Reporting Issues and Trends of Alaska Moose Hunters

Jen Schmidt

Post Doc, Institute of Arctic Biology, UAF

Contact: fsjis@uaf.edu

Under Reporting by Moose Hunters: Background• Previously researched by Andersen and Alexander 1992 in interior

Alaska

• Ours differs in that we:– Expanded the focus to Statewide– Added some new parameters– More of a statistical approach

• Two measures of reported harvest– Subsistence household surveys conducted by members of the

community through the division of Subsistence at the Alaska Department of Fish and Game (ADF&G)

– Harvest tickets that are returned to division of Wildlife Conservation at ADF&G

• Measure of under reporting– Ratio = Subsistence Household Surveys

Hunter Harvest Tickets

Under Reporting by Moose Hunters: Limitations

• The “year” does not match up between the two databases– Subsistence (January-December)– Hunter Harvest Tickets (July-June)– Since most moose are harvested in the fall this minimizes this

issue since fall is in the same “year” for the two databases

• In large communities not all households can be surveyed so survey information must be extrapolated to represent the whole community

n = 118n = 97

Under Reporting by Moose Hunters: Model & Parameters

• General linear model

• Parameters (* used by Andersen and Alexander 1992) – Percent of a community that:

• Attempts to harvest a moose*

• Harvests a moose*

• Receives meat or other parts of a moose*

• Shares/Gives meat or other parts of a moose*

• Is Native*

– Population Size*– Median Household Income*– Presence of an Area Biologist employed by ADF&G*– Distance (Km) from a community with an Area Biologist– Presence of a license vendor

Model Results

Parameter * Co -Efficient

P-value

Intercept 0.86 0.919

% hunt a moose -0.16 0.161

% harvest a moose 0.54 0.008

% use a moose -0.46 0.023

% receive a moose 0.40 0.025

% give a moose 0.11 0.474

% Native 0.01 0.901

Distance to area biologist 0.03 0.125

Population size +0.00 0.600

Median household income -0.00 0.731

Presence of an area biologist

Yes N/A N/A

No 3.21 0.535

Presence of a license vendor

Yes N/A N/A

No -1.69 0.640

Parameter* Co-Efficient

P-value

Intercept 2.28 0.488

Harvest 0.42 0.002

Use -0.45 0.013

Receive 0.44 0.006

*Percent of a community

Positive value indicates increase in under-reporting

Full Model P- value = 0.02 Reduced Model P-value = 0.002

Strong Sharing Network

  Use moose meat or other parts

Attempt to harvest Harvest a moose Give moose meat or other parts

Attempt to harvest 0.75     Pearson Correlation 

  <0.0001     P-value  

Harvest a moose 0.75 0.80    

  <0.0001 <0.0001    

Give moose meat or other parts

0.81 0.62 0.76  

  <0.0001 <0.0001 <0.0001  

Receive moose meat or other parts

0.89 0.51 0.46 0.70

  <0.0001 <0.0001 <0.0001 <0.0001

Results: t-tests

Less Under-Reporting More Under-Reporting

n = 13 n = 84

Parameter Mean Standard Error

Mean Standard Error

P- value

% hunt 31.95 6.62 45.77 2.22 0.029

% harvest 11.58 3.43 27.91 1.89 0.002

% use 44.26 7.98 67.51 2.53 0.002

% receive 38.17 7.22 50.93 2.16 0.041

% give 13.28 3.03 27.39 1.71 0.002

% Native 31.85 7.63 74.30 3.22 <0.001

Population size* 1,032 506 563 110 0.382

Distance to area biologist 87.16 18.35 113.14 8.65 0.265

Median household income

37,587 3,886 32,590 1,343 0.185

* Indicates unequal variances

Under Reporting by Moose Hunters: Conclusions

• The simplest model that explains under reporting contains the percent of the community that:– harvests a moose– uses meat or any part of a moose– receives meat or any part of a moose

• Smaller and more rural communities appear to have more under reporting, but if small amounts of under reporting by large cities can amount to large under reporting

Under Reporting by Moose Hunters: Future

• Explore if reporting rates differ in areas that have or had co-management programs or working groups

• Better understand why the results from the two methods used differ for the percent of the community that hunts moose and uses moose meat or parts

Statewide Trends in Moose Hunting

Background

• Data used was the hunter harvest tags returned by moose hunters to the Alaska Department of Fish and Game (ADF&G) regardless of success

• Statewide analysis

• Dates range from 1990 to 2006

Number of Moose Hunter, Harvest, and Success

0

5000

10000

15000

20000

25000

30000

35000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

0%

5%

10%

15%

20%

25%

30%

Hunted

Killed

Success

Success by Transportation Type for Moose Hunters in Alaska from 2003 to 2006

0%

10%

20%

30%

40%

50%

60%

Airpla

ne

Horse

/Dog

Tea

mBoa

t

3 or

4 W

heel

er

Snowm

achi

neO

RV

Highw

ay

Airboa

t

% Success

% Use

n = 111,985p < 0.001

n = 111,985p < 0.001

In the legend the change in 3 or 4 wheeler use decreases from left to right

Top 10 GMUs with Biggest Change in 3 or 4 Wheeler Usage from 1990 to 2006

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

14A 20B 20A 13A 15C 13E 20D 20E 16A 13B

Average Distance by Success for Moose Hunters

0

15

30

45

60

75

90

105

120

135

150

165

180

195

1987 1992 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Av

era

ge

Dis

tan

ce

(K

M)

Successful

Unsuccessful

Average Distance (KM) to Harvest a Moose

0

100

200

300400

500

600

700

800

Dis

tanc

e (K

M)

1990-06 Average

2006

72753

3

93

5442

713 9103

25

470

28

Numbers above bars represent number of hunters who were successful in 2006

Conclusions

• Management decisions at the local level can be observed at the Statewide level

• Location and presence of moose influence how far hunters travel

• There is a lot of spatial variability, however certain trends can be observed such as:– Increase of 3 or 4 wheelers and airboats– Relatively content number of moose hunters, harvest

level, and overall success

Thanks to EPSCoR for there support

Also thanks to the Alaska Department of Fish and Game for the use of their data and

feedback.

Jen SchmidtContact: fsjis@uaf.edu

Examples of moose-habitat rules• Direct climate effects on moose

– Moose void deep snow (>2.3 ft) because it increases death of moose– Warm conditions are stressful for moose

• Winter >23°F (-5°C); Summer 57°F (14°C)

• Indirect climate effects: More wildfire– Moose prefer recent burns (11-25 years)– Moose prefer burn edges and unburned patches within a burn– Moose move into burns if moose density high – Moose move into burns if unburned habitat is poor for moose and/or

limits the number of moose• Changes in vegetation

– Moose prefer deciduous over spruce or tundra, so changes of spruce or tundra to deciduous will increase moose habitat

• Hunter behavior– Moose hunting is concentrated near roads and rivers– Weather (e.g., warm fall, early snow) influences harvest success– Increased temperature in fall can lead to spoilage of moose meat– Influence of gas price/employment on harvest level