The file name should include fcl (to 

identify it as a feature class), park code (4 letters), DeerSurveyDataOffset, year, and 

the letter “t” (to identify it as a point layer). An example is 

fclWicrDeerSurveyDataOffset2007t. In this file add an attribute field called DeerID. 

The second file to create is a temporary line shapefile. This file will be the parallel 
56

distance from the deer location collected with the GPS unit. For the purpose of this 

document this file will be referred to as LineTemp.shp. 

3. Open the program file ArcMap. 

4. Digitize parallel line features: In the ArcMap project, open the following layers: deer 

GPS locations on tour road for the current year (ex: fclParkDeerSurveyData20XXt), 

park tour road, park boundary, and the 2 files created in step 2 

(fclParkDeerSurveyDataOffset20XXt and LineTemp). 

5. Start the editor with the Task as New Feature and Target as LineTemp. Set the 

Snapping tool for the fclParkDeerSurveyData20XXt layer only. 

6. You will now digitize new line features in the LineTemp file using the sketch tool. 

Click once on a fclParkDeerSurveyData20XXt point. Next input the parallel length 

measurement for the point you are working on. This can be done by right clicking 

and selecting Length from the menu or by typing Ctrl^L. A Length textbox is now 

open. Type in the Parallel Distance for the point and Enter. The line is now locked 

to the length of the parallel distance. Now move the line so that it runs straight out 

along the road. The directions the line runs depends on the Quadrant_C attribute field 

for the point, which indicates if the line runs in front or behind the GPS location. 

When you have the line placed in the correct spot, double click the left mouse button 

to finish the line. Repeat this step for all deer locations. 

7. Digitize deer offsets: After the LineTemp file is complete, change the editor Target

to fclParkDeerSurveyDataOffset20XXt and the snapping options to 

fclParkDeerSurveyData20XXt and LineTemp, vertex only for both files. 

8. Now digitize the deer offset points (fclParkDeerSurveyDataOffset20XXt) by using 

the Distance-Distance editor tool. First click on the fclParkDeerSurveyData20XXt 

point. Next type D on the keyboard, this opens a distance textbox. Type in the value 

Distance_m from the table and Enter. You will see a circular buffer appear around 

the point. Then click on the far end of the LineTemp line and type D on the keyboard 

again, type the perpendicular distance in and Enter. Notice that your mouse snaps 

to the locations that the two circles intersect. See what your Quadrant_C attribute 

says (right or left) and click on the intersecting point on the correct side. Attribute the 

table with the correct DeerID number. Repeat this step for all deer locations. 

9. Make sure all edits are saved and click Stop Editing from the Editor menu. 

V. Creation of GIS Habitat Layers 

Procedures: 

1. In ArcCatalog create two new files. The first file will be a feature class polygon 

saved in the correct feature dataset in the geodatabase. This file will be the visibility 

extent that can be seen during the deer surveys. Name the file fcl, park code, 

DeerHabitat, year, and the letter “p” (to identify it as a polygon layer) (Ex: 

fclWicrDeerHabitat2007p). The second file will be a temporary line shapefile. This 

file can be named anything as long as you remember what the name is until the 

completion of this section. For the purposes of this document the file will be called 

VisTemp.shp. 
57

2. Open ArcMap and add the following layers to the project: fclParkDeerHabitat20XXp, 

VisTemp, tour road, park boundary, and fclParkVisibility20XXt. 

3. In this step, if more then one night of visibility estimates are made it helps to either 

display only one night of visibility points out of the number taken (by using the 

definition query) or display the different nights in different colors or symbols. Open 

the attribute table for the visibility points. Start the Editor, select New Feature as the 

Task and VisTemp as the Target. The snapping tool should be set for the 

fclParkVisibility20XXt file. You will now digitize the rangefinders lines of sight. 

Click on the first visibility point and then press Ctrl^L on the keyboard (this brings 

up the length textbox). Type in Left Side of the Vehicle measurement and Enter. 

Move your line so that it is on the left side of the road at a perpendicular angle to the 

road. Next click on the same visibility point and then press Ctrl^L on the keyboard 

(this brings up the length textbox). Type in Right Side of the Vehicle measurement 

and Enter. Move your line so that it is on the right side of the road at a perpendicular 

angle to the road. Do this for all visibility GPS points. 

4. Once all VisTemp lines are created, the next step is to digitize the habitat polygon. In 

the ArcMap project open the deer offset layer for the park and year you are working 

on. Then on the Editor toolbar change the target to fclParkDeerHabitat20XXp and 

the snapping to VisTemp vertex only and fclParkDeerSurveyDataOffset20XXt. 

Next digitize the habitat polygon. Start with the first VisTemp line on the left of the 

road and click on the end of the line. Now digitize the polygon along the outside 

edges of the VisTemp layer and if the fclParkDeerSurveyDataOffset20XXt layer is 

beyond the VisTemp digitize it into the habitat polygon (see Figure 7.03). When 

finished digitizing click Save and Stop editing. 
58

Figure 7.03. Example of deer visibility and habitat GIS layers. 

5. Finally add the acreage measurement to fclParkDeerHabitat20XXp file. This can be 

done by highlighting the file in the ArcMap data view and selecting Add Acres/Miles

from the AlaskaPak extension menu. The completed geodatabase should resemble 

Figure 7.04. 
59

Figure 7.04. File tree of the deer geodatabase. 
60

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.8 Standard Operating Procedure 8: Data Management 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. Version 

# 

Revision 

Date 

Author Changes Made Reason for 

Change 

New Version 

# 

 

This Standard Operating Procedure (SOP) gives step-by-step instructions on how to 

manage data for white-tailed deer monitoring on National Park Service lands within the 

Heartland Network Inventory and Monitoring Program. 

I. Metadata 

Data for the white-tailed deer monitoring project is maintained in an ArcGIS (ESRI, Inc.) 

geodatabase called Deer_Surv_GDB. Use of a geodatabase allows the data manager to 

take advantage of the ArcGIS metadata utilities. The geodatabase itself is simply a 

container for the data. Metadata specifically addresses feature datasets and the feature 

classes which are contained in the geodatabase. 

Detailed metadata including attribute information should be created for each feature 

class. 

Procedure: 

1. Open ArcCatalog. 

2. Highlight DeerSurv_GDB_2.1 from the directory in the left window. 

3. Select FGDC ESRI in the Stylesheet on the upper left part of the window. 

4. Expand the directory tree so that the geodatabase is expanded to show all of the 

feature datasets and feature classes. 

5. Highlight a feature class in the left window. 

6. In the right window, there are three tabs: Contents”, “Preview” and “Metadata”. 

7. Click on the “Metadata” tab. 

8. If metadata has already been created, there will be entries for “Description”, 

“Spatial” and “Attributes” sections. 
61

9. Preview the existing metadata by clicking on the various tabs and headings. 

10. To edit the existing metadata, click on the button (pencil and paper icon) to the 

right of the Stylesheet combo box. 

11. A form will appear for editing the metadata (see Figure 8.01). 

12. Fill out the form and save your changes. 

13. Export the new or modified metadata. 

14. Click on the export button to the right of the Style Sheet selection on the top bar. 

15. Save in XML format as this is the industry standard for metadata. Do not use html 

format except for display purposes. 

16. Upload metadata (XML file) to the WASO clearinghouse, NR-GIS or the 

equivalent. Contact WASO I&M staff for the latest upload procedures (see 

Section V below for current procedures). 

Figure 8.01 – Metadata editing tool for ArcGIS feature classes. 

II. Data Model 

The data model for the deer monitoring geodatabase is shown in Figure 8.02 below. The 

geodatabase should be maintained in three parts: (a) event-related data such as weather 

and start/end times for each survey; (b) deer observations and locations logged into the 

GPS using a data dictionary and (c) purely spatial data gathered by the GPS unit. Both (b) 

and (c) should be directly imported from the GPS into the GIS. 
62

Figure 8.02 – Entity relationship diagram for Deer_Surv_GDB_2.1 

III. Data Entry 

Data entry is limited to event-related data. This data is recorded at the top of each 

spotlight survey form. The data must be entered manually into Access. 

Procedure: 

1. Open the geodatabase using Access. 

2. The Event data form will appear (see Figure 8.03 below). 

3. Select the PeriodID for the sampling event. 

4. New periodIDs should be created by the project leader by filling out a new record 

in tbl_SamplingPeriods. The new periodID will appear on the SamplingEvents 

form. 

5. Enter the date, start time, end time, name of the route and count #. Count # will 

usually be one because most surveys pass only once on the survey route. If more 

than one survey is conducted, then increment the count #. 

6. Enter observer initials. 

7. Make entries at the start and end of the survey for: temperature, humidity, wind 

speed, wind direction and precipitation. 

8. Complete one record for each survey. 

shapefile 

Coverage 

geodatabase 

(a) (b) (c) 
63

Figure 8.03 – Data entry form for Sampling Event records. 

IV. Data Verification and Validation 

Data verification and validation is greatly simplified by using a detailed data dictionary 

with the GPS unit. Field data entry for deer counts represents most of the monitoring 

data. Since it is already in electronic format, copy errors from paper data sheets to the 

database are eliminated. Data verification of weather data is still necessary. Follow the 

directions below for both tbl_SamplingEvents and tbl_EventObservers. 

Procedure: 

1. Open the table. 

2. Print records corresponding to the current year. 

3. Verify all values with original field data sheets. 

4. Make corrections directly to the table. 

5. Repeat steps 3 and 4 until there are no errors. 

Data validation for deer counts is accomplished through the geodatabase. EventID related 

data is validated entirely through the data entry form. PeriodIDs are restricted to tablebased pick lists; park and EventIDs are auto-generated by PeriodID, date and time. 

Weather and physical conditions are limited by control validation rules, that is, range 

limits for values entered into text fields. 
64

V. Database Administration and Availability 

Details on how to administer monitoring databases and how to make them available are 

discussed in the Heartland Network Data Management Plan. The Plan may be 

downloaded at: 

http://www1.nature.nps.gov/im/units/htln/data_management/data_management.htm

Availability of metadata is critical. In order for potential data users to know the available 

data products at your program, they must have access to metadata. 

Posting the databases themselves on clearinghouse websites is less critical. They are 

dynamic and quickly become out-of-date. They are also large and more easily distributed 

on an “as needed” basis via “ftp”. Metadata may be uploaded to NPS WASO NR-GIS 

clearinghouse at 

http://science.nature.nps.gov/nrdata/

Detailed procedures are provided for uploading metadata at this site. 

VI. References 

Rowell, Gareth A., Michael H. Williams and Michael D. DeBacker. 2005. Data 

Management Plan: Heartland I&M Network And Prairie Cluster Prototype 

Monitoring Program. 
65

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.9 Standard Operating Procedure 9: Data Summary and Analysis 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. Version 

# 

Revision 

Date 

Author Changes Made Reason for 

Change 

New Version 

# 

 

This Standard Operating Procedure (SOP) gives step-by-step instructions on how to 

summarize and analyze white-tailed deer monitoring data collected on National Park 

Service lands within the Heartland Network Inventory and Monitoring Program. A 

critical component of any long-term monitoring protocol is a consistent and systematic 

way of analyzing and reporting on information (data) collected. The information must 

serve two purposes: (1) describe the current condition or status of a deer population, and 

(2) detect changes in a population through time. 

I. Data Summary 

Index of Relative Abundance

The variable selected for data summary purposes is an index of relative population 

density. This index is positively related to absolute abundance, but to an unknown 

degree. This annual index of relative population density provides information to park 

managers on trends in park deer populations and may provide feedback on the effects of 

implemented management efforts (e.g., population control or vegetation restoration 

efforts). This index of relative population density, defined as the number of individuals 

observed from the road/km2, allows evaluation of annual change in addition to long-term 

trends. To calculate this index of relative abundance, two pieces of information are 

needed: (1) the number of individuals within the sample area, and (2) the size of the area 

sampled. 
66

Procedures: 

1. Using the area surveyed annually (see SOP #7 “Geospatial Data Management” for 

details on determining annual survey areas), calculate the index of nightly deer 

densities for a park as: 

D = C / A 

 D = index of deer density in individuals/km2

 C = maximum number of deer counted 

 A = annual area surveyed (km2

) 

2. Calculate the annual mean deer density and standard deviation from the nightly 

maximum deer counts for that year, usually six. 

3. Determine the range in deer population densities each year from replicate values. 

Mapping Deer Distribution

The locations of individual deer and deer groups will be mapped for the monitoring 

period (Figure 9.01). Areas where deer congregate in the park and preferred habitats are 

easily visualized from the map. All deer maps are to be created by using ArcGIS. The 

layout of the maps should have a similar look to them from year to year and park to park. 

 

Procedure:

1. Open ArcMap 

2. Add the following layers to the map dataview: deer locations, park boundary, and the 

most current park image for the background. 

3. On the map layout add the following items: scale bar in meters, scale text, legend, and 

north arrow. 

4. When finished export the map as a .jpeg and store in the project folder. 
67

Figure 9.01 - Distribution of deer at Wilson’s Creek National Battlefield, 2006. 

II. Data Analysis 

Recommendations for Routine Data Summaries and Analyses

Procedures: 

1. The percent change in annual deer densities from the previous year is calculated as 

follows: 

 + % change = [(second year density – first year density) / first year density] x 100 

Recommendations for Long-term Trend Analyses

Procedures: 

1. The primary method of evaluating long-term trends will be to plot point estimates of 

relative abundance, along with some associated measure of variability or reliability 

over time. Graphs are easily interpretable and serve as useful tools for interpreting 
68

monitoring results by resource managers. Standard deviations or standard errors 

serve as estimates of variability; confidence limits serve as estimates of reliability. 

Confidence limits are expressed in terms of a confidence coefficient. Although the 

choice of confidence coefficient is somewhat arbitrary, in practice 90% and 95% are the 

most commonly used. 

Confidence limits (1 - ) are defined as (assuming a normal distribution): 

Y ± t( /2, N -1) s /√ N

where Y is the sample mean, s is the sample standard deviation, N is the sample size,  is 

the desired significance level, and t( /2, N -1) is the upper critical value of the t distribution 

with N - 1 degrees of freedom. 
69

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.10 Standard Operating Procedure 10: Reporting 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. 

Version 

# 

Revision 

Date 

Author Changes Made Reason for Change New 

Version 

# 

 

I. Report Format 

Template

The report template for Natural Resource Technical Reports should be followed 

(http://www.nature.nps.gov/publications/NRPM/index.cfm). Natural resource reports are 

the designated medium for disseminating high priority, current natural resource 

management information with managerial application. The Natural Resource Technical 

Reports series is used to disseminate the peer-reviewed results of scientific studies in the 

physical, biological, and social sciences for both the advancement of science and the 

achievement of the National Park Service’s mission. 

Style

Standards for scientific writing as recommended in the CBE Style Manual (CBE Style 

Manual Committee 1994) should be followed. Reports should be direct and concise. 

Refer also to Mack (1986), Goldwasser (1999), Day and Gastel (2006), and Strunk and 

White (2000) for guidelines on appropriate writing style. 
70

Types of Reports and Review Process 

Table 10.1 summarizes the types of reports produced and review process. Adapted from 

DeBacker et al. 2005. 

Type of Report Purpose of Report Primary Audience Review Process Frequency 

Annual Status 

Reports for 

Specific Protocols 

Summarize 

monitoring data 

collected during the 

year and provide an 

update on the status 

of selected natural 

resources. 

Document related 

data management 

activities and data 

summaries. 

Park resource 

managers and 

external scientists 

Internal peer 

review by HTLN 

staff 

Annually 

Executive 

Summary of 

Annual Reports for 

Specific Protocols 

Same as Annual 

Status Reports but 

summarized to 

highlight key points 

for non-technical 

audiences. 

Superintendents, 

interpreters, and the 

general public 

Internal peer 

review by HTLN 

staff 

Simultaneous with 

Annual Status 

Reports 

Comprehensive 

Trends and 

Analysis and 

Synthesis Reports 

Describe and 

interpret trends in 

individual vital 

signs. Describe and 

interpret 

relationships 

among observed 

trends and park 

management, 

known stressors, 

climate, etc. 

Highlight resources 

of concern that may 

require 

management action. 

Park resource 

managers and 

external scientists 

Internal peer 

review by HTLN 

staff 

Every 5-7 years 

Executive 

Summary of 

Comprehensive 

Trends and 

Analysis and 

Synthesis Reports 

Same as 

Comprehensive 

Trends and 

Analysis and 

Synthesis Reports, 

but summarized to 

highlight findings 

and 

recommendations 

for non-technical 

audiences. 

Superintendents, 

interpreters, and the 

general public 

Internal peer 

review by HTLN 

staff 

Simultaneous with 

Comprehensive 

Trends Analysis 

and Synthesis 

Reports 
71

Report Distribution 

Following review, annual reports will be distributed by September 1st of the year in 

which data is collected. Reports can also be distributed to partners involved in 

conservation of the monitored resource. This determination is made by the park, the 

network, or the regional office. All data collected is public property and subject to 

requests under the Freedom of Information Act (FOIA). However, sensitive data, such as 

the location of rare species, must be withheld in some cases. Reports containing nonsensitive data will be made publicly available and disseminated through the network 

website. 

IV. References 

CBE Style Manual Committee. 1994. Scientific style and format: the CBE manual for 

authors, editors, and publishers. 6th edition. Council of Biology Editors, Cambridge 

University Press, New York, New York. 

Day, R. A. and B. Gastel. 2006. How to write and publish a scientific paper. 6th edition. 

Greenwood Press, Westport, CT. 

DeBacker, M. D., C. C. Young, P. Adams., L. Morrison, D. Peitz, G. A. Rowell, M. 

Williams, and D. Bowles. 2005. Heartland Inventory and Monitoring and Prairie 

Cluster Prototype Monitoring Program vital signs monitoring plan. U.S. National 

Park Service, Heartland I&M Network and Prairie Cluster Prototype Monitoring 

Program, Wilson’s Creek National Battlefield, Republic, Missouri. 

Goldwasser, L. 1999. A collection of grammatical points. Bulletin of the Ecological 

Society of America. 79: 148-150. 

Mack, R. N. 1986. Writing with precision, clarity, and economy. Bulletin of Ecological 

Society of America 67:31-35. 

Strunk, W., Jr., and E. B. White. 2000. The Elements of Style. 4th Edition. Macmillan, 

New York, New York.
72

White-tailed Deer Monitoring Protocol for the 

Heartland Network Inventory and Monitoring Program 

10.11 Standard Operating Procedure 11: Procedures and Equipment 

Storage after the Field Season 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. Version 

# 

Revision 

Date 

Author Changes Made Reason for 

Change 

New Version 

# 

 

This Standard Operating Procedure (SOP) gives step-by-step instructions that all field 

observers using the white-tailed deer survey protocol should be familiar with and follow 

after the field season is completed. 

Procedures: 

1. Clean and repair all equipment prior to returning it to the proper storage areas in the 

HTLN storage building, office, or mobile trailer. All reference materials and extra 

data sheets should be filed in their appropriate filing cabinet. Clean the insides and 

outsides of all vehicles used in the field. 

2. Organize field data sheets and check that they have been filled out completely. As a 

rule, all data sheets should be reviewed for completeness before the crew leaves the 

field. However, because of the number of field days and crew members, some 

deficiencies in data recording may not be identified until all data sheet have been 

organized and reviewed as a group. If this situation arises, all attempts to locate 

deficient information should be made. If this is not possible, then an explanation on 

what information is missing should be placed in the trip report for that sampling 

event. Trip reports are links to their corresponding data through the database. 

3. Identify and obtain ancillary data. It is of critical importance that this data be 

incorporated into the deer monitoring efforts. First and foremost, knowledge of 

management efforts in a park for that year will be used to assess the effects of these 

efforts on deer numbers present. Certain plants affected by a management action may 

be utilized for food, cover, or bedding habitat by deer, thus altering the number of 

deer observed. Climate can also influence deer numbers, both directly and indirectly. 

Therefore, annual climate data will be obtained from active weather stations in or 

near each park. 

4. At the end of each field trip, file a trip report with the data manager, outlining daily 

accomplishments, hours worked, field-crew members and their responsibilities, and 
73

any unique situations encountered. This information is incorporated in the database 

and used during data analysis. This information is critical for identifying causes of 

discrepancies and inconsistencies in the data. The project manager is responsible for 

filing all trip reports. 
74

White-tailed Deer Monitoring Protocol for the Heartland 

Network Inventory and Monitoring Program 

10.12 Standard Operating Procedure 12: Revising the Protocol 

Version 1.00 (August 2007) 

Revision History Log: 

Prev. Version 

# 

Revision 

Date 

Author Changes Made Reason for 

Change 

New Version 

# 

 

This Standard Operating Procedure (SOP) explains how to make changes to the white-tailed deer 

monitoring Protocol Narrative and accompanying SOPs, and tracking these changes. Observers 

asked to edit the Protocol Narrative or any one of the SOPs need to follow this outlined 

procedure in order to eliminate confusion in how data is collected and analyzed. All observers 

should be familiar with this SOP in order to identify and use the most current methodologies. 

Procedures: 

1. The narrative for the “White-tailed Deer Monitoring Protocol for the Heartland Network 

Inventory and Monitoring Program” and accompanying SOPs has attempted to incorporate 

the most sound, up-to-date methodologies for collecting and analyzing deer data. However, 

all protocols regardless of how sound require editing as new and different information 

becomes available. Required edits should be made in a timely manner and appropriate 

reviews undertaken. 

2. All edits require review for clarity and technical soundness. Small changes or additions to 

existing methods will be reviewed in-house by HTLN staff. However, if a complete change 

in methods is sought, an outside review is required. Regional and national staff of the 

National Park Service with familiarity in deer monitoring and data analysis will be utilized as 

reviewers. Experts in deer research and statistical methodologies outside of the National 

Park Service will be utilized in the review process as well. 

3. Document edits and protocol versioning in the Revision History Log that accompanies the 

Protocol Narrative and each SOP. Log changes in the Protocol Narrative or SOP being 

edited only. Version numbers increase incrementally by hundredths (e.g., version 1.01, 

version 1.02, ...etc.) for minor changes. Major revisions should be designated with the next 

whole number (e.g., version 2.00, 3.00, 4.00 ...). Record the previous version number, date 

of revision, author of the revision, identify paragraphs and pages where changes are made, 

and the reason for making the changes along with the new version number. 

4. Inform the Data Manager about changes to the Protocol Narrative or SOP so the new version 

number can be incorporated in the Metadata of the project database. The database may have 

to be edited by the Data Manager to accompany changes in the Protocol Narrative and SOPs. 
75

5. Post new versions on the internet and forward copies to all individuals with a previous 

version of the affected Protocol Narrative or SOP. 
76

The NPS has organized its parks with significant natural resources into 32 networks linked by geography and shared natural 

resource characteristics. HTLN is composed of 15 National Park Service (NPS) units in eight Midwestern states. These parks 

contain a wide variety of natural and cultural resources including sites focused on commemorating civil war battlefields, Native 

American heritage, westward expansion, and our U.S. Presidents. The Network is charged with creating inventories of its species

and natural features as well as monitoring trends and issues in order to make sound management decisions. Critical inventories

help park managers understand the natural resources in their care while monitoring programs help them understand meaningful 

change in natural systems and to respond accordingly. The Heartland Network helps to link natural and cultural resources by 

protecting the habitat of our history. 

The I&M program bridges the gap between science and management with a third of its efforts aimed at making information 

accessible. Each network of parks, such as Heartland, has its own multi-disciplinary team of scientists, support personnel, and

seasonal field technicians whose system of online databases and reports make information and research results available to all. 

Greater efficiency is achieved through shared staff and funding as these core groups of professionals augment work done by 

individual park staff. Through this type of integration and partnership, network parks are able to accomplish more than a single 

park could on its own. 

The mission of the Heartland Network is to collaboratively develop and conduct scientifically credible inventories and long-term 

monitoring of park “vital signs” and to distribute this information for use by park staff, partners, and the public, thus enhancing 

understanding which leads to sound decision making in the preservation of natural resources and cultural history held in trust by 

the National Park Service. 

www.nature.nps.gov/im/units/htln/

The Department of the Interior protects and manages the nation’s natural resources and cultural heritage; provides scientific and 

other information about those resources; and honors its special responsibilities to American Indians, Alaska Natives, and 

affiliated Island Communities. 

NPS D-70, August 2007 
National Park Service 

U.S. Department of the Interior 

Natural Resource Program Center 

Natural Resource Program Center 

1201 Oakridge Drive, Suite 150 

Fort Collins, CO 80525 

www.nature.nps.gov 

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