National Park Service

U.S. Department of the Interior

Natural Resource Stewardship and Science

Analysis of VHF Moose Telemetry Data within the 

Upper Koyukuk River Drainage, 2008-2013

Natural Resource Report NPS/GAAR/NRR—2015/970
ON THE COVER

Sukakpak Mountain during VHF telemetry surveys, April 2009.

Photograph by: Kyle Joly
Analysis of VHF Moose Telemetry Data within the 

Upper Koyukuk River Drainage, 2008-2013

Natural Resource Report NPS/GAAR/NRR—2015/970

Matthew D. Cameron, Kyle Joly, and Mathew S. Sorum

Gates of the Arctic National Park and Preserve

4175 Geist Road

Fairbanks, AK 99709

May 2015

U.S. Department of the Interior

National Park Service

Natural Resource Stewardship and Science 

Fort Collins, Colorado
ii

The National Park Service, Natural Resource Stewardship and Science office in Fort Collins, 

Colorado, publishes a range of reports that address natural resource topics. These reports are of 

interest and applicability to a broad audience in the National Park Service and others in natural 

resource management, including scientists, conservation and environmental constituencies, and the 

public.

The Natural Resource Report Series is used to disseminate comprehensive information and analysis 

about natural resources and related topics concerning lands managed by the National Park Service. 

The series supports the advancement of science, informed decision-making, and the achievement of 

the National Park Service mission. The series also provides a forum for presenting more lengthy 

results that may not be accepted by publications with page limitations.

All manuscripts in the series receive the appropriate level of peer review to ensure that the 

information is scientifically credible, technically accurate, appropriately written for the intended 

audience, and designed and published in a professional manner. 

This report received informal peer review by subject-matter experts who were not directly involved 

in the collection, analysis, or reporting of the data. Data in this report were collected and analyzed 

using methods based on established, peer-reviewed protocols and were analyzed and interpreted 

within the guidelines of the protocols.

Views, statements, findings, conclusions, recommendations, and data in this report do not necessarily 

reflect views and policies of the National Park Service, U.S. Department of the Interior. Mention of 

trade names or commercial products does not constitute endorsement or recommendation for use by 

the U.S. Government.

This report is available from the Natural Resource Publications Management website 

(http://www.nature.nps.gov/publications/nrpm/). To receive this report in a format optimized for 

screen readers, please email irma@nps.gov.

Please cite this publication as:

Cameron, M. D., Joly, K., Sorum, M. S. 2015. Analysis of VHF moose telemetry data within the 

upper Koyukuk River drainage, 2008-2013. Natural Resource Report NPS/GAAR/NRR—

2015/970. National Park Service, Fort Collins, Colorado.

NPS 185/128681, May 2015
iii

Contents

Page

Figures...................................................................................................................................................iv

Tables....................................................................................................................................................iv

Abstract/Executive Summary ................................................................................................................v

Acknowledgments..................................................................................................................................v

Introduction............................................................................................................................................1

Methods..................................................................................................................................................2

Study Area ......................................................................................................................................2

Moose Capture and VHF Data .......................................................................................................2

Habitat Information ........................................................................................................................3

Land-cover and Fire Class Error Assessment ................................................................................3

Results....................................................................................................................................................4

Moose Locations ............................................................................................................................4

Home Ranges of Moose .................................................................................................................4

Habitat Use Patterns of Moose .......................................................................................................7

Land-cover and Fire Class Error Assessment ................................................................................9

Discussion............................................................................................................................................10

Management Implications....................................................................................................................11

Literature Cited ....................................................................................................................................12
iv

Figures 

Page

Figure 1. The Koyukuk moose study area with a Minimum Convex Polygon (MCP) 

encompassing all VHF moose detections from 2008 to 2013. ..............................................................1

Figure 2. All 2119 high-quality VHF moose locations in the study area from 2008 to 

2013........................................................................................................................................................5

Figure 3. Minimum Convex Polygons for the 4 male and 19 female moose with 30 or 

more detections with individuals identified by distinct colors. .............................................................6

Figure 4. Proportion of moose detections in each aspect category. ......................................................7

Figure 5. Proportion of moose detections in each GIS habitat type......................................................8

Figure 6. Proportion of moose detections in each fire history type. .....................................................9

Tables 

Page

Table 1. Number of survey days per month and year for the moose tracking effort within 

the upper Koyukuk River basin, Alaska, between March 2008 and March 2013. ................................3

Table 2. Estimates of moose home range size with 30 or more detections in the Koyukuk 

study area using 100% Minimum Convex Polygons. ............................................................................4

Table 3. Mean terrain ruggedness values for moose detections by sex.................................................7

Table 4. Totals of moose detections in each GIS habitat type. .............................................................8

Table 5. Comparison between visual and GIS habitat type classifications...........................................9
v

Abstract/Executive Summary 

From 2008 – 2013, 119 moose (Alces alces) – 27 males and 92 females – were radio collared and 

tracked via VHF relocation in the upper Koyukuk Valley of Alaska. We determined 2119 total 

locations, ranging from 1 – 53 per moose. Home ranges were delineated using 100% Minimum 

Convex Polygons (MCPs) for those moose with 30 or more locations. Habitat characteristics such as 

vegetation type, fire history, aspect, elevation, and terrain ruggedness were analyzed for each 

location. While we calculated the area of MCPs for individuals with 30 or more locations, we were 

not confident enough in the limited data to draw any conclusions on moose home ranges. Moose 

were detected most often in coniferous and mixed forests, exhibited a preference for unburned areas 

but avoided flat terrain. We compared moose habitat use based on visual observations during aerial 

radio telemetry flights with the habitat type as determined by GIS and satellite land cover imagery 

for that same location. Habitats classified by visual observation (which assessed the area around the 

moose) did not correspond well with remotely-sensed classifications (which were based on the exact 

coordinates for the moose). This could be due to a wide array of factors including differing 

methodologies. Burn classification showed a stronger agreement between the 2 data sources. While 

informative for some habitat use characteristics, this VHF data illustrates the point that larger data 

sets, such as those obtained from GPS collars, are necessary for robust home range and habitat 

analyses.

Acknowledgments

This project was promoted by public subsistence and wildlife advisory groups. Funding was provided 

by the National Park Service, US Fish and Wildlife Service, Alaska Department of Fish and Game, 

and the Bureau of Land Management. We thank pilots Troy Cambier, Mike Spindler, Marty Webb, 

Paul Zaczkowski, Curtis Cebulski, Les Dillard, Pete Christian, Andy Greenblatt, Heather Bartlett, 

Nikki Guldager, Dave Sowards, and Sandy Hamilton for making this project possible and safe. Stacia 

Backensto, John Burch, Jason Caikoski, Roy Churchwell, Tim Craig, Kristin DeGroot, Jen Dillard, 

Mel Flamme, Alyssa Morris, Christopher Harwood, Tony Hollis, Erin Julianus, Heidi Kristenson, 

Jim Lawler, Nate Pamperin, Tom Paragi, Kumi Rattenbury, Carl Roberts, Lisa Saperstein, Glenn 

Stout and many others provided critical assistance with project implementation. Christopher 

Harwood provided database expertise. We also thank John Burch for his review of this report.
1

Introduction

Public concern that the Dalton Highway Management Corridor might be acting as a population sink 

for moose moving from Kanuti National Wildlife Refuge and Gates of the Arctic National Park and 

Preserve helped prompt a study investigating the movements of moose in the upper Koyukuk River 

valley.

Figure 1. The Koyukuk moose study area with a Minimum Convex Polygon (MCP) encompassing all VHF 

moose detections from 2008 to 2013.
2

Methods

Study Area

The study area lies within the upper Koyukuk River region, including all of Kanuti National Wildlife 

Refuge, the southeast portion of Gates of the Arctic National Park and Preserve, sections of the 

Dalton Highway Management Corridor, and parcels of State and native owned lands (Figure 1).

Habitats range from alpine tundra, shrub lands, taiga and extensive wetlands. The climate is strongly 

continental.

Moose Capture and VHF Data

Moose were captured using standard aerial darting techniques and equipped with VHF telemetry 

collars. Thirty-seven individuals were instrumented with GPS collars but the analysis of those data is

presented elsewhere (see Joly et al. in press a, b). All moose captures adhered to State of Alaska 

Animal Care and Use Committee (ACUC) guidelines (#07-11). Radio tracking flights were 

conducted from March 13, 2008 until March 1, 2013. For each location, GPS coordinates and habitat 

characteristics of the surrounding area were recorded. Survey effort per month ranged from 0 – 7 

flights (Table 1) and was contingent on observer and plane availability, weather, logistics and 

funding.

High-quality (visual observation) moose locations were mapped, attributed and analyzed using 

ArcMap 10.3 (Environmental Systems Research Institute, Redlands, CA). We used VHF locations of 

moose to estimate home ranges using 100% Minimum Convex Polygons (MCPs) using the National 

Park Service’s animal movement toolbox in ArcMap 10.3 for all moose with 3 or more locations but 

focused analyses on moose with 30 or more locations.

We used VHF locations to describe habitat use patterns of moose. We used simple descriptive 

statistics (e.g., means) to evaluate use between sexes.
3

Table 1. Number of survey days per month and year for the moose tracking effort within the upper 

Koyukuk River basin, Alaska, between March 2008 and March 2013.

Month 2008 2009 2010 2011 2012 2013

Jan - 3 3 0 0 0

Feb - 2 3 2 2 3

Mar 5 4 4 4 4 1

Apr 3 3 4 4 2 -

May 7 3 6 4 2 -

Jun 1 1 0 2 0 -

Jul 4 3 5 3 0 -

Aug 5 3 2 2 2 -

Sep 4 2 5 4 2 -

Oct 1 3 1 4 3 -

Nov 2 2 7 2 4 -

Dec 2 3 0 0 0 -

Habitat Information

Land-cover and topographical variables used in the habitat use analysis for moose were determined 

from existing 30-meter resolution raster GIS data (Ducks Unlimited 2002a, 2002b, Homer et al. 

2007, Jorgenson et al. 2009). We used a digital elevation model (DEM) to create aspect and terrain 

ruggedness layers. We categorized aspect into northeast (0-90o), northwest (270-0o), southeast (90-

180o), and southwest (180-270). We assigned pixels with no slope as no aspect (flat). We calculated 

terrain ruggedness using the vector ruggedness measure (VRM; Sappington et al. 2007) at 2 scales:

180 m and 1 km. We reclassified initial land-cover classes into 8 classes (unvegetated, water, conifer 

forest, deciduous or mixed forest, sedge/herbaceous, tall shrub, dwarf shrub and tussock tundra). We 

estimated time since last fire (TSLF) using fire inventory data from the region (Alaska Fire Service).

All GIS-derived attributes were obtained from the 30-meter grid cell that contained the coordinates 

(i.e., latitude/longitude) of the visual observation.

Land-cover and Fire Class Error Assessment

We collected both land-cover and fire information at each VHF location during the telemetry flight.

We assessed the percentage of locations that had the same classification of land-cover and TSLF 

using the mirroring GIS layers and visual information collected at VHF locations. For the 

comparison, an area was considered burned if the digital fire data indicated 99 years or less since last 

fire and unburned if greater than 100 years.
4

Results

Moose Locations

We collected 2119 VHF locations via aerial telemetry flights from 119 individual moose (92 female, 

27 male) between March 2008 and March 2013 (Figure 2). The number of detections per animal 

ranged from 1-53.

Home Ranges of Moose

Of the 119 individuals monitored in this study, only 23 moose had ≥30 locations (Table 2). All of 

these had MCPs which intersected Kanuti National Wildlife Refuge (Figure 3). The number of 

locations for males (mean = 43.8) was similar to females (mean = 42.3) for these 23 moose.

Table 2. Estimates of moose home range size with 30 or more detections in the Koyukuk study area 

using 100% Minimum Convex Polygons.

Sex n Mean Area (km2) SE Range (km2)

Male 4 304.4 103.4 130.1 - 603.1

Female 19 510.4 118.9 83.7 - 2092.9
5

Figure 2. All 2119 high-quality VHF moose locations in the study area from 2008 to 2013.
6

Figure 3. Minimum Convex Polygons for the 4 male and 19 female moose with 30 or more detections 

with individuals identified by distinct colors.
7

Habitat Use Patterns of Moose

Use of topographical features varied by sex. Females tended to use lower elevation areas (365 m) 

than males (444 m). Individual means ranged from 155.8 to 866.2 m, while individual locations 

ranged from 121.9 m to 1271.9 m. Males were found, on average, in more rugged terrain, at both the 

fine (180 m) and coarse (1 km) scales that we analyzed (Table 3).

Table 3. Mean terrain ruggedness values for moose detections by sex.

Sex 180 m 1 km

Female 0.003969 0.029493

Male 0.004425 0.038107

Usage of flat areas was low for both sexes (Figure 4). Approximately 31 % of the study area was 

categorized as flat. Males were detected on southeast aspects more than any other aspect, while 

females were most commonly found on northwest slopes.

Figure 4. Proportion of moose detections in each aspect category.

Forested habitats were utilized heavily by both male and female moose (Table 4, Figure 5).

Specifically, conifer forest was the habitat type most used, though deciduous/mixed forest habitats 

were often used. Tall and dwarf shrub habitats were the next most commonly used groups, with 

relatively few locations found in other habitat types.

0

5

10

15

20

25

30

35

Flat NE SE SW NW

Proportion of Detections

Aspect Category

Female

Male
8

Table 4. Totals of moose detections in each GIS habitat type.

Vegetation Class

Count of Detections

Female Male

Unvegetated 109 17

Water 55 8

Conifer Forest 625 174

Deciduous/Mix Forest 393 54

Sedge/Herbaceous 29 10

Tall Shrub 212 43

Dwarf Shrub 293 71

Tussock 15 2

No Data 9 0

Total 1731 371

Figure 5. Proportion of moose detections in each GIS habitat type.

Both sexes utilized unburned areas most heavily (Figure 6), although males used unburned areas to a 

greater degree. Areas burned 10 - 30 years ago were the second most utilized by both sexes, and

females used recently burned and 30 – 60 year old areas more than males. Neither sex appeared to 

utilize areas burned 60 - 99 years ago.

0

10

20

30

40

50

Proportion of Detections

Land-cover Class

Female

Male
9

Figure 6. Proportion of moose detections in each fire history type.

Land-cover and Fire Class Error Assessment

We used land-cover and fire information collected at 1899 VHF locations to assess classification 

comparability of the digital land-cover and fire maps to visual observations obtained from radio 

tracking flights. This differs from the 2119 total locations due to incomplete data recording or 

incomparable vegetation characteristics.

Habitat types identified by observers from fixed-wing aircraft while tracking moose generally did not 

match up well with habitat types attributed to those locations using the GIS layers (Table 5). The 

most commonly used habitat types (conifer forest, deciduous/mixed forest and tall shrub) showed the 

greatest levels of agreement between the 2 systems, whereas infrequently used habitat types showed 

very poor levels of agreement.

Burn classification between the aerial observer and the digital fire perimeter data matched for 64.9% 

of all locations. Areas categorized as burned by the observer comprised 28.7% of all moose

locations.

Table 5. Comparison between visual and GIS habitat type classifications.

Vegetation Type Total Visual Locations % Match

Unvegetated 106 0

Water 58 10.3

Conifer Forest 716 45.8

Deciduous/Mix Forest 421 36.8

Sedge/Herbaceous 35 0

Tall Shrub 229 49.3

Dwarf Shrub 319 10.3

Tussock 15 0

0

10

20

30

40

50

60

70

0 - 10 10 - 30 30 - 60 60 - 99 100

Proportion of Detections

Years Since Last Fire

Female

Male
10

Discussion

On initial consideration, 2119 total moose locations collected throughout this 5 year study may seem 

substantial. However, when considered at the individual level, locations ranged from 1 to 53. We

considered home ranges of the 23 moose with 30 or more detections, but 50 detections is the widely 

accepted minimum for MCP analysis. We only had 3 moose with more than 50 detections. Further, 

we are not confident about making comparisons between male and female home ranges due to their 

differences in sample size, 4 and 19, respectively. These factors become evident when considering

the wide range of female MCP areas: 83.7 - 2092.9 km2. For all of these reasons, we are not 

confident enough in our home range data to make any VHF-based extrapolations for moose home 

ranges in the study area.

While these data are limited in scope for home range analysis, characteristics of each individual 

moose location can be informative. Moose were detected predominantly in conifer and 

deciduous/mixed forest types, which are the dominant vegetation type in the study area. Both sexes 

were detected most often in unburned areas, which may be surprising given the frequent fire history 

of the area and reported selection of habitats burned 10-30 years ago. We also found that moose used 

slopes more than flat areas. We did not provide available habitat information in this report because 

we feel the VHF data is not robust enough to analyze moose habitat use.

Comparisons of vegetation classification between aerial observations and remote sensing data 

exhibited less agreement than we expected. The most common habitat types exhibited the most 

agreement, although less than half matched up. Many explanations may account for this, such as 

micro-scale habitat differences within a larger habitat resolution scale, differences between observed 

habitat and the location marked by a GPS in an airplane, and differences between habitat types 

missed by remote sensing software. Visual assessment of habitat type from aircraft looked at the area 

nearby (i.e., ~ 1⁄4 mile circle around the moose), whereas the GIS assessment determined the habitat 

type for the exact, recorded position of the moose that fell within a 30m cell of the remotely-sensed 

land cover map. These methodological differences also likely were a factor in the poor agreement 

between techniques. In contrast, our fire history data exhibited greater concurrence. Aerial 

observations classified nearly 30% of locations as burned while roughly 35% of all locations were 

classified based on GIS layers as burned within the last 30 years (visually, the time frame most easily 

recognized as burned).
11

Management Implications

Many wildlife projects in Alaska have to make difficult decisions about the number and type of radio 

collars they utilize. VHF collars are much less expensive than GPS collars but require substantial 

aviation costs and risks in order to collect data. Dedicated efforts to aerial track VHF collared moose 

monthly only resulted in a maximum of 30-50 relocations per individual over a 5-year study period.

Using these data, male moose had smaller home ranges than females. This finding runs contrary to 

the results utilizing GPS radio collars in this study (Joly et al., in press a,b) and elsewhere 

(Hundertmark 1997) and is likely erroneous due to poor sample sizes of both individuals and number 

of relocations. While visual observations of habitat utilized by moose are likely superior to habitat 

classifications assigned by remotely-sensed imagery, the paucity of VHF relocations simply did not 

allow for a robust analysis of habitat selection using the VHF data. The premiere use of VHF collars 

comes from data that is not related to relocations but rather visual observations. In our study, that 

information is presence or absence of a calf, which will be utilized to analyze productivity of moose 

in the region in another resource report. For future moose projects involving tracking collars, we 

recommend the use of GPS-equipped collars for studies not solely focused on productivity. GPS 

collars collect more data at more regular and shorter intervals than VHF-only collars but also allow 

biologists to track individual animals and visually observe them, their environment, and how they 

interact with the environment, as needed, if the GPS collars are equipped with VHF beacons. The 

combination of copious data and biologists intimately connected to the data streams, via captures and 

visual observations from aircraft, will likely provide the greatest opportunities for data analysis and 

reasoned interpretation.
12

Literature Cited

Ducks Unlimited. 2002A. Dalton Highway Earth cover classification. BLM-Alaska technical Report 

XX (sic). Bureau of Land Management, Anchorage, Alaska, USA. 47 pp.

Ducks Unlimited. 2002B. Kanuti NWR/Ray Mountains/Hogatza River Earth cover classification. 

BLM-Alaska technical Report 28. Bureau of Land Management, Anchorage, Alaska, USA. 85 

pp.

Homer, C., J. Dewitz, J. Fry, M. Coan, N. Hossain, C. Larson, N. Herold, A. McKerrow, J. N. 

VanDriel, and J. Wickham. 2007. Completion of the 2001 National Land Cover Database for the 

Conterminous United States. Photogrammetric Engineering and Remote Sensing 73: 337-341.

Hundertmark, K.J. 1997. Home range, dispersal and migration. Pages 303-335 in Ecology and 

management of the North American moose, Franzmann, A. W., and C. C. Schwartz (editors). 

Wildlife Management Institute, Washington, DC, USA.

Joly, K., T. Craig, M. S. Sorum, J. S. McMillan, and M. A. Spindler. Moose (Alces alces) movement 

patterns in the upper Koyukuk river drainage, northcentral Alaska. Alces : In press A.

Joly, K., T. Craig, M. S. Sorum, J. S. McMillan, and M. A. Spindler. Variation in fine-scale 

movements of moose (Alces alces) in the upper Koyukuk river drainage, northcentral Alaska. 

Alces: In press B.

Jorgenson, M. T., J. E. Roth, P. F. Miller, M. J. Macander, M. S. Duffy, A. F. Wells, G. V. Frost, and 

E. R. Pullman. An ecological land survey and landcover map of the Arctic Network. Natural 

Resource Technical Report NPS/ARCN/NRTR—2009/270. National Park Service, Fort Collins, 

Colorado. 307 pp.

Sappington, J. J., K. M. Longshore, and D. B. Thompson. 2007. Quantifying landscape ruggedness 

for animal habitat analysis: a case study using Bighorn sheep in the Mojave Desert. Journal of 

Wildlife Management 71: 1419-1426.

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 185/128681, May 2015
National Park Service

U.S. Department of the Interior

Natural Resource Stewardship and Science

1201 Oakridge Drive, Suite 150

Fort Collins, CO 80525

www.nature.nps.gov

EXPERIENCE YOUR AMERICA TM