The Relationship between Wildlife Watchers, Hunters, and Anglers Addendum to the 2001 National... 
|
small (250x250 max)
medium (500x500 max)
large ( > 500x500)
Full Resolution
|
|
U.S. Fish & Wildlife Service
The Relationship between
Wildlife Watchers,
Hunters, and Anglers
Addendum to the 2001 National
Survey of Fishing, Hunting, and
Wildlife-Associated Recreation
Report 2001-7
The Relationship between
Wildlife Watchers,
Hunters, and Anglers
Addendum to the 2001 National
Survey of Fishing, Hunting, and
Wildlife-Associated Recreation
Report 2001-7
U.S. Fish & Wildlife Service
March 2005
Jerry Leonard
Division of Federal Assistance
U.S. Fish and Wildlife Service
Arlington VA
This report is intended to complement the National and State Reports for the
2001 National Survey of Fishing, Hunting and Wildlife-Associated Recreation.
The conclusions in this report are the author’s and do not represent official positions
of the U.S. Fish and Wildlife Service.
The author thanks Sylvia Cabrera, Richard Aiken, Natalia Perez, Jim Greer, and
Dave Buschena for valuable input into this report.
2 The Relationship between Wildlife Watchers, Hunters, and Anglers
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Report Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Data and Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Part One—Wildlife-Watching Participation by Sportsperson Classification . . . . . . . . . . . 5
Wildlife Watching Nationally . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Wildlife Watching by State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Part Two—Socioeconomic Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Comparison of Wildlife Watchers and Sportspersons . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Characteristics of Different Recreationist Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Implication of Demographic Change on Wildlife-Related Recreation . . . . . . . . . . . . . 16
Part Three—Expenditures by Type of Recreationist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Part Four—Historical Fishing and Hunting Activity of Wildlife Watchers . . . . . . . . . . . . 20
Part Five—Wildlife-Watching Participation Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Calculated Probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
A. Wildlife-Watching Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
B. Wildlife-Watching Days by State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
C. Selected Characteristics of Wildlife Watchers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
D. Expenditures for Wildlife Watching and Sporting Activities . . . . . . . . . . . . . . . . . . 38
Contents
The Relationship between Wildlife Watchers, Hunters, and Anglers 3
Introduction
In 2001 there were 82 million U.S.
residents 16 years old and older
who participated in wildlife-related
recreation. This total of wildlife-related
recreationists is often split into two
different types: non-consumptive
and consumptive. Non-consumptive
recreation includes activities such as
feeding, observing, or photographing
wildlife. Consumptive recreation
includes both hunting and fishing. In
2001 participants in non-consumptive
activities, who are often referred to as
wildlife watchers, totaled 66.1 million,
and participants in consumptive
activities, who are often referred to as
sportspersons, totaled 37.8 million.
A graphical representation of
consumptive and non-consumptive
recreationists is presented in Figure 1.
54% of wildlife-related recreationists
were wildlife watchers only, 19% were
sportspersons only, and 27% were both
wildlife watchers and sportspersons.
The populations of consumptive and non-consumptive
recreationists are certainly
interrelated. Both share a mutual
concern and appreciation for the outdoors
and wildlife resources. Moreover, there
are a relatively large number who
participate in both non-consumptive and
consumptive recreation.
Of the 37.8 million sportspersons (anglers
and hunters) nearly 22 million were also
wildlife watchers in 2001. To some that
feel sportspersons and watchers have few
common interests, this statistic may come
as a surprise. Pick a sportsperson at
random and there is nearly a 60% chance
that he or she will also be a wildlife
watcher. Or, put another way, only about
4 in 10 sportspersons will not participate
in any wildlife watching.
Despite the interrelationship, the two
groups are sometimes considered or
treated as separate and distinct by
professionals involved with wildlife
recreation from a management,
marketing, advocacy, or academic
perspective. The notion of separate and
distinctive groups of recreationists is
due in part to the existence of interest
groups who represent each group nearly
exclusively. These interest groups
sometimes have divergent opinions
about resource management objectives;
and, when conflict arises, both sides can
become emphatically opposed to one
another.
To be sure, besides their sometimes
differing resource management
objectives, there are other important
differences between the two groups.
For example, there are some notable
differences in their socioeconomic
characteristics. The proportion of
the U.S. population who participates
in wildlife watching tends to go up
with age, whereas the proportion who
participates in sporting activities,
i.e., hunting or fishing, tends to go
down. When considered in conjunction
with information about ongoing
demographic changes in the U.S., these
socioeconomic characteristics have
important implications about recreation
participation in the future.
This report seeks to broaden the
understanding of the interrelationship
between consumptive and non-consumptive
recreationists through
the following objectives. Analyze
sportspersons participation in wildlife
watching. In other words, segment
total wildlife-watching participants
by sportsperson classification i.e.,
whether they also participated in
hunting and fishing. After segmenting
wildlife-watching participants by
Figure 1. Wildlife-Related Recreationists, by Type of Activity: 2001
(Population 16 years of age and older.)
Note: Sportspersons are hunters and anglers. Wildlife watchers are observers, photographers, and
feeders of wildlife.
��
����
4 The Relationship between Wildlife Watchers, Hunters, and Anglers
sportsperson classification, compare
the types of wildlife-watching activities
enjoyed by both groups. Compare the
socioeconomic characteristics of the
three different groups of recreationists
shown in Figure 1: wildlife watchers
exclusively, sportspersons exclusively,
and those who are both sportspersons
and wildlife watchers. The socioeconomic
characteristics compared include
population size of residence, geographic
region of residence, age, sex, ethnicity,
race, income, and education. Examine
wildlife-related recreation spending by
the three different groups. Examine
the relationship between historical
hunting/fishing participation and wildlife
watching. Lastly, examine the change
in an individual’s likelihood of wildlife-watching
participation given that he or
she participated in hunting or fishing.
Knowledge obtained through this
analysis could be useful for a variety of
reasons. Differing participation patterns
among the two groups by age and
ethnicity could indicate how aging baby
boomers and increasing urbanization
in the U.S. may affect recreation
participation in the future. Knowledge
of expenditures by the different groups
could give manufacturers a better
understanding of total sales potential for
different types of products. Knowledge
of the relationship between prior
hunting and fishing activity and wildlife
watching may foster greater consensus
about the appropriate stewardship
of resources among interest groups
or give resource managers guidance
in designing resource plans that
are capable of bringing the greatest
satisfaction to all recreationists.
Report Organization
The report is organized into five parts:
Part One: The “Wildlife Watching
Participation by Sportsperson
Classification” section examines the size
and geographic dispersion of the wildlife-watching
population by type of activity
and by sportsperson classification.
Estimates of total participation levels
and days of participation are made for
numerous aspects of around-the-home
and away-from-home wildlife watching.
Part Two: The “Socioeconomic
Characteristics” section compares the
characteristics of the three different
groups of recreationists who appear in
Figure 1: wildlife watchers exclusively,
sportspersons exclusively, and those
who are both sportspersons and wildlife
watchers.
Part Three: The “Expenditures by
Type of Recreationist” section provides
a detailed analysis of all wildlife
recreation spending by recreationist
type. Recreationists are treated as either
watchers exclusively, sportspersons
exclusively, or sportspersons and wildlife
watchers.
Part Four: The “Historical Fishing and
Hunting Activity of Wildlife Watchers”
section examines the percent of all
wildlife watchers who have participated
in hunting or fishing in the past.
Part Five: Lastly, in the “Wildlife-
Watching Participation Model” section a
logit regression model is used to examine
the impact that numerous variables have
on the probability that an individual will
participate in wildlife watching.
Data and Definitions
All reported data contained herein
are from the 2001 National Survey
of Fishing, Hunting, and Wildlife-
Associated Recreation (FHWAR).1
Consequently, all participation, dollar
expenditures, and hunting behavior
statistics are representative of 2001.
Additionally, all data represents persons
age 16 years and older.
The exact questions used to identify
wildlife watchers appear in Appendix A;
but, in summary, the following definitions
are applicable.
An away-from-home wildlife watcher is
one who took trips or outings at least one
mile from home for the primary purpose
of observing, photographing, or feeding
wildlife. Trips do not include those to
zoos, circuses, aquariums, museums, nor
those for hunting, fishing, or scouting.
An around-the-home wildlife watcher
is one who participated in one or more
of the following activities within a one
mile radius of home: photographing
any type of wildlife; feeding any type of
wildlife; visiting public parks or publicly
owned natural areas for the purpose of
observing, photographing, or feeding
wildlife; taking a special interest in
wildlife other than simply noticing
wildlife while doing other activities; or
maintaining natural areas or plantings
for the benefit of wildlife.
For the sake of brevity wildlife watchers
are often referred to simply as watchers.
The activity of wildlife watching
is referred to simply as watching.
Sportsperson activities, i.e., hunting
and fishing, are referred to simply as
sporting activities. Recreationists that
do not participate in sporting activities
are referred to as non-sportspersons.
The three recreationist groups shown
in Figure 1 are referred to as follows:
watchers only participate in wildlife
watching only; sportspersons only
participate in sporting activities only;
watchers-sportspersons participate in
both watching and sporting activities.
1 FHWAR documents are available on the
U.S. Fish and Wildlife Service webpage:
http://federalaid.fws.gov/surveys/
surveys.html.
The Relationship between Wildlife Watchers, Hunters, and Anglers 5
Part One–Wildlife-Watching Participation
by Sportsperson Classification
Analysis of wildlife watching by
sportsperson classification reveals the
portion of nonconsumptive recreation
attributable to sportspersons and
differences in the nonconsumptive
recreation activities between
sportspersons and non-sportspersons.
Wildlife Watching Nationally
Table 1 reveals the number of
participants and days of wildlife
watching by type of activity and
sportsperson classification. It reveals
that a substantial portion of all
nonconsumptive recreationists in 2001,
33%, were also sportspersons. The
remaining percentages in column five
can be used to gauge which activities
have a comparatively higher proportion
attributable to sportspersons. For
example, a comparison of row two and
row six reveals that sportspersons
make up a substantially higher share of
participants in away-from-home than
around-the-home wildlife watching.
They make up 44% of away-from-home
watchers and 32% of around-the-home
watchers. Comparisons of percentages
are useful in determining how wildlife
watching activities of sportspersons differ
in emphasis from non-sportspersons.
Table 1 indicates little variation
in sportspersons’ share of wildlife
watching activities within the broader
around-the-home and away-from-home
classifications. The proportion
of sportspersons within all activities
classified as away from home are close to
44%. There is a slight increase in share
for feeding wildlife, 46%, and a slight
decrease in share for photographing,
42%. Interestingly, within the around-the-
home activities, the share of
sportspersons is slightly higher for
photographing wildlife.
Table 1. Wildlife-Watching Participants and Days by Type of Activity and
Sportsperson Classification: 2001
(Population 16 years of age and older. Numbers in thousands.)
All
Non-
Sportspersons
Percent
of All Sportspersons
Percent
of All
Participants
All Wildlife Watching 66,105 44,263 67% 21,842 33%
Away from Home 21,823 12,190 56% 9,633 44%
Observe Wildlife 20,080 11,594 58% 8,487 42%
Photograph Wildlife 9,427 5,423 58% 4,004 43%
Feed Wildlife 7,078 3,798 54% 3,279 46%
Around the Home 62,928 42,766 68% 20,162 32%
Observe Wildlife 42,111 28,385 67% 13,726 33%
Photograph Wildlife 13,937 8,825 63% 5,113 37%
Feed Wildlife 53,988 36,757 68% 17,231 32%
Visit Public Parks or Areas 10,981 7,326 67% 3,655 33%
Maintain Plantings or
Natural Areas
13,073 8,769 67% 4,304 33%
Average Days of Participation
All Wildlife Watching 83 83 84
Away from Home 17 17 18
Observe Wildlife 15 14 16
Photograph Wildlife 8 8 9
Feed Wildlife 15 14 15
Around the Home 81 81 82
Observe Wildlife 123 124 119
Photograph Wildlife 14 14 14
Visit Public Parks or Areas 4 4 5
Total Days
All Wildlife Watching 5,488,866 3,659,767 67% 1,829,099 33%
Away from Home 372,006 201,582 54% 170,425 46%
Observe Wildlife 295,345 162,190 55% 133,155 45%
Photograph Wildlife 76,324 41,436 54% 34,888 46%
Feed Wildlife 103,307 53,043 51% 50,264 49%
Around the Home 5,116,860 3,458,186 68% 1,658,674 32%
Observe Wildlife 5,159,259 3,532,392 69% 1,626,867 32%
Photograph Wildlife 190,120 119,255 63% 70,865 37%
Visit Public Parks or Areas 225,324 141,599 63% 83,725 37%
6 The Relationship between Wildlife Watchers, Hunters, and Anglers
Table 1 also shows the total days and
average days of wildlife watching around
the home and away from home. The total
number of days around the home and
away from home was 5.5 billion, and the
proportion attributable to sportspersons
is identical to that for participants, 33%.
The average days of wildlife watching
of sportspersons and non-sportspersons
are very similar. The average of
sportspersons is one to two days higher
for most types of wildlife watching.
However, it is notably 5 days lower for
observing wildlife around the home.
Table 2 displays the distribution of
away-from-home and around-the-home
watchers by species of wildlife observed.
Sportspersons and non-sportspersons
do have some apparent differences in
species viewed. For around the home,
sportspersons have an appreciably
higher concentration of watchers
who observe fish and other wildlife,
large land mammals, and reptiles or
amphibians. Sportspersons’ shares of
total participation for these species are
45%, 40%, and 39% respectively, which
is higher than their overall around-the-home
share of 32%. Sportspersons also
have a relatively higher than average
share of participants observing large
land mammals and fish away from home,
where their shares of total participants
are 47% and 48% respectively.
Additionally, at 47%, sportspersons
have a higher share of away-from-home
watchers of “Other Birds.”
In summary, whether from a days or total
participants perspective, sportspersons
comprise a substantial portion of wildlife
watching. Further, the information in
Tables 1 and 2 reveals that sportspersons
and non-sportspersons have very slight
differences in the average number of
days across all types of watching, but
there are some apparent differences
in species observed. Sportspersons
have a relatively higher proportion of
participants who observe large land
mammals and fish.
Table 2. Participants in Wildlife Watching by Species and Sportsperson
Classification: 2001
(Population 16 years of age and older. Numbers in thousands.)
All
Non-
Sportspersons
Percent
of All Sportspersons
Percent
of All
Away from Home, Total 21,823 12,190 56% 9,633 44%
Total Birds 18,580 10,987 59% 7,593 41%
Birds of Prey 12,495 7,176 57% 5,319 43%
Waterfowl 14,432 8,477 59% 5,955 41%
Water Birds 10,314 6,089 59% 4,225 41%
Songbirds 12,878 7,633 59% 5,245 41%
Other Birds 7,907 4,211 53% 3,695 47%
Total Land Mammals 15,506 8,612 56% 6,894 45%
Large Land Mammals 12,226 6,485 53% 5,741 47%
Small Land Mammals 12,958 7,500 58% 5,458 42%
Fish 6,330 3,290 52% 3,040 48%
Marine Mammals 3,013 2,016 67% 997 33%
Other Wildlife 9,409 5,604 60% 3,805 40%
Around the Home, Total 62,928 42,766 68% 20,162 32%
Birds 40,306 27,377 68% 12,929 32%
Large Land Mammals 17,481 10,548 60% 6,933 40%
Small Land Mammals 32,747 22,254 68% 10,494 32%
Reptiles or Amphibians 9,773 5,975 61% 3,798 39%
Insects 13,835 9,195 66% 4,640 34%
Fish or Other Wildlife 7,932 4,324 55% 3,609 45%
The Relationship between Wildlife Watchers, Hunters, and Anglers 7
Wildlife Watching by State
Tables 3, 4, and 5 reveal the number of
watchers by sportsperson classification
and state where watching occurred.
Table 3 presents the state distribution of
away-from-home watchers, and Table 4
presents the state distribution of around-the-
home watchers. Table 5 presents
the total recreationists by type shown in
Figure 1: watchers only, sportspersons
only, and watchers-sportspersons.
Generally, the tables reveal a wide
variation in the proportional distribution
of watchers with respect to sportsperson
classification.
Table 3 reveals that the proportional
distribution of away-from-home
watchers between non-sportspersons
and sportspersons varies substantially
by state. At 80% Mississippi has the
highest sportsperson share. Minnesota,
Oklahoma, and Georgia follow with 63%,
59%, and 57% sportspersons. Altogether,
sportspersons account for 50% or more
of away-from-home watchers in 14 states.
States with the least sportsperson
share of away-from-home watchers are
California, Delaware, Connecticut, and
Massachusetts, with 21%, 26%, 26%, and
28% respectively.
Table 3. Away-from-Home Wildlife Watchers by Sportsperson Classification and
State Where Activity Occurred: 2001
(Population 16 years of age and older. Numbers in thousands.)
All Away-from-
home
Non-
Sportspersons
Percent
of All Sportspersons
Percent
of All
AK 292 141 48% 151 52%
AL 276 145 53% 132 47%
AR 211 94 45% 117 55%
AZ 638 446 70% 191 30%
CA 2270 1804 79% 466 21%
CO 838 493 59% 346 41%
CT 279 207 74% 73 26%
DE 96 71 74% 25 26%
FL 1503 889 59% 614 41%
GA 411 178 43% 234 57%
HI 141 88 62% 53 38%
IA 310 141 45% 169 55%
ID 451 277 61% 174 39%
IL 638 347 54% 291 46%
IN 474 262 55% 212 45%
KS 297 147 49% 150 51%
KY 385 192 50% 193 50%
LA 314 151 48% 163 52%
MA 542 388 72% 154 28%
MD 533 315 59% 218 41%
ME 419 261 62% 158 38%
MI 884 479 54% 405 46%
MN 634 233 37% 400 63%
MO 738 357 48% 381 52%
MS 131 ** ** *105 *80%
MT 511 327 64% 184 36%
NC 588 327 56% 261 44%
ND 93 58 62% 35 38%
NE 186 102 55% 84 45%
NH 425 291 68% 134 32%
NJ 688 484 70% 204 30%
NM 387 263 68% 124 32%
NV 309 201 65% 107 35%
NY 1330 860 65% 469 35%
OH 898 529 59% 370 41%
OK 403 166 41% 237 59%
OR 910 625 69% 285 31%
PA 1279 786 61% 493 39%
RI 98 54 55% 44 45%
SC 331 157 47% 174 53%
SD 181 80 44% 101 56%
TN 683 413 60% 270 40%
TX 1002 566 56% 435 44%
UT 530 266 50% 263 50%
VA 772 517 67% 255 33%
VT 307 210 68% 97 32%
WA 1065 700 66% 365 34%
WI 1000 527 53% 473 47%
WV 219 134 61% 85 39%
WY 416 233 56% 182 44%
*Estimate based on small sample size.
**Sample Size too small to report data reliably
8 The Relationship between Wildlife Watchers, Hunters, and Anglers
Table 4 reveals that the distribution of
around-the-home watchers between
non-sportspersons and sportspersons
also varies substantially by state. At 61%
Wyoming has the highest sportsperson
share. Alaska, Utah, and Montana follow
with 56%, 48%, and 48% respectively.
At 15% California has the lowest
sportsperson share for around-the-home
watchers just as it does for away-from-home.
Massachusetts, Nevada, and
Rhode Island all follow with 22%.
Table 4. Around-the-Home Wildlife Watchers by Sportsperson Classification and
State of Residence: 2001
(Population 16 years of age and older. Numbers in thousands.)
All Around-the-
Home
Non-
Sportspersons
Percent
of All Sportspersons
Percent
of All
AK 221 98 44% 123 56%
AL 925 588 64% 337 36%
AR 762 455 60% 308 40%
AZ 1,063 822 77% 241 23%
CA 4,853 4,111 85% 742 15%
CO 1,127 729 65% 398 35%
CT 859 631 73% 228 27%
DE 168 119 71% 48 29%
FL 2,635 1,617 61% 1,017 39%
GA 1,305 781 60% 524 40%
HI 120 71 59% 49 41%
IA 939 601 64% 338 36%
ID 333 196 59% 137 41%
IL 2,379 1,512 64% 866 36%
IN 1,727 1,161 67% 566 33%
KS 718 433 60% 285 40%
KY 1,234 769 62% 466 38%
LA 802 520 65% 282 35%
MA 1,443 1,126 78% 316 22%
MD 1,261 905 72% 357 28%
ME 501 345 69% 156 31%
MI 2,361 1,564 66% 797 34%
MN 1,932 1,024 53% 908 47%
MO 1,514 941 62% 572 38%
MS 576 357 62% 219 38%
MT 341 178 52% 163 48%
NC 1,815 1,321 73% 494 27%
ND 125 66 53% 59 47%
NE 469 301 64% 168 36%
NH 445 319 72% 126 28%
NJ 1,640 1,205 73% 435 27%
NM 449 335 75% 114 25%
NV 300 234 78% 66 22%
NY 3,442 2,528 73% 914 27%
OH 2,653 1,905 72% 748 28%
OK 997 588 59% 409 41%
OR 1,204 838 70% 366 30%
PA 3,371 2,365 70% 1,005 30%
RI 237 184 78% 53 22%
SC 1,045 652 62% 393 38%
SD 241 140 58% 101 42%
TN 1,655 1,134 69% 520 31%
TX 2,930 1,835 63% 1,095 37%
UT 515 267 52% 248 48%
VA 2,105 1,484 71% 620 29%
VT 280 181 65% 99 35%
WA 2,105 1,452 69% 653 31%
WI 2,076 1,310 63% 766 37%
WV 492 345 70% 147 30%
WY 154 60 39% 93 61%
The Relationship between Wildlife Watchers, Hunters, and Anglers 9
Figure 2 displays a graphical
representation of sportspersons’ share
of away-from-home wildlife watchers
by state.
Figure 3 displays a graphical
representation of the sportsperson
share of around-the-home wildlife
watchers by state.
Table 5 indicates similarly that the share
of recreationists that are watchers-sportspersons
varies dramatically by
state. Those that participate in both
activities ranges from a low of 16%
for California to a high of 47% for
Montana. Other states with notably low
proportions of watchers-sportspersons
are Massachusetts, New Jersey, and
Arizona, which all have less than 20%.
At the other extreme, Minnesota and
Utah both have greater than 41%
watchers-sportspersons.
���
������������
Figure 2. Percent Away-from-Home Wildlife Watchers Who Were also Sportspersons
< 30 percent
30–39 percent
40–49 percent
≥ 50 percent
��
����������
��
Figure 3. Percent Around-the-Home Wildlife Watchers Who Were also Sportspersons
< 25 percent
25–34 percent
35–39 percent
≥ 40 percent
10 The Relationship between Wildlife Watchers, Hunters, and Anglers
Table 5. Participation in Wildlife-Related Recreation by Recreationist Type and State of Residence: 2001
(Population 16 years of age and older. Numbers in thousands.)
All
Recreationists
Watchers
Only
Percent
of All
Sportspersons
Only
Percent
of All
Watchers-
Sportspersons
Percent
of All
AK 320 115 36% 79 25% 126 39%
AL 1,323 597 45% 358 27% 368 28%
AR 1,038 417 40% 260 25% 361 35%
AZ 1,296 859 66% 189 15% 248 19%
CA 6,873 4,387 64% 1,382 20% 1,104 16%
CO 1,518 839 55% 305 20% 374 25%
CT 996 665 67% 113 11% 218 22%
DE 220 126 57% 50 23% 44 20%
FL 3,857 1,699 44% 1,001 26% 1,157 30%
GA 1,932 796 41% 606 31% 530 28%
HI 195 81 42% 69 35% 45 23%
IA 1,212 632 52% 229 19% 351 29%
ID 507 201 40% 119 23% 187 37%
IL 3,148 1,641 52% 656 21% 851 27%
IN 2,179 1,265 58% 393 18% 521 24%
KS 942 451 48% 207 22% 284 30%
KY 1,547 844 55% 283 18% 420 27%
LA 1,326 497 37% 486 37% 343 26%
MA 1,726 1,205 70% 233 13% 288 17%
MD 1,546 975 63% 235 15% 336 22%
ME 607 351 58% 87 14% 169 28%
MI 2,950 1,625 55% 526 18% 799 27%
MN 2,388 951 40% 395 16% 1,042 44%
MO 2,010 934 46% 398 20% 678 34%
MS 851 318 37% 272 32% 261 31%
MT 438 159 36% 76 17% 203 47%
NC 2,330 1,348 58% 446 19% 536 23%
ND 228 58 25% 93 41% 77 34%
NE 623 315 51% 125 20% 183 29%
NH 506 331 65% 56 11% 119 24%
NJ 1,993 1,324 66% 299 15% 370 19%
NM 595 339 57% 124 21% 132 22%
NV 439 245 56% 105 24% 89 20%
NY 3,990 2,497 62% 466 12% 1,027 26%
OH 3,407 1,894 55% 639 19% 874 26%
OK 1,308 578 44% 266 20% 464 36%
OR 1,545 934 60% 259 17% 352 23%
PA 4,169 2,521 60% 647 16% 1,001 24%
RI 280 184 66% 38 13% 58 21%
SC 1,375 701 51% 296 22% 378 27%
SD 326 150 46% 75 23% 101 31%
TN 2,109 1,206 57% 403 19% 500 24%
TX 4,515 1,770 39% 1,427 32% 1,318 29%
UT 736 268 37% 164 22% 304 41%
VA 2,535 1,565 62% 367 14% 603 24%
VT 319 194 61% 32 10% 93 29%
WA 2,537 1,605 63% 303 12% 629 25%
WI 2,489 1,348 54% 330 13% 811 33%
WV 694 341 49% 177 26% 176 25%
WY 223 85 38% 51 23% 87 39%
The Relationship between Wildlife Watchers, Hunters, and Anglers 11
This section compares the socioeconomic
characteristics of wildlife watchers and
sportspersons from several perspectives.
The aim is to show how socioeconomic
characteristics of different groups
or sets of recreationists differ from
one another. The comparisons made
in this section can best be explained
through the use of Figure 1. First,
the socioeconomic characteristics of
the set of all wildlife watchers are
compared to the characteristics of the
set of all sportspersons. In Figure 1
the group of recreationists in areas
A and C are compared to the group
of recreationists in C and B. This is a
simplistic comparison that ignores the
overlap or intersection of the two groups.
Second, the characteristics of those who
are watchers-sportspersons, area C, are
compared to those who are watchers
only, area B, and sportspersons only,
area A. The socioeconomic characteristics
addressed include the following:
population size of residence, Bureau
of Census geographic region, age, sex,
ethnicity, race, household income, and
education.
As will be shown below, an understanding
of the distinctiveness of the different
recreationist groups yields information
about how each will likely be affected
by ongoing demographic trends in the
U.S. such as population urbanization,
increasing average age, and minority
growth.
Comparison of Wildlife Watchers and
Sportspersons
Table 6 summarizes the socioeconomic
characteristics of wildlife watchers and
sportspersons. The first row in Table 6
indicates 31% of all U.S. residents 16 years
of age and older are wildlife watchers,
and 18% are sportspersons. Deviations
from this overall distribution yield
information about how socioeconomic
characteristics of wildlife watchers
differ from sportspersons. This overall
distribution is referred to as an “average.”
The discussion that follows addresses
each of the socioeconomic characteristics
presented in Table 6.
Population Size of Residence
The population size of residence is
measured in terms of metropolitan
statistical area (MSA). “The general
concept of a metropolitan . . . statistical
area is that of a core area containing a
substantial population nucleus, together
with adjacent communities having a high
degree of economic and social integration
with that core . . . Each metropolitan
statistical area must have at least
one urbanized area of 50,000 or more
inhabitants.”
Consequently, classification by MSA type
provides information on the population of
recreationist residences. The categories
of MSA listed in Table 6 indicate whether
the recreationist lived in a MSA of
various sizes or lived outside of a MSA,
which indicates a more rural residency.
The table indicates that the percent of the
population who participates (participation
rate) falls for both wildlife watching and
sporting activities as the population size
of residence rises. The participation rate
in wildlife watching falls from 41% for
those residing outside MSAs to 29% for
those residing inside MSAs. Similarly, the
participation rate in sporting activities
falls from 27% for those residing outside
MSAs to 16% for those residing inside
MSAs. Moreover, the rate also tends to
fall as the size of MSA increases.
When considering the change in the
participation rate between recreationists
residing outside MSAs and those inside
MSAs, it is important to note that the
proportional decrease is greater for
sporting activities. The participation rate
for sporting activities falls from 27% to
16%, which represents a proportional
change of -43%, compared to a -29%
change in wildlife watching.
Census Geographic Regions
The participation rate of both wildlife
watchers and sportspersons varies
substantially by geographic region.
The participation rate for both groups
is highest in the West North Central
region with rates of 43% and 29%
respectively. The lowest participation
rate for watching occurs in the West
South Central with 25%. The Middle
Atlantic and Pacific tie for the lowest
Part Two–Socioeconomic Characteristics
12 The Relationship between Wildlife Watchers, Hunters, and Anglers
Table 6. Selected Characteristics of Wildlife Watchers and Sportspersons: 2001
(Population 16 years of age and older. Numbers in thousands.)
U.S.
Population
Wildlife
Watchers
Percent of
Population Sportspersons
Percent of
Population
Total All Persons 212,298 66,105 31% 37,805 18%
Population Size of Residence
Metropolitan statistical area (MSA) 171,147 49,414 29% 26,564 16%
1,000,000 or more 112,984 29,724 26% 14,739 13%
250,000 to 999,999 41,469 12,880 31% 7,638 18%
50,000 to 249,999 16,693 6,811 41% 4,186 25%
Outside MSA 41,151 16,691 41% 11,241 27%
Census Geographic Region
New England 10,575 3,875 37% 1,504 14%
Middle Atlantic 29,806 8,740 29% 3,810 13%
East North Central 34,082 11,631 34% 6,400 19%
West North Central 14,430 6,206 43% 4,239 29%
South Atlantic 39,286 11,395 29% 6,957 18%
East South Central 12,976 4,514 35% 2,865 22%
West South Central 23,337 5,747 25% 4,924 21%
Mountain 13,308 4,619 35% 2,757 21%
Pacific 34,498 9,377 27% 4,349 13%
Age
16-17 7,709 1,678 22% 1,497 19%
18-24 22,234 3,051 14% 3,303 15%
25-34 35,333 8,869 25% 7,136 20%
35-44 44,057 14,939 34% 9,966 23%
45-54 40,541 14,491 36% 7,826 19%
55-64 25,601 10,326 40% 4,629 18%
65+ 36,823 12,752 35% 3,447 9%
Sex
Male 101,916 30,695 30% 28,462 28%
Female 110,381 35,409 32% 9,343 8%
Ethnicity
Hispanic 21,910 2,699 12% 1,743 8%
Non-Hispanic 190,388 63,409 33% 36,063 19%
Race
White 181,129 62,781 35% 35,300 19%
Black 21,708 2,029 9% 1,666 8%
Asian 7,141 654 9% 365 5%
All Others 2,320 641 28% 474 20%
continues
The Relationship between Wildlife Watchers, Hunters, and Anglers 13
percent of sportspersons with 13%. While
the participation rate varies substantially
for both watching and sporting activities,
there is relatively more variation in
sporting participation.
Age
Participation rates for watching and
sporting activities vary substantially with
respect to age. The participation rate for
sporting activities is rather stable by age
categories, except for the recreationists
65 years of age and older. Beyond 64 the
participation rate for sporting activities
declines substantially. However, there
is a positive correlation with the rate of
wildlife watching by age. The percent of
the population who participates climbs
from 22% for those 16-17 to 40% for
those 55-64. It then declines to 35% for
those over 64, but overall the positive
correlation persists.
Sex
The participation rate for watching
and sporting activities also differ
substantially with respect to gender.
The rate of participation in watching is
relatively stable around 31% for both
males and females. However, for sporting
activities the participation rate of males
is substantially higher than that of
females.
Ethnicity
Hispanics have a substantially lower
participation rate than Non-Hispanics
in both wildlife watching and sporting
activities. 12% of Hispanics participate
in watching compared to 33% of Non-
Hispanics. Similarly, 8% of Hispanics
participate in sporting activities
compared to 19% of Non-Hispanics.
Race
The participation rate for both wildlife
watching and sporting activities is
substantially higher for Whites than
Blacks and Asians. While 35% of
Whites are watchers, Blacks and Asians
participate at a 9% rate. Similarly, the
participation rate of Whites in sporting
activities is 19%, while Blacks and
Asians participate at rates of 8% and 5%
respectively.
Annual Household Income
The participation rates of both watching
and sporting activities generally
increase as incomes increase. The rate
for watching climbs from 23% for those
with incomes of under $10,000 to 44% for
those with incomes of $75,000-$99,999.
Similarly, the rate for sporting activities
climbs from 9% for those with incomes
of under $10,000 to 25% for those with
incomes of $50,000-$99,999.
Education
The participation rate for watching
has a positive correlation with years of
education, whereas the participation
rate for sporting activities is positively
correlated over a portion of the range.
The rate for watching climbs from 22%
for those with 11 years of education or
less to 43% for those with 5 or more years
of college. The rate for sporting activities
climbs from 14% for those with 11 years
of education or less to 20% for those with
1-3 years of college, and then falls slightly
to 18% for those with 5 or more years of
college.
Characteristics of Different
Recreationist Groups
Rather than compare all wildlife
watchers with all sportspersons, this
section compares the socioeconomic
characteristics of the three different
groups of recreationists in Figure 1:
watchers only, sportspersons only,
watchers-sportspersons. In other
words it compares the socioeconomic
characteristics of those in regions A,
B, and C in Figure 1. Comparison by
type of recreationist reveals additional
information about how the composition of
wildlife recreationists will likely change
due to demographic shifts.
Table 6. Selected Characteristics of Wildlife Watchers and Sportspersons: 2001 – continued
(Population 16 years of age and older. Numbers in thousands.)
U.S.
Population
Wildlife
Watchers
Percent of
Population Sportspersons
Percent of
Population
Annual Household Income
Under $10,000 10,594 2,387 23% 978 9%
$10-$19,999 15,272 3,837 25% 1,831 12%
$20-$24,999 10,902 2,879 26% 1,659 15%
$25-$29,999 11,217 3,461 31% 2,000 18%
$30-$34,999 11,648 4,069 35% 2,349 20%
$35-$39,999 9,816 3,142 32% 2,186 22%
$40-$49,999 16,896 6,402 38% 4,116 24%
$50-$74,999 31,383 12,359 39% 7,893 25%
$75-$99,999 17,762 7,735 44% 4,413 25%
$100,000 or More 19,202 8,010 42% 4,521 24%
Not Reported 57,606 11,823 21% 5,858 10%
Education
11 years or less 32,820 7,201 22% 4,705 14%
12 years 73,719 21,154 29% 13,039 18%
1-3 years of college 49,491 16,013 32% 9,980 20%
4 years of college 34,803 12,603 36% 5,994 17%
5 years or more of college 21,464 9,133 43% 3,817 18%
14 The Relationship between Wildlife Watchers, Hunters, and Anglers
Table 7. Socioeconomic Characteristics of Different Types of Wildlife-Related Recreationists: 2001
(Population 16 years of age and older. Numbers in thousands.)
All Wildlife
Recreationists
Watchers
Only
Percent
of All
Sportspersons
Only
Percent
of All
Watchers-
Sportspersons
Percent
of All
Total All Persons 82,068 44,263 54% 15,963 20% 21,842 27%
Population Size of Residence
Metropolitan statistical area (MSA) 60,876 34,312 56% 11,462 19% 15,102 25%
1,000,000 or more 36,087 21,348 59% 6,363 18% 8,376 23%
250,000 to 999,999 16,164 8,526 53% 3,284 20% 4,354 27%
50,000 to 249,999 8,625 4,439 51% 1,814 21% 2,372 28%
Outside MSA 21,192 9,951 47% 4,501 21% 6,740 32%
Census Geographic Region
New England 4,428 2,924 66% 553 12% 951 22%
Middle Atlantic 10,133 6,323 62% 1,393 14% 2,417 24%
East North Central 14,129 7,729 55% 2,498 18% 3,903 27%
West North Central 7,717 3,478 45% 1,511 20% 2,728 35%
South Atlantic 14,485 7,528 52% 3,090 21% 3,867 27%
East South Central 5,804 2,939 51% 1,290 22% 1,575 27%
West South Central 8,174 3,250 40% 2,427 30% 2,497 30%
Mountain 5,744 2,987 52% 1,125 20% 1,632 28%
Pacific 11,455 7,106 62% 2,078 18% 2,271 20%
Age
16-17 2,641 1,144 43% 963 37% 534 20%
18-24 4,963 1,660 33% 1,912 39% 1,391 28%
25-34 12,267 5,131 42% 3,398 28% 3,738 30%
35-44 19,033 9,067 48% 4,094 21% 5,873 31%
45-54 17,350 9,524 55% 2,859 16% 4,967 29%
55-64 11,926 7,297 61% 1,600 14% 3,029 25%
65+ 13,888 10,441 75% 1,136 8% 2,311 17%
Sex
Male 43,257 14,795 34% 12,562 29% 15,900 37%
Female 38,810 29,467 76% 3,401 9% 5,942 15%
Ethnicity
Hispanic 3,824 2,081 55% 1,125 29% 619 16%
Non-Hispanic 78,249 42,186 54% 14,840 19% 21,223 27%
Race
White 77,202 41,902 54% 14,421 19% 20,879 27%
Black 3,130 1,464 47% 1,101 35% 565 18%
Asian 882 517 59% 228 26% 137 15%
All Others 855 381 45% 214 25% 260 30%
continues
The Relationship between Wildlife Watchers, Hunters, and Anglers 15
Table 7 summarizes the socioeconomic
characteristics of the different
recreationist groups. The first row
indicates 54% of all recreationists are
watchers only, 19% are sportspersons
only, and 27% are watchers-sportspersons.
As discussed for the tables above,
deviations from these percentages yield
information about how the different types
of recreationists differ from one another.
Population Size of Residence
Table 7 indicates that recreationists who
live outside MSAs are more likely to be
watchers-sportspersons than those who
live inside MSAs. 32% of recreationists
who live outside MSAs are watchers-sportspersons,
which compares to 25% of
those who live inside MSAs. There is also
an apparent negative correlation between
the size of MSA and the proportion of
watchers-sportspersons. The proportion
goes from a low of 23% for MSAs of one
million or more residents to 27% for
MSAs of less than a million.
Census Geographic Regions
The share of watchers-sportspersons
varies dramatically by geographic region.
The highest proportion occurs in the
West North Central Region with 35%.
The West South Central region follows
close behind with 31%. At the other
extreme are the Pacific Region with 20%
and New England with 22%.
If there is some conflict between the
resource management objectives of wildlife
watchers and sportspersons, then potential
conflict could be greater in regions with
a lower share of watchers-sportspersons.
A lower share of watchers-sportspersons
indicates fewer recreationists who desire
a management strategy that provides
for a desirable mix of both activities.
The individuals that participate in both
activities are likely to favor ��middle-of-the
road�� management practices. To be
sure, individuals who participate in both
activities will likely differ in their optimal
“mix” of management practices to satisfy
both interests, but they all will desire
preservation of resource amenities useful
for both. In the West North Central and
West South Central a relatively large
portion of watchers are also sportspersons
and vice versa. Alternatively, in the Pacific
region there is a substantially smaller
intersection in recreation practices. If it is
true that conflict is greater in regions with
a smaller intersection of recreationists, one
implication is that resource managers in
the Pacific region may have a more difficult
task of satisfying the desires of both.
Age
Age has a dramatic impact on the
type of recreation in which individuals
participate. The proportion of all
recreationists who are watchers only
is positively correlated with age. For
recreationists 18-24, only 33% are
watchers only. However, as age increases
this share climbs consistently up to 75%
for those 65 and older. Conversely, those
who participate in only sporting activities
fall from 39% in the 18-24 category to 8%
for those 65 and older.
Sex
37% of males are watchers-sportspersons,
which compares to only 15% of females.
Ethnicity
Hispanics are notably less likely than
Non-Hispanics to participate in watching
and sporting activities. The share of
watchers-sportspersons for Hispanics is
16%, while for Non-Hispanics the share
climbs to 27%.
Race
The results for race indicate some
noteworthy differences in recreationist
type. For sportspersons only, Whites
participate at notably lower rate
than the other races. Whites also
have a substantially higher share of
watchers-sportspersons. Compared
to the variation in sportspersons only
and watchers-sportspersons there is
relatively little racial variation in the
proportion of recreationists who are
watchers only.
Table 7. Socioeconomic Characteristics of Different Types of Wildlife-Related Recreationists: 2001 – continued
(Population 16 years of age and older. Numbers in thousands.)
All Wildlife
Recreationists
Watchers
Only
Percent
of All
Sportspersons
Only
Percent
of All
Watchers-
Sportspersons
Percent
of All
Annual Household Income
Under $10,000 2,912 1,934 66% 525 18% 453 16%
$10-$19,999 4,749 2,918 62% 912 19% 919 19%
$20-$24,999 3,614 1,955 54% 735 20% 924 26%
$25-$29,999 4,327 2,327 54% 866 20% 1,134 26%
$30-$34,999 5,012 2,663 53% 943 19% 1,406 28%
$35-$39,999 4,120 1,934 47% 978 24% 1,208 29%
$40-$49,999 8,104 3,988 49% 1,702 21% 2,415 30%
$50-$74,999 15,564 7,671 49% 3,205 21% 4,688 30%
$75-$99,999 9,447 5,034 53% 1,712 18% 2,701 29%
$100,000 or More 9,620 5,099 53% 1,610 17% 2,911 30%
Not Reported 14,599 8,741 60% 2,776 19% 3,082 21%
Education
11 years or less 9,712 5,007 51% 2,511 26% 2,194 23%
12 years 26,766 13,727 51% 5,612 21% 7,427 28%
1-3 years of college 19,926 9,946 50% 3,913 20% 6,067 30%
4 years of college 14,986 8,992 60% 2,383 16% 3,611 24%
5 years or more of college 10,406 6,589 63% 1,273 12% 2,544 24%
16 The Relationship between Wildlife Watchers, Hunters, and Anglers
Annual Household Income
There is some variation in the proportion
of recreationists who are watchers-sportspersons
at the very low end of the
income distribution. The lowest income
brackets have a notably lower share.
Those with incomes of less than $10,000
and $10,000-$19,999 have shares of 16%
and 19% respectively. This percent climbs
sharply for those with incomes of $20,000
or more.
Education
There is some variation in recreationist
type by years of education. The share of
watchers only increases sharply for those
with 4 years of college or more. Their
share climbs from around 50% for those
with less than 4 years of college to around
61% for those with more.
Implication of Demographic
Change on Wildlife Recreation
Under certain conditions, the
socioeconomic information discussed
above can be used to gauge the likely
effect of ongoing demographic trends
on participation in the different
types of wildlife recreation. If certain
assumptions hold, current demographic
trends have implications on the future
participation rate of individuals in
wildlife watching and sporting activities.
They also have implications about the
proportion of all recreationists who will
likely participate in both watching and
sporting activities.
Major Demographic Trends in the U.S.
There are several demographic trends in
the U.S. that will likely impact wildlife-related
recreation in the years ahead.
It is beyond the scope of this report to
analyze each trend in detail, but a short
summary is warranted.
The percent of the U.S. population living
in rural housing continues to fall. In 1960
approximately 30% of U.S. residents
lived in rural areas. This percent has
since fallen to 27% in 1970, 25% in 1995,
and 22% in 2000.2
The percent of the U.S. population of
Hispanic ethnicity is on the rise. In 1980,
6.4% of U.S. residents were Hispanic.
This percent has since risen to 9.0% in
1990 and 12.0% in 2000. It is expected to
rise to 14.6% by 2010.3
The percent of the population who are
of White and not of Hispanic origin
is declining. In 1980, 79.6% of U.S.
residents were White and not Hispanic,
and this has since fallen to 75.6% in
1990 and 69.5% in 2000. This percent is
expected to fall further to 67.3% by 20103.
Finally, there is the trend of an aging
population in the U.S., due to maturing
baby boomers. In 1990 the percent of
the population over 55 years of age was
20.9%. This percent rose to 21.1% in
2000 and 22.6% in 2005. This percent is
expected to continue climbing to 24.7% in
2010 and 28.9% in 20203.
Impact on Wildlife Watching and
Sporting Activities
Under the assumption of relative stability
in the participation percentages in Table
6 for population size of residence and
age, the demographic trends discussed
above provide some indication of how
the overall participation rate for wildlife
watching will change relative to that
of sporting activities. The assumption
of relative stability in the participation
percentages is best explained using an
example. Table 6 indicates that 35%
of the U.S. population 65 and over
participates in wildlife watching, 40% of
those between 55-64 participate, and 36%
of those between 45-54 participate. The
assumption is that these percentages
will not change, or if they do change,
they will change only slightly. This is
an important assumption to keep in
mind in the following discussion. There
may be reason to believe that this
assumption will not hold. For example,
Table 6 indicates that 9% of those 65 and
over participate in sporting activities.
However, advances in medical care and
nutrition continue to improve the health
of older Americans. Consequently, it is
possible that in the future a greater share
of people 65 and older will participate in
sporting activities.
If there are relatively stable participation
rates for population size of residence and
age, current demographic trends imply
that the overall participation rate for
wildlife watching will increase relative
to sporting activities. As discussed
above, the decline in participation
that occurs because individuals reside
inside an MSA as opposed to outside
is greater for sporting activities than
for wildlife watching. The implication
is that increased urbanization will have
a relatively greater impact on sporting
activities than on wildlife watching.
Additionally, the wildlife watching
participation rate is positively correlated
with age, and the participation rate
for sporting activities is negatively
correlated with age. Consequently, the
continued aging of the U.S. population
likely portends growth in wildlife
watching relative to hunting and fishing.
Impact on Share of Recreationists that
Participate in Both Wildlife Watching
and Sporting Activities
Current demographic trends also imply
that the share of recreationists who
participate in both wildlife watching and
sporting activities will likely decline. This
conclusion is based on an assessment of
how trends will affect those recreationists
that are represented in the “Watchers-
Sportspersons” column of Table 7, and
it could have important political and
resource management implications.
Essentially, changes in the share of
recreationists that participate in both
wildlife watching and sporting activities
indicate whether the population of
recreationists will become increasingly
united or divided. A smaller share of
participants in both activities indicates
that the composition of wildlife
recreationists will become increasingly
divided.
All of the demographic trends discussed
above portend increasing division of
wildlife recreationists. Table 7 indicates
that the proportion of those who are
both watchers-sportspersons falls as
age increases. Consequently, the aging
population of baby boomers suggests
that the share of all recreationists that
participate in both watching and sporting
activities will likely decline in the future.
Table 7 also indicates that the share
of watchers-sportspersons falls as the
population size of residence increases,
and the ongoing demographic trend is
one of increased urbanization. Hispanics
are substantially less likely to participate
in both watching and sporting activities
than Non-Hispanics, and the Hispanic
population is rapidly increasing. Lastly,
Whites are more likely to participate in
both types of recreation than all other
races taken together, and the White
population is growing slower than others.
2 “Factors Related to Hunting and Fishing
Participation Among the Nation’s Youth,”
Responsive Management (2003).
3 “Statistical Abstract of the United States
2004-2005,” U.S. Census Bureau.
The Relationship between Wildlife Watchers, Hunters, and Anglers 17
This section examines wildlife recreation
spending by type of recreationist:
watchers only, sportspersons only, and
watchers-sportspersons. The analysis of
spending by type of recreationist differs
from the conventional analysis by type
of activity. Examining wildlife recreation
spending by type of recreationist reveals
that the majority of spending on wildlife
recreation is made by individuals that
participate in both watching and sporting
activities. This finding helps dispel the
notion that spending is made by two
separate groups of recreationists.
The 2001 FHWAR queried respondents
about their spending attributable to
wildlife recreation, and it distinguished
non-consumptive spending from
consumptive spending. In other words,
it distinguished spending made pursuant
to wildlife watching from that made
pursuant to either hunting or fishing.
In the published data tables of the
2001 FHWAR, these expenditures are
presented in detail. However, publishing
estimates by type of activity alone
conceals the substantial crossover of
recreationists from one type of activity
into the other. In a sense, estimates by
type of activity alone foster an impression
that the two types of recreationists
belong to separate cliques or factions.
However, the analysis presented above
indicates that this is clearly not the case,
as substantial crossover does occur.
Although not presented in the published
tables, data available from the 2001
FHWAR CD can be used to analyze
spending from numerous other
perspectives. Total wildlife-watching
expenditures can be apportioned between
sportspersons and non-sportspersons.
Total hunting and fishing spending
can be apportioned between those who
participate in wildlife watching and those
who do not. Average expenditures of
sportspersons who are wildlife watchers
can be calculated and compared to those
who are not. Average expenditures of
wildlife watchers who are sportspersons
can be calculated and compared to those
who are not. Total wildlife recreation
spending can be apportioned between
recreationists of different types. Table
8 and tables in Appendix D address
wildlife-recreation spending in every
perspective listed here. However,
this discussion is focused on the last
perspective, as it is the most instructive
in highlighting the interrelationship of
the different types of recreationists.
Figure 4 displays total wildlife-related
recreation spending in two ways. The
graph on the top displays spending by
type of activity. It indicates that 65%
of all wildlife recreation spending is
made pursuant to hunting or fishing
and 35% to wildlife watching. This is
the historical method in which spending
has been displayed. The graph on the
bottom displays spending by type
of recreationist. It indicates that
the majority of spending on wildlife
recreation is done by persons who
participate in both wildlife watching and
sporting activities. 57% of all recreation
expenditures are made by recreationists
in both “camps.” Expenditures made by
recreationists who participate in only
sporting activities or wildlife watching
are nearly equal and respectively
comprise 20% and 23% of all spending.
From this perspective, it is clear that the
majority of recreation spending is not
made by two mutually exclusive groups.
Table 8 presents spending by
recreationist type in greater detail.
Expenditures are categorized by type of
good purchased. “Hunting equipment”
includes purchases of rifles, ammunition,
and hunting dogs. “Fishing equipment”
includes purchases of rods, reels, tackle
boxes, and lures. “Auxiliary hunting and
fishing equipment” includes spending
made pursuant to either hunting or
fishing such as camping equipment,
clothing, and taxidermy costs. Wildlife-watching
equipment includes binoculars,
photographic equipment, film, bird food,
bird houses, etc. “Auxiliary wildlife-watching
equipment” is similar to
auxiliary hunting and fishing equipment
and includes camping equipment, tents,
Part Three–Expenditures by Type of Recreationist
USFWS/Debbie McCrensky
18 The Relationship between Wildlife Watchers, Hunters, and Anglers
tarps, and backpacking equipment, but
the primary intended use of these items
was to support wildlife-watching activity,
not hunting or fishing. Special equipment
includes purchases of big ticket items
such as boats, campers, trucks, and
cabins that are primarily purchased for
use in wildlife-related recreation.
For trip-related expenditures, 60% is
attributable to watchers-sportspersons,
24% is attributable to sportspersons
only, and 16% is attributable to watchers
only. The relatively lower share for
watchers only is due to substantially
lower spending on “Other trip costs.”
Watchers only account for 4% of other
trip costs, and in the largest category
of expenditures within other trip costs,
boating costs, they account for only 1%.
The only category within other trip costs
where watchers only account for a higher
than average proportion of spending is
public land use fees, where their share
is 25%. This likely results from their
relatively high use of public parks that
charge admission fees.
Two-thirds of all spending on fishing
equipment and more than two-thirds of
all spending on hunting equipment is
attributable to watchers-sportspersons.
This is a potentially valuable piece of
information for manufacturers of hunting
and fishing equipment.
Almost two-thirds of wildlife-watching
equipment is attributable to watchers
only. This is generally in line with
the proportion of wildlife-watching
participants that do not participate
in sporting activities, which is seen in
Table 1.
In summary, there are items where
the proportional distribution of
wildlife recreation expenditures
differs from the 23%, 20%, and 57%
for all items presented in Figure 4.
Nevertheless, there is not one type
of good where spending from only
one of the recreationist categories
dominates all spending. Spending for
every good is attributable to more than
one recreationist classification, which
underscores the interrelationship that
recreationists have in the marketplace.
Figure 4. Expenditures for Wildlife-Related Recreation
(Total expenditures $108 billion.)
������
������
����
��������
��
���
The Relationship between Wildlife Watchers, Hunters, and Anglers 19
Table 8. Expenditures for all Wildlife-Related Recreation by Recreationist Type: 2001
(Population 16 years of age and older. Numbers in thousands of dollars.)
All
Watchers
Only
Percent
of All
Sportspersons
Only
Percent
of All
Watchers-
Sportspersons
Percent
of All
Total, All Items 108,390,816 24,481,139 23% 22,153,608 20% 61,756,074 57%
Trip-Related Expenditures
Total trip-related 28,070,831 4,520,120 16% 6,755,896 24% 16,794,814 60%
Food and lodging, total 13,149,781 2,770,299 21% 2,843,705 22% 7,535,778 57%
Food 8,957,513 1,535,602 17% 2,094,846 23% 5,327,066 60%
Lodging 4,192,268 1,234,697 29% 748,859 18% 2,208,712 53%
Transportation, total 7,900,619 1,502,425 19% 1,679,980 21% 4,718,215 60%
Public 1,288,653 531,225 41% 201,928 16% 555,501 43%
Private 6,611,965 971,200 15% 1,478,052 22% 4,162,713 63%
Other trip costs, total 7,020,431 247,396 3% 2,232,212 32% 4,540,822 65%
Guide fees, pack trip or package fees 1,177,171 50,917 4% 338,945 29% 787,309 67%
Public land use fees 289,585 73,192 25% 63,950 22% 152,443 53%
Private land use fees 514,249 13,428 3% 133,710 26% 367,111 71%
Equipment rental 395,107 57,196 14% 104,546 27% 233,366 59%
Boating costs 3,042,802 38,025 1% 974,448 32% 2,030,328 67%
Heating and cooking fuel 205,249 14,638 7% 60,842 30% 129,769 63%
Bait 1,105,350 N.A. N.A. 444,396 40% 660,954 60%
Ice 290,917 N.A. N.A. 111,376 38% 179,541 62%
Equipment and Other Expenses
Total 80,319,985 19,961,019 25% 15,397,711 19% 44,961,260 56%
Hunting equipment 4,866,399 N.A. N.A. 1,437,191 30% 3,429,207 70%
Fishing equipment 4,640,715 N.A. N.A. 1,592,844 34% 3,047,872 66%
Auxiliary hunting and fishing equipment 2,627,686 N.A. N.A. 684,658 26% 1,943,028 74%
Wildlife-watching equipment 7,353,977 4,564,821 62% N.A. N.A. 2,789,158 38%
Auxiliary wildlife-watching equipment 716,899 319,264 45% N.A. N.A. 397,637 55%
Special equipment 44,288,116 10,446,204 23% 9,564,151 22% 24,277,764 55%
Magazines, books 639,936 177,021 28% 74,500 11% 388,415 61%
Land leasing and ownership 11,889,496 3,325,727 28% 1,536,556 13% 7,027,213 59%
Membership dues and contributions 1,435,465 674,276 47% 109,741 8% 651,448 45%
Plantings 699,309 453,706 65% N.A. N.A. 245,602 35%
Licenses, stamps, tags, and permits 1,161,988 N.A. N.A. 398,072 34% 763,915 66%
(Z) less than 0.5%.
N.A. Not Applicable
Note: “Hunting equipment” includes purchases of rifles, ammunition, and hunting dogs. “Fishing equipment” includes purchases of rods, reels, tackle boxes,
and lures. “Auxiliary hunting and fishing equipment” includes spending made pursuant to either hunting or fishing such as camping equipment, clothing,
and taxidermy costs. Wildlife-watching equipment includes binoculars, photographic equipment, film, bird food, bird houses, etc. “Auxiliary wildlife-watching
equipment” is similar to auxiliary hunting and fishing equipment and includes camping equipment, tents, tarps, and backpacking equipment, but the primary
intended use of these items was to support wildlife-watching activity, not hunting or fishing. Special equipment includes purchases of big ticket items such as
boats, campers, trucks, and cabins that are primarily purchased for use in wildlife-related recreation
20 The Relationship between Wildlife Watchers, Hunters, and Anglers
Heretofore, this analysis has shown
that there are numerous wildlife
recreationists who participate in both
wildlife watching and hunting or fishing
in the same year: a third of all watchers
in 2001 participated in sporting activities,
and more than half of all sportspersons
in 2001 participated in wildlife watching.
Consequently, the notion of two mutually
exclusive groups of recreationists is
not tenable, and it is more difficult to
distinguish two groups of recreationists
than one might suppose.
The distinctiveness of two separate
groups is even more obscure when
recreation activity is considered for more
than the span of one year. If someone did
not participate in hunting or fishing in
2001, but did in prior years, should he or
she still be considered a sportsperson?
If so, how many years of inactivity in
hunting or fishing must pass before one
is no longer considered a sportsperson?
These are certainly subjective questions
that elicit different responses. Some
may consider a recreationist a viable
sportsperson if he or she participated in
hunting or fishing within the last three
years; whereas, others may consider
participation within the last five years
to be sufficient. Fortunately, data from
the 2001 screen phase of the FHWAR
can be used to satisfactorily answer this
question from different perspectives.
The 2001 FHWAR was conducted in two
phases by the U.S. Census Bureau. The
first was the screen phase in which the
Census Bureau interviewed a sample
of 80,000 households nationwide to
determine who in the household had
fished, hunted, or engaged in wildlife-watching
activities in years 2000 and
before, and who planned to engage in
those activities in 2001. In most cases,
one adult household member provided
information for all household members.
The second was the detailed interview
phase in which those selected as likely
anglers, hunters, and wildlife watchers
from the screen were given detailed
interviews about their recreation
activities in 2001. Heretofore, all the
data discussed in this analysis was from
the detailed interview phase because
it provides the most information about
recreationist activities in 2001. The screen
data could not have been used because
respondents answer only a limited set
of questions about prior activity and
expected future activity, and it has a
longer recall period, so it is more prone to
suffer from recall bias. However, because
the screen does query respondents about
sporting activities for years prior to
2000, it is uniquely suited to analyze the
relationship between wildlife watching in
2000 and prior sporting activities.
Figures 5 and 6 display the distribution
of away-from-home and around-the-home
watchers based on prior sporting
activities. The distributions presented
rely on only that portion of the screen
sample that answered questions about
his or her own activities. All observations
where the survey respondent was
queried about the activity of another
household member were excluded for
reliability considerations. Lastly, those
who are considered watchers in each
figure indicated that they participated in
wildlife watching in the year 2000.
Figure 5 indicates that the proportion
of all away-from-home watchers who
are also sportspersons is substantially
greater than the 44% previously indicated
in Table 1 if historical sporting activities
are considered valid criteria for one’s
inclusion into the set of all sportspersons.
It indicates that within two years prior to
the time of the survey, 57% of all away-from-
home watchers hunted or fished.
More than half of all respondents who
indicated that they had participated in
away-from-home wildlife watching in
2000 also participated in either hunting
Part Four–Historical Fishing and Hunting
Participation of Wildlife Watchers
The Relationship between Wildlife Watchers, Hunters, and Anglers 21
or fishing from 1998 to 2000. The
proportion of away-from-home watchers
who participated in hunting or fishing
within 5 years of the time of the survey
goes up to 63%. Lastly, and perhaps most
surprising, Figure 5 indicates that 80% of
away-from-home watchers have hunted
or fished at some point.
Similarly, Figure 6 indicates that
the proportion of all around-the-home
watchers who are considered
sportspersons is substantially greater
than the 32% previously indicated in
Table 1 if historical sporting activities
are considered valid criteria for one’s
inclusion into the set of all sportspersons.
It indicates that within the two years
prior to the time of the survey, 44% of all
around-the-home watchers either hunted
or fished. The proportion of around-the-
home watchers who participated in
hunting or fishing within 5 years of the
time of the survey goes up to 49%. Lastly,
Figure 6 indicates that 72% of around-the-
home watchers have hunted or fished
at some point.
Given the findings here that more
than 60% of away-from-home and 49%
of around-the-home watchers have
participated in either hunting or fishing
within 5 years from the time of the
survey, this analysis supports the notion
that it is more difficult to distinguish
two separate groups of recreationists if
respondents’ prior sporting activities are
taken into account. It underscores just
how interrelated the different types of
wildlife recreationists really are.
Figure 6. Distribution of Around-the-Home Wildlife Watchers by
Hunting and Fishing Activity
Figure 5. Distribution of Away-from-Home Wildlife Watchers by
Hunting and Fishing Activity
��
���������
����
��
���
����
����
���
������������
22 The Relationship between Wildlife Watchers, Hunters, and Anglers
Figures 5 and 6 indicate that the
majority of both around-the-home and
away-from-home wildlife watchers have
participated in sporting activities at some
point. However, these tables alone do not
assess the increase in the probability that
someone will be a wildlife watcher given
he or she has hunted or fished in the past.
This section presents a wildlife-watching
regression model to estimate this effect.
To appropriately assess the increase
in probability that someone will be a
wildlife watcher if he or she has hunted
in the past, the regression model should
also include several other variables
that are significantly correlated with
wildlife-watching participation. Table 6
indicates that there are numerous other
variables that are likely correlated with
wildlife watching. The participation
rate appears to vary with respect to all
the variables that appear in Table 6:
population size and geographic region of
residence, age, gender, ethnicity, race,
income, and education. Logit regression
is an appropriate method to assess the
change in the probability in watching
participation attributable to all of
these variables. Logit regression helps
eliminate the confounding effects of cross
correlation among these variables. For
example, the participation rate increases
as income increases and as age increases.
However, income also tends to increase
with age. This cross correlation acts to
conceal the independent impact that age
and income have on participation. By
using regression, the effect of each on
the probability of wildlife watching can
be isolated more effectively. Additionally,
regression permits assessment of
whether the correlations of the different
variables with wildlife watching are
significant. In other words it permits
an assessment of the probability that
the observed relationship occurred by
chance.
The logit regression used here models
the logarithm of the odds ratio that
an individual participated in wildlife
watching in 2000 as a function of a set
of explanatory variables or hunter
characteristics. All wildlife watching,
both around-the-home and away-from-home,
is grouped together in this model.4
The logit regression is described by the
following two equations.
(1)
(2)
where:
Pi = Probability that the ith individual
wildlife watched in 2000 (i.e., “yes”)
Xi = Vector of explanatory variables
β = Vector of coefficients to be estimated
Variables
The explanatory variables that are
used in the logit regression model
are contained in Table 9. Many of the
variables are nominal variables. Each
nominal variable used in the logit has a
base or reference case. The reference
case is given a value of 0 in the estimated
equation. Consequently, the calculated
coefficient for the reference case is
embodied in the coefficient for the
intercept term. The reference case for
each nominal variable is given by the
first level for each in Table 9. Thus, the
reference case is as follows:
■ Neither Hunted nor Fished from
1995-2000
■ White race
■ Not Hispanic
■ Male
■ Lives in MSA of more than
one million people
■ More than 5 years of college education
■ Never married or widowed
■ Lives in Pacific or Middle Atlantic or
East North Central regions5
Every variable value other than the
reference case has a coefficient. Each
of these coefficients indicate the change
in the log odds ratio from equation 2
that occurs when the value of the
respective nominal variable is different
than the reference case. For example,
since “Neither Hunted nor Fished from
1995-2000” is the reference case for
HUNT_FISH, each of the other levels
(Both Hunted and Fished, Fished Only,
Hunted Only) will have a coefficient. The
coefficient for “Fished Only” will indicate
the change in the log odds that results
because a wildlife watcher in 2000 went
fishing but not hunting from 1995-2000.
The same will also be the case for the
“Both Hunted and Fished” and “Hunted
Only” coefficients. These results for the
HUNT_FISH variable are the primary
focus of this analysis.
Results
The results from the logistic regression
procedure are presented in Table 10.
A negative number in the Estimation
column indicates that the variable in
question has a negative relationship with
the likelihood that one participated in
wildlife watching in 2000. Additionally,
the Pr > ChiSq column indicates the
probability that the relationship between
each variable and the target variable
(likelihood of wildlife watching) occurs
by chance. A Pr > ChiSq of less than
0.05 is considered strongly statistically
significant, while a value of less than 0.1
is considered significant. An example will
serve to explain the particulars of Table
10. The table indicates that the estimate
for “Fished Only” is 0.975. Since the
base case for HUNT_FISH is “Neither
Hunted nor Fished,” the positive result
indicates that, all other things equal,
individuals that went fishing but not
hunting from 1995-2000 were more likely
to participate in wildlife watching in 2000.
Part Five–Wildlife-Watching Participation Model
4 Independent models for away-from-home
and around-the-home watching were also
estimated by the author, and the results are
available by request.
5 These regions were grouped together
because differences in likelihood of wildlife
watching between them were found
insignificant.
The Relationship between Wildlife Watchers, Hunters, and Anglers 23
Additionally, the Pr > ChiSq indicates a
probability of <.0001, which is strongly
significant. This significance indicates
that there is greater than a 99.99%
probability that the relationship between
“Fished Only” and wildlife watching did
not occur by chance.
The results here confirm the statistical
significance of several of the relationships
that appear in Table 6. All other things
equal, as income increases and as age
increases the likelihood of participation
in wildlife watching also increases. Being
Hispanic indicates lower likelihood of
participation in wildlife watching. The
negative coefficients for all the values
of RACE indicate that each has a lower
likelihood of participation in wildlife
watching than Whites, which is the
reference case value. The reference case
for MSA is metropolitan areas of one
million people or more. Consequently,
the positive coefficients for all the values
of MSAs of less than one million people
indicate that all individuals that reside
in smaller MSAs and outside MSAs are
more likely to participate in wildlife
watching. Moreover, the coefficients for
“50,000-249,999” and “Outside MSA”
are notably larger than that of “250,000-
999,999,” which indicates that those who
reside in the smallest MSAs and outside
MSAs are the most likely to participate in
wildlife watching.6 The positive coefficient
for “Female” indicates that women are
more likely to participate than men.
Those who are either “Divorced” or
“Married” are more likely to participate
than those who have never married or are
widowed. It is possible that those who are
divorced or married are more likely to
participate in wildlife watching because
they are also more likely have children,
and those with children are more likely to
participate in wildlife watching.
Residents of several regions have
significantly lower likelihood of
participation in wildlife watching than the
base case of Pacific, East North Central,
and Middle Atlantic, and residents in only
one region are significantly more likely.
Individuals in the East South Central,
Mountain, South Atlantic, West North
Central, and West South Central are all
6 Linear hypotheses tests on the regression
coefficients indicate that the differences
between ���Outside MSA” and “250,000-
999,999” are significant at the 0.01 level.
Likewise, the differences between “50,000-
249,999” and “250,000-999,999” are also
significant at the 0.01 level.
Table 9. Logit Regression Explanatory Variables
Age Age of recreationist in years for those older than 15
INCOME Ordinal variable with 10 levels, treated as continuous
Under $10,000
$10,000-$19,999
$20,000-$24,999
$25,000-$29,999
$30,000-$34,999
$35,000-$39,999
$40,000-$49,999
$50,000-$74,999
$75,000-$99,999
$100,000 or More
HUNT_FISH Nominal variable with 4 levels that indicate hunting and fishing
activity from 1995-2000
Neither hunted or fished
Both hunted and fished
Fished only
Hunted only
RACE Nominal variable with 3 levels to indicate race
White
Asian
Black
Other
HISPANIC Indicator variable with 2 values to indicate ethnicity
Not Hispanic
Hispanic
SEX Indicator variable with 2 values to indicate respondent gender
Male
Female
MSA Nominal variable with 4 levels to indicate size of residence
1,000,000 or more
250,000-999,999
50,000-249,999
Outside MSA
EDUC Nominal variable with 5 levels to indicate years of education
5 years or more of college
4 years of college
1-3 years of college
12 years
11 Years or less
MARITAL Nominal variable with 3 levels to indicate marital status
Never Married or Widowed
Married or Divorced
CENDIV Nominal variable with 9 levels to indicate geographic
region of residence
Pacific/East North Central/Middle Atlantic
East South Central
Mountain
New England
South Atlantic
West North Central
West South Central
24 The Relationship between Wildlife Watchers, Hunters, and Anglers
significantly less likely to participate in
wildlife watching than those in the Pacific,
East North Central, or Middle Atlantic.
Only individuals in New England are
significantly more likely to participate.
Individuals who participated in
hunting or fishing from 1995-2000
are significantly more likely to have
participated in wildlife watching in 2000
than those who did not. This is indicated
by the positive coefficients for “Hunted
and Fished,” “Fished Only,” and “Hunted
Only.” Moreover, those who both “Hunted
and Fished” have the highest likelihood
of participation in wildlife watching,
followed by those who “Fished Only,”
and then those who “Hunted Only.”7
These results suggests that even after
controlling for other factors that are also
correlated, there is still a statistically
significant increase in likelihood of
wildlife watching participation given
participation in hunting or fishing within
five years prior to the survey.
Calculated Probabilities
The results in Table 10 can be used to
directly calculate the probability that
an individual participated in wildlife
watching in 2000 if appropriate values
of the explanatory variables are known.
To refrain from a discussion about how
to use the results, several tables are
created that exhibit the results of the
regression procedure. Tables 11 and
12 show the probability, expressed as a
percent, that individuals participated in
wildlife watching in 2000. Table 11 shows
the probabilities for individuals who have
never married or are widowed. Table 12
shows the probabilities for individuals
who are either married or divorced.
Each cell in Tables 11-12 contains the
probability that an individual participated
in wildlife watching in 2000. For example,
the first row and first column of Table
11 indicates the following: a White
male who lives in the Pacific region in
a metropolitan statistical area with
greater than one million residents
has a probability of wildlife watching
participation of 33%. If the individual is
otherwise the same, but did participate
in both hunting and fishing within 5 years
prior to 2000, the probability of wildlife
watching rises to 68%. This is displayed
in the second row and first column from
the left in Table 11.
The probabilities are calculated using
the mean value of income, age, and
education. The probabilities shown
will certainly change for individuals
that do not have mean income, age,
and education. The means are used
to convey an understanding of how
7 Linear hypotheses tests indicate that
all pairwise comparisons for differences
between coefficients for “Fish Only,” Hunt
Only,” and “Hunt and Fish” are all significant
at the 0.05 level.
Table 10. Analysis of Maximum Likelihood Estimates of Logit Regression
Variable Value Estimate Standard Error Chi-Square Pr > ChiSq
Intercept -1.558 0.070 490.7 <.0001
AGE 0.018 0.001 614.0 <.0001
INCOME 0.044 0.005 84.5 <.0001
HUNT_FISH Fished Only 0.975 0.027 1285.1 <.0001
HUNT_FISH Hunted Only 0.798 0.078 105.9 <.0001
HUNT_FISH Hunted and Fished 1.439 0.038 1411.6 <.0001
RACE Asian -1.259 0.080 249.7 <.0001
RACE Black -0.989 0.045 476.4 <.0001
RACE Other -0.355 0.089 15.7 <.0001
HISPANIC Hispanic -0.572 0.049 134.8 <.0001
SEX Female 0.432 0.025 309.5 <.0001
MSA 250,000-999,999 0.091 0.032 8.3 0.004
MSA 50,000-249,999 0.291 0.042 49.0 <.0001
MSA Outside MSA 0.260 0.031 72.7 <.0001
EDUC 0-11 years -0.674 0.050 182.3 <.0001
EDUC 1-3 years of college -0.296 0.040 55.8 <.0001
EDUC 12 years -0.582 0.039 218.0 <.0001
EDUC 4 years of college -0.277 0.041 45.1 <.0001
MARITAL Married/Divorced 0.242 0.027 80.1 <.0001
CENDIV East South Central -0.226 0.047 23.0 <.0001
CENDIV Mountain -0.174 0.037 22.4 <.0001
CENDIV New England 0.152 0.037 16.6 <.0001
CENDIV South Atlantic -0.108 0.034 10.0 0.001
CENDIV West North Central -0.112 0.040 7.7 0.005
CENDIV West South Central -0.445 0.050 80.8 <.0001
The Relationship between Wildlife Watchers, Hunters, and Anglers 25
different categorical variables affect
the probability of wildlife watching. The
mean values used in these calculations
are income of $30,000-39,9999, age of 50,
and education of 1-3 years of college.
There is no implication of causality
in the probabilities. In the example
previously mentioned, it was indicated
that the probability that a White male
individual who lives in the Pacific region
in a metropolitan statistical area with
greater than one million residents
has a probability of wildlife watching
participation of 33%, and if he also
participated in hunting and fishing this
probability rises to 68%. It should not be
interpreted that participating in hunting
and fishing causes the probability of
wildlife watching to increase 35%. The
modeling performed here makes use
of what data are available from the
FHWAR screen. The reality is that there
are likely variables excluded from the
modeling that affect both the likelihood
of participation in wildlife watching
and the likelihood of participation in
hunting and fishing. This is referred to
as a confounding variables impact. One
variable that is often discussed as having
a substantial impact on participation
in wildlife recreation is exposure to the
activity at an early age. The real cause of
the high association of non-consumptive
recreation (wildlife watching) and
consumptive recreation (hunting and
fishing) could be childhood exposure
to both types of activities. The data
available do not permit an analysis of this
impact. What is known is that, whatever
the cause, individuals who participate
in hunting and fishing have a higher
probability of participation in wildlife
watching than those who do not.
With these clarifications in mind, there
are several interesting aspects of Tables
11 and 12 that merit some discussion. The
tables clearly indicate that the impact
of urbanization on the probability of
wildlife watching is relatively small when
compared to that of hunting and fishing
activity, race, and sex. The previous
example indicated that the probability
that a White male who lives in the Pacific
region in a MSA with greater than one
million residents has a probability of
wildlife watching participation of 33%.
If the only change is that the individual
resides outside of a MSA, this probability
rises to 39%. All other things equal,
income, sex, marital status, education,
etc., the change in probability resulting
from a change in metropolitan status
alone is relatively small. By comparison,
if the individual is Asian rather than
White, then the probability falls from
33% to 12%. The change in probability
resulting from variation in race is on par
with that of prior hunting and fishing
activity. The largest relative changes
in wildlife watching participation are
observed when race and prior hunting
and fishing activity are varied.
There is relatively little variation in
wildlife watching probability from
changes in geographic region. Lastly,
relatively moderate changes in wildlife
watching probabilities are observed when
gender and marital status are changed.
26 The Relationship between Wildlife Watchers, Hunters, and Anglers
continues
Table 11. Probability of Never Married/Widowed Individuals with Mean Income, Age, and Education Participating in Wildlife Watching in 2000
MSA of 1 million or more MSA of 250,000-999,999 MSA of 50,000-249,999 Outside MSA
Gender Region Hunt/Fish White Asian Black Other White Asian Black Other White Asian Black Other White Asian Black Other
Male
Pac./Mid Atl./East N. Cent. Did not Hunt or Fish 33% 12% 16% 26% 35% 13% 17% 27% 40% 16% 20% 32% 39% 15% 19% 31%
Hunted and Fished 68% 37% 44% 59% 69% 39% 46% 61% 74% 44% 51% 66% 73% 43% 50% 65%
Fished Only 57% 27% 33% 48% 59% 29% 35% 50% 64% 33% 39% 55% 63% 32% 39% 54%
Hunted Only 52% 24% 29% 43% 55% 25% 31% 46% 59% 29% 35% 51% 59% 29% 35% 50%
East South Central Did not Hunt or Fish 28% 10% 13% 22% 30% 11% 14% 23% 34% 13% 16% 27% 34% 13% 16% 26%
Hunted and Fished 62% 32% 38% 54% 64% 34% 40% 56% 69% 39% 45% 61% 68% 38% 44% 60%
Fished Only 51% 23% 28% 42% 53% 24% 30% 44% 58% 28% 34% 49% 57% 28% 33% 49%
Hunted Only 47% 20% 25% 38% 49% 21% 26% 40% 54% 25% 30% 45% 53% 24% 30% 44%
Mountain Did not Hunt or Fish 29% 11% 13% 23% 31% 11% 14% 24% 36% 14% 17% 28% 35% 13% 17% 27%
Hunted and Fished 64% 33% 39% 55% 66% 35% 42% 57% 70% 40% 47% 62% 69% 39% 46% 61%
Fished Only 52% 24% 29% 44% 55% 25% 31% 46% 60% 29% 35% 51% 59% 29% 35% 50%
Hunted Only 48% 21% 26% 39% 50% 22% 27% 41% 55% 26% 31% 46% 54% 25% 31% 46%
New England Did not Hunt or Fish 36% 14% 18% 29% 39% 15% 19% 31% 43% 18% 22% 35% 43% 17% 22% 34%
Hunted and Fished 71% 41% 47% 63% 73% 43% 50% 65% 76% 48% 55% 69% 76% 47% 54% 69%
Fished Only 60% 30% 36% 52% 62% 32% 38% 54% 67% 37% 43% 59% 66% 36% 42% 58%
Hunted Only 56% 27% 32% 47% 58% 28% 34% 49% 63% 33% 39% 54% 62% 32% 38% 54%
South Atlantic Did not Hunt or Fish 31% 11% 14% 24% 33% 12% 15% 25% 37% 14% 18% 29% 36% 14% 18% 29%
Hunted and Fished 65% 35% 41% 57% 67% 37% 43% 59% 71% 41% 48% 64% 71% 41% 47% 63%
Fished Only 54% 25% 30% 45% 56% 27% 32% 47% 61% 31% 37% 52% 60% 30% 36% 52%
Hunted Only 50% 22% 27% 41% 52% 23% 29% 43% 57% 27% 33% 48% 56% 27% 32% 47%
West North Central Did not Hunt or Fish 31% 11% 14% 24% 33% 12% 15% 25% 37% 14% 18% 29% 36% 14% 18% 29%
Hunted and Fished 65% 35% 41% 57% 67% 37% 43% 59% 71% 41% 48% 64% 71% 41% 47% 63%
Fished Only 54% 25% 30% 45% 56% 27% 32% 47% 61% 31% 37% 52% 60% 30% 36% 52%
Hunted Only 49% 22% 27% 41% 52% 23% 29% 43% 57% 27% 33% 48% 56% 27% 32% 47%
West South Central Did not Hunt or Fish 24% 8% 11% 18% 26% 9% 11% 20% 30% 11% 14% 23% 29% 10% 13% 22%
Hunted and Fished 57% 27% 33% 48% 59% 29% 35% 51% 64% 34% 40% 56% 63% 33% 39% 55%
Fished Only 46% 19% 24% 37% 48% 21% 25% 39% 53% 24% 29% 44% 52% 24% 29% 43%
Hunted Only 41% 17% 21% 33% 43% 18% 22% 35% 48% 21% 26% 40% 48% 21% 25% 39%
The Relationship between Wildlife Watchers, Hunters, and Anglers 27
Table 11. Probability of Never Married/Widowed Individuals with Mean Income, Age, and Education Participating in Wildlife Watching in 2000 – continued
MSA of 1 million or more MSA of 250,000-999,999 MSA of 50,000-249,999 Outside MSA
Gender Region Hunt/Fish White Asian Black Other White Asian Black Other White Asian Black Other White Asian Black Other
Female
Pacific Did not Hunt or Fish 43% 18% 22% 35% 45% 19% 24% 37% 50% 22% 27% 42% 50% 22% 27% 41%
Hunted and Fished 76% 48% 54% 69% 78% 50% 57% 71% 81% 55% 61% 75% 81% 54% 61% 74%
Fished Only 67% 36% 43% 59% 69% 38% 45% 61% 73% 43% 50% 65% 72% 43% 49% 65%
Hunted Only 63% 32% 39% 54% 65% 34% 41% 56% 69% 39% 46% 61% 69% 38% 45% 61%
East South Central Did not Hunt or Fish 38% 15% 18% 30% 40% 16% 20% 32% 45% 19% 23% 36% 44% 18% 23% 36%
Hunted and Fished 72% 42% 49% 64% 74% 44% 51% 66% 77% 49% 56% 71% 77% 48% 55% 70%
Fished Only 62% 31% 37% 53% 64% 33% 40% 55% 68% 38% 44% 60% 68% 37% 44% 59%
Hunted Only 57% 28% 33% 49% 60% 29% 35% 51% 64% 34% 40% 56% 64% 33% 39% 55%
Mountain Did not Hunt or Fish 39% 15% 19% 31% 41% 17% 21% 33% 46% 20% 24% 37% 45% 19% 24% 37%
Hunted and Fished 73% 43% 50% 65% 75% 46% 52% 67% 78% 51% 57% 72% 78% 50% 56% 71%
Fished Only 63% 32% 39% 54% 65% 34% 41% 57% 69% 39% 46% 61% 69% 38% 45% 61%
Hunted Only 59% 29% 35% 50% 61% 31% 37% 52% 65% 35% 41% 57% 65% 34% 41% 56%
New England Did not Hunt or Fish 47% 20% 25% 38% 49% 22% 26% 40% 54% 25% 31% 45% 53% 25% 30% 45%
Hunted and Fished 79% 51% 58% 72% 80% 54% 60% 74% 83% 59% 65% 78% 83% 58% 64% 77%
Fished Only 70% 40% 47% 62% 72% 42% 49% 64% 76% 47% 54% 69% 75% 46% 53% 68%
Hunted Only 66% 36% 42% 58% 68% 38% 44% 60% 72% 43% 49% 65% 72% 42% 49% 64%
South Atlantic Did not Hunt or Fish 41% 16% 20% 32% 43% 18% 22% 34% 48% 21% 25% 39% 47% 20% 25% 38%
Hunted and Fished 74% 45% 52% 67% 76% 47% 54% 69% 79% 52% 59% 73% 79% 51% 58% 72%
Fished Only 64% 34% 40% 56% 66% 36% 42% 58% 71% 41% 47% 63% 70% 40% 47% 62%
Hunted Only 60% 30% 36% 51% 62% 32% 38% 54% 67% 37% 43% 59% 66% 36% 42% 58%
West North Central Did not Hunt or Fish 40% 16% 20% 32% 43% 17% 22% 34% 48% 21% 25% 39% 47% 20% 25% 38%
Hunted and Fished 74% 45% 52% 67% 76% 47% 54% 69% 79% 52% 59% 73% 79% 51% 58% 72%
Fished Only 64% 34% 40% 56% 66% 36% 42% 58% 71% 41% 47% 63% 70% 40% 46% 62%
Hunted Only 60% 30% 36% 51% 62% 32% 38% 54% 67% 36% 43% 59% 66% 36% 42% 58%
West South Central Did not Hunt or Fish 33% 12% 15% 25% 35% 13% 17% 27% 39% 16% 19% 31% 39% 15% 19% 31%
Hunted and Fished 67% 37% 43% 59% 69% 39% 46% 61% 73% 44% 51% 66% 73% 43% 50% 65%
Fished Only 56% 27% 32% 47% 59% 29% 34% 50% 63% 33% 39% 55% 63% 32% 38% 54%
Hunted Only 52% 23% 29% 43% 54% 25% 31% 45% 59% 29% 35% 50% 58% 28% 34% 50%
28 The Relationship between Wildlife Watchers, Hunters, and Anglers
continues
Table 12. Probability of Married/Divorced Individuals with Mean Income, Age, and Education Participating in Wildlife Watching in 2000
MSA of 1 million or more MSA of 250,000-999,999 MSA of 50,000-249,999 Outside MSA
Gender Region Hunt/Fish White Asian Black Other White Asian Black Other White Asian Black Other White Asian Black Other
Male
Pac./Mid Atl./East N. Cent. Did not Hunt or Fish 39% 15% 19% 31% 41% 16% 20% 33% 46% 19% 24% 37% 45% 19% 23% 36%
Hunted and Fished 73% 43% 50% 65% 74% 45% 52% 67% 78% 50% 57% 71% 77% 49% 56% 71%
Fished Only 62% 32% 38% 54% 65% 34% 40% 56% 69% 39% 45% 61% 68% 38% 45% 60%
Hunted Only 58% 28% 34% 49% 60% 30% 36% 52% 65% 35% 41% 57% 64% 34% 40% 56%
East South Central Did not Hunt or Fish 33% 12% 16% 26% 35% 13% 17% 28% 40% 16% 20% 32% 39% 16% 19% 31%
Hunted and Fished 68% 37% 44% 60% 70% 40% 46% 62% 74% 45% 51% 66% 73% 44% 50% 66%
Fished Only 57% 27% 33% 48% 59% 29% 35% 50% 64% 34% 40% 55% 63% 33% 39% 55%
Hunted Only 53% 24% 29% 44% 55% 26% 31% 46% 60% 30% 36% 51% 59% 29% 35% 50%
Mountain Did not Hunt or Fish 35% 13% 16% 27% 37% 14% 18% 29% 41% 17% 21% 33% 41% 16% 20% 32%
Hunted and Fished 69% 39% 45% 61% 71% 41% 48% 63% 75% 46% 53% 68% 74% 45% 52% 67%
Fished Only 58% 28% 34% 50% 61% 30% 36% 52% 65% 35% 41% 57% 64% 34% 40% 56%
Hunted Only 54% 25% 30% 45% 56% 27% 32% 47% 61% 31% 37% 52% 60% 30% 36% 52%
New England Did not Hunt or Fish 42% 17% 21% 34% 44% 19% 23% 36% 49% 22% 27% 41% 49% 21% 26% 40%
Hunted and Fished 76% 47% 53% 68% 77% 49% 56% 70% 81% 54% 61% 74% 80% 53% 60% 74%
Fished Only 66% 35% 42% 58% 68% 38% 44% 60% 72% 42% 49% 65% 72% 42% 48% 64%
Hunted Only 62% 32% 38% 53% 64% 34% 40% 55% 68% 38% 45% 60% 68% 37% 44% 60%
South Atlantic Did not Hunt or Fish 36% 14% 17% 28% 38% 15% 19% 30% 43% 18% 22% 35% 42% 17% 21% 34%
Hunted and Fished 70% 40% 47% 63% 72% 42% 49% 65% 76% 47% 54% 69% 76% 47% 53% 68%
Fished Only 60% 30% 36% 51% 62% 32% 38% 53% 67% 36% 43% 58% 66% 35% 42% 58%
Hunted Only 56% 26% 32% 47% 58% 28% 34% 49% 63% 32% 38% 54% 62% 32% 38% 53%
West North Central Did not Hunt or Fish 36% 14% 17% 28% 38% 15% 19% 30% 43% 18% 22% 34% 42% 17% 21% 34%
Hunted and Fished 70% 40% 47% 62% 72% 42% 49% 65% 76% 47% 54% 69% 75% 47% 53% 68%
Fished Only 60% 30% 36% 51% 62% 32% 38% 53% 67% 36% 43% 58% 66% 35% 42% 57%
Hunted Only 55% 26% 32% 47% 58% 28% 34% 49% 63% 32% 38% 54% 62% 31% 38% 53%
West South Central Did not Hunt or Fish 29% 10% 13% 22% 31% 11% 14% 24% 35% 13% 17% 27% 34% 13% 16% 27%
Hunted and Fished 63% 33% 39% 54% 65% 35% 41% 57% 69% 39% 46% 61% 69% 38% 45% 61%
Fished Only 52% 23% 28% 43% 54% 25% 30% 45% 59% 29% 35% 50% 58% 28% 34% 49%
Hunted Only 47% 20% 25% 39% 49% 22% 27% 41% 54% 25% 31% 46% 54% 25% 30% 45%
The Relationship between Wildlife Watchers, Hunters, and Anglers 29
Table 12. Probability of Married/Divorced Individuals with Mean Income, Age, and Education Participating in Wildlife Watching in 2000 – continued
MSA of 1 million or more MSA of 250,000-999,999 MSA of 50,000-249,999 Outside MSA
Gender Region Hunt/Fish White Asian Black Other White Asian Black Other White Asian Black Other White Asian Black Other
Female
Pacific Did not Hunt or Fish 49% 22% 26% 40% 51% 23% 28% 43% 56% 27% 32% 48% 56% 26% 32% 47%
Hunted and Fished 80% 54% 60% 74% 82% 56% 62% 76% 85% 61% 67% 79% 84% 60% 66% 79%
Fished Only 72% 42% 49% 64% 74% 44% 51% 66% 77% 49% 56% 71% 77% 49% 55% 70%
Hunted Only 68% 38% 44% 60% 70% 40% 47% 62% 74% 45% 52% 67% 74% 44% 51% 66%
East South Central Did not Hunt or Fish 44% 18% 22% 35% 46% 19% 24% 37% 51% 23% 28% 42% 50% 22% 27% 41%
Hunted and Fished 76% 48% 55% 70% 78% 50% 57% 71% 81% 55% 62% 75% 81% 54% 61% 75%
Fished Only 67% 37% 43% 59% 69% 39% 45% 61% 73% 44% 50% 66% 73% 43% 50% 65%
Hunted Only 63% 33% 39% 55% 65% 35% 41% 57% 70% 39% 46% 62% 69% 39% 45% 61%
Mountain Did not Hunt or Fish 45% 19% 23% 36% 47% 20% 25% 38% 52% 24% 29% 43% 51% 23% 28% 43%
Hunted and Fished 77% 49% 56% 71% 79% 52% 58% 72% 82% 57% 63% 76% 82% 56% 62% 76%
Fished Only 68% 38% 44% 60% 70% 40% 47% 62% 74% 45% 52% 67% 74% 44% 51% 66%
Hunted Only 64% 34% 40% 56% 66% 36% 42% 58% 71% 41% 47% 63% 70% 40% 47% 62%
New England Did not Hunt or Fish 53% 24% 30% 44% 55% 26% 31% 46% 60% 30% 36% 51% 59% 29% 35% 51%
Hunted and Fished 83% 57% 64% 77% 84% 60% 66% 78% 86% 64% 70% 82% 86% 64% 70% 81%
Fished Only 75% 46% 53% 68% 77% 48% 55% 70% 80% 53% 60% 74% 79% 52% 59% 73%
Hunted Only 71% 42% 48% 64% 73% 44% 50% 66% 77% 49% 55% 70% 76% 48% 55% 69%
South Atlantic Did not Hunt or Fish 46% 20% 24% 38% 49% 21% 26% 40% 54% 25% 30% 45% 53% 24% 30% 44%
Hunted and Fished 79% 51% 58% 72% 80% 53% 60% 74% 83% 58% 65% 77% 83% 57% 64% 77%
Fished Only 70% 40% 46% 62% 72% 42% 48% 64% 75% 47% 53% 68% 75% 46% 53% 68%
Hunted Only 66% 35% 42% 57% 68% 37% 44% 60% 72% 42% 49% 64% 71% 42% 48% 64%
West North Central Did not Hunt or Fish 46% 20% 24% 38% 49% 21% 26% 40% 54% 25% 30% 45% 53% 24% 29% 44%
Hunted and Fished 78% 51% 58% 72% 80% 53% 60% 74% 83% 58% 64% 77% 83% 57% 64% 77%
Fished Only 70% 39% 46% 62% 71% 42% 48% 64% 75% 47% 53% 68% 75% 46% 52% 68%
Hunted Only 66% 35% 42% 57% 68% 37% 44% 60% 72% 42% 49% 64% 71% 41% 48% 64%
West South Central Did not Hunt or Fish 38% 15% 19% 30% 40% 16% 20% 32% 45% 19% 24% 37% 45% 19% 23% 36%
Hunted and Fished 72% 43% 49% 65% 74% 45% 52% 67% 78% 50% 57% 71% 77% 49% 56% 70%
Fished Only 62% 32% 38% 54% 64% 34% 40% 56% 69% 38% 45% 61% 68% 38% 44% 60%
Hunted Only 58% 28% 34% 49% 60% 30% 36% 51% 65% 34% 41% 56% 64% 34% 40% 56%
30 The Relationship between Wildlife Watchers, Hunters, and Anglers
Often the populations of all wildlife
recreationists are divided into
groups of either wildlife watchers or
sportspersons. Sometimes these two
groups of recreationists are perceived as
mutually exclusive or nearly exclusive.
However, they are really interrelated
from numerous perspectives. This
report analyzes several aspects of their
interrelationship.
Perhaps the most tangible evidence
against the notion of two mutually
exclusive groups of recreationists is the
magnitude of their intersection. The
majority of sportspersons also participate
in wildlife watching. Alternatively, 32%
of all around-the-home and 44% of all
away-from-home wildlife watchers are
also sportspersons. Moreover, these
percentages rise substantially if an
individual’s prior historical participation
in sporting activities is considered.
If a recreationist is still considered a
sportsperson if he or she participated in
either hunting or fishing within the last
five years, sportsperson share of around-the-
home and away-from-home watchers
increases to 49% and 63% respectively.
Further, this report uses regression
analysis to show the increase in
the probability of wildlife watching
participation given information on prior
hunting and fishing activity. The results
suggests that even after controlling for
other factors that are also correlated,
there is still a statistically significant
increase in likelihood of wildlife watching
given participation in hunting or fishing
within five years prior to the survey.
Additionally, the probabilities generated
from the regression indicate that,
compared to other variables, there are
relatively large changes in wildlife-watching
participation due to changes in
prior hunting and fishing activity.
From the perspective of spending in the
marketplace and subsequent impact
on the economy, there is substantial
interrelationship between consumptive
and non-consumptive recreationists. This
report shows that the majority of wildlife-recreation
expenditures are made by
those who participate in both wildlife
watching and sporting activities. Those
who participate in both watching and
sporting activities account for 57% of all
spending, while those who participate in
only wildlife watching and only sporting
activities each account for around 21%.
In the years ahead the interrelationship
of consumptive and non-consumptive
recreationists will likely experience
change due to the distinctive
socioeconomic characteristics of each.
Demographic trends in the U.S. portend
several changes in the participation rates
for different types of wildlife recreation.
Relatively fast growth in metropolitan
populations, relatively slow growth in
the population of Whites compared to
other races, rapid population growth
in Hispanics, and an aging populace
will likely have two effects: the overall
participation rate for wildlife watching
will increase relative to sporting
activities, and the share of recreationists
who participate in both wildlife watching
and sporting activities will likely decline.
Summary
The Relationship between Wildlife Watchers, Hunters, and Anglers 31
The analysis for this report is based
on information collected by the 2001
National Survey of Fishing, Hunting,
and Wildlife-Associated Recreation. The
questions used to collect the information
are provided below.
An away-from-home wildlife watcher
is someone who answered yes to the
following question:
“From January 1, 2001 to December
31, 2001 did you take any trips or
outings in the United States of at least
one mile from home for the primary
purpose of observing, photographing,
or feeding wildlife? Do not include
trips to zoos, circuses, aquariums,
museums, or trips for hunting,
fishing, or scouting.”
An around-the-home wildlife watcher is
someone who answered yes to one of the
following questions:
“From January 1, 2001 to December
31, 2001 did you take any special
interest in wildlife around your home
(area within a one-mile radium
of your home), other than simply
noticing wildlife while doing other
activities? By this I mean, did you
closely observe wildlife or try to
identify types of wildlife you did not
know?
“From January 1, 2001 to December
31, 2001 did you photograph any type
of wildlife around your home?”
“From January 1, 2001 to December
31, 2001 did you feed wild birds
around your home?”
“From January 1, 2001 to December
31, 2001 did you feed any kind of fish
or wildlife, other than birds, around
your home?”
“From January 1, 2001 to December
31, 2001 did you visit any public parks
or publicly-owned natural areas
within a one-mile radius of your
home, for the purpose of observing
photographing, or feeding wildlife?”
“During 2001, did you maintain
in the area around your home any
plantings, such as food or cover
plants, for the PRIMARY PURPOSE
of benefiting fish or wildlife? Include
areas in agricultural crops.”
Appendix A. Wildlife-Watching
Questions
32 The Relationship between Wildlife Watchers, Hunters, and Anglers
Appendix B. Wildlife-Watching Days by State
Table B-1. Wildlife-Watching Days Away from Home by Sportsperson Classification and State Where Watching Occurred: 2001
(Population 16 years of age and older. Numbers in thousands.)
All Non-Residential Non-Sportspersons Percent of All Sportspersons Percent of All
AK 3,892 1,693 44% 2,199 57%
AL 3,643 1,708 47% 1,936 53%
AR 1,562 605 39% 957 61%
AZ 4,584 2,705 59% 1,879 41%
CA 23,807 19,455 82% 4,352 18%
CO 9,510 5,119 54% 4,391 46%
CT 7,241 4,448 61% 2,793 39%
DE 722 311 43% 411 57%
FL 21,388 9,026 42% 12,362 58%
GA 4,868 1,172 24% 3,696 76%
HI 1,718 970 57% 748 44%
IA 6,393 2,883 45% 3,511 55%
ID 3,610 2,350 65% 1,260 35%
IL 7,656 5,051 66% 2,605 34%
IN 11,999 5,790 48% 6,209 52%
KS 2,416 1,144 47% 1,272 53%
KY 5,689 3,293 58% 2,396 42%
LA 2,432 679 28% 1,753 72%
MA 10,198 6,670 65% 3,528 35%
MD 6,809 4,049 60% 2,759 41%
ME 4,981 2,749 55% 2,232 45%
MI 13,999 5,525 40% 8,473 61%
MN 13,234 4,600 35% 8,634 65%
MO 12,448 6,451 52% 5,997 48%
MS 3,288 ** ** *3,133 *95%
MT 4,612 2,627 57% 1,984 43%
NC 5,947 3,605 61% 2,342 39%
ND 523 255 49% 268 51%
NE 2,240 1,062 47% 1,177 53%
NH 3,178 2,061 65% 1,117 35%
NJ 9,873 5,987 61% 3,886 39%
NM 6,381 4,607 72% 1,774 28%
NV 1,567 1,032 66% 534 34%
NY 21,583 9,829 46% 11,754 55%
OH 19,814 11,414 58% 8,399 42%
OK 4,058 1,395 34% 2,663 66%
OR 8,517 5,984 70% 2,533 30%
PA 18,990 13,062 69% 5,928 31%
RI 1,414 694 49% 720 51%
SC 4,616 1,006 22% 3,610 78%
SD 1,923 1,082 56% 840 44%
TN 6,144 3,770 61% 2,374 39%
TX 7,711 3,327 43% 4,384 57%
UT 4,414 1,660 38% 2,754 62%
VA 8,906 6,015 68% 2,891 33%
VT 3,717 2,885 78% 832 22%
WA 11,256 7,039 63% 4,218 38%
WI 16,499 6,287 38% 10,212 62%
WV 2,619 851 33% 1,768 68%
WY 3,924 1,972 50% 1,952 50%
*Estimate based on small sample size. **Sample Size too small to report data reliably
The Relationship between Wildlife Watchers, Hunters, and Anglers 33
Table B-2. Wildlife-Watching Days Around the Home by Sportsperson Classification and State of Residence: 2001
(Population 16 years of age and older. Numbers in thousands.)
All Around the Home Non-Sportspersons Percent of All Sportspersons Percent of All
AK 11,921 5,634 47% 6,287 53%
AL 72,899 50,496 69% 22,403 31%
AR 51,652 29,999 58% 21,653 42%
AZ 110,828 89,094 80% 21,735 20%
CA 266,148 224,568 84% 41,580 16%
CO 76,580 57,537 75% 19,043 25%
CT 89,931 67,313 75% 22,617 25%
DE 11,028 8,041 73% 2,987 27%
FL 162,652 115,772 71% 46,880 29%
GA 98,987 53,415 54% 45,572 46%
HI 8,815 3,359 38% *5,456 *62%
IA 115,051 70,870 62% 44,181 38%
ID 22,854 9,801 43% 13,052 57%
IL 193,555 128,307 66% 65,247 34%
IN 206,598 138,179 67% 68,419 33%
KS 49,325 29,595 60% 19,730 40%
KY 70,426 52,967 75% 17,459 25%
LA 67,055 46,042 69% 21,012 31%
MA 127,510 104,150 82% 23,360 18%
MD 81,304 53,650 66% 27,654 34%
ME 51,707 35,316 68% 16,391 32%
MI 192,186 122,855 64% 69,332 36%
MN 128,152 56,471 44% 71,681 56%
MO 101,873 65,326 64% 36,547 36%
MS 52,032 31,211 60% 20,821 40%
MT 41,660 22,376 54% 19,284 46%
NC 112,606 67,630 60% 44,976 40%
ND 8,612 6,447 75% 2,165 25%
NE 37,939 24,544 65% 13,395 35%
NH 34,369 24,909 73% 9,460 28%
NJ 132,869 100,523 76% 32,346 24%
NM 49,236 38,248 78% 10,988 22%
NV 23,894 18,254 76% *5,639 *24%
NY 308,032 215,959 70% 92,073 30%
OH 212,353 139,980 66% 72,372 34%
OK 87,639 51,232 59% 36,407 42%
OR 104,403 77,807 75% 26,596 26%
PA 354,204 235,304 66% 118,901 34%
RI 17,064 13,759 81% 3,305 19%
SC 64,760 40,183 62% 24,577 38%
SD 21,101 14,459 69% 6,642 32%
TN 126,188 88,188 70% 38,000 30%
TX 217,276 125,915 58% 91,362 42%
UT 39,115 18,478 47% 20,638 53%
VA 203,983 132,863 65% 71,120 35%
VT 27,934 20,666 74% 7,267 26%
WA 171,757 119,695 70% 52,062 30%
WI 226,381 157,428 70% 68,953 31%
WV 46,014 33,475 73% 12,539 27%
WY 14,049 7,540 54% 6,509 46%
*Estimate based on small sample size.
34 The Relationship between Wildlife Watchers, Hunters, and Anglers
Appendix C. Selected Characteristics of Wildlife Watchers
Table C-1. Selected Characteristics of Away-from-Home Wildlife Watchers by Sportsperson Classification
(Population 16 years of age and older. Numbers in thousands.)
All Away
from Home
Non-
Sportspersons
Percent
of All Sportspersons
Percent
of All
Total All Persons 21,823 12,190 56% 9,633 44%
Population Size of Residence
Metropolitan statistical area (MSA) 16,536 9,906 60% 6,630 40%
1,000,000 or more 10,126 6,354 63% 3,773 37%
250,000 to 999,999 4,191 2,410 58% 1,781 43%
50,000 to 249,999 2,218 1,142 52% 1,077 49%
Outside MSA 5,287 2,284 43% 3,003 57%
Census Geographic Region
New England 1,155 744 64% 411 36%
Middle Atlantic 2,849 1,731 61% 1,118 39%
East North Central 3,571 1,859 52% 1,712 48%
West North Central 2,059 863 42% 1,196 58%
South Atlantic 3,469 1,849 53% 1,621 47%
East South Central 1,086 556 51% 530 49%
West South Central 1,822 787 43% 1,035 57%
Mountain 2,020 1,135 56% 885 44%
Pacific 3,793 2,667 70% 1,127 30%
Age
16-17 688 366 53% 321 47%
18-24 1,364 657 48% 707 52%
25-34 3,770 1,963 52% 1,806 48%
35-44 5,701 2,964 52% 2,738 48%
45-54 4,991 2,918 59% 2,073 42%
55-64 2,929 1,762 60% 1,167 40%
65+ 2,381 1,560 66% 822 35%
Sex
Male 11,388 4,922 43% 6,466 57%
Female 10,436 7,268 70% 3,167 30%
Ethnicity
Hispanic 890 710 80% 180 20%
Non-Hispanic 20,933 11,480 55% 9,453 45%
Race
White 20,890 11,595 56% 9,295 45%
Black 535 327 61% 209 39%
Asian 178 *153 *86% ** **
All Others *220 *115 *52% *105 *48%
continues
The Relationship between Wildlife Watchers, Hunters, and Anglers 35
Table C-1. Selected Characteristics of Away-from-Home Wildlife Watchers by Sportsperson Classification – continued
(Population 16 years of age and older. Numbers in thousands.)
All Away
from Home
Non-
Sportspersons
Percent
of All Sportspersons
Percent
of All
Annual Household Income
Under $10,000 491 289 59% 202 41%
$10,000-$19,999 867 567 66% 299 35%
$20,000-$24,999 854 515 60% 339 40%
$25,000-$29,999 1,109 625 56% 484 44%
$30,000-$34,999 1,459 752 52% 707 49%
$35,000-$39,999 1,109 543 49% 567 51%
$40,000-$49,999 2,365 1,255 53% 1,110 47%
$50,000-$74,999 4,585 2,449 53% 2,136 47%
$75,000-$99,999 2,910 1,664 57% 1,247 43%
$100,000 or More 2,872 1,705 59% 1,167 41%
Not Reported 3,202 1,825 57% 1,377 43%
Education
11 years or less 1,845 943 51% 901 49%
12 years 5,938 2,891 49% 3,047 51%
1-3 years of college 5,796 2,934 51% 2,861 49%
4 years of college 4,464 2,787 62% 1,678 38%
5 or more years of college 3,781 2,635 70% 1,146 30%
*Estimate based on small sample size.
**Sample Size too small to report data reliably
36 The Relationship between Wildlife Watchers, Hunters, and Anglers
Table C-2. Selected Characteristics of Around-the-Home Wildlife Watchers by Sportsperson Classification
(Population 16 Years of Age and Older. Numbers in Thousands.)
All Around
the Home
Non-
Sportspersons
Percent
of All Sportspersons
Percent
of All
Total All Persons 62,928 42,766 68% 20,162 32%
Population Size of Residence
Metropolitan statistical area (MSA) 46,889 33,274 71% 13,615 29%
1,000,000 or more 28,152 20,634 73% 7,518 27%
250,000 to 999,999 12,210 8,305 68% 3,905 32%
50,000 to 249,999 6,527 4,335 66% 2,192 34%
Outside MSA 16,040 9,492 59% 6,548 41%
Census Geographic Region
New England 3,765 2,787 74% 978 26%
Middle Atlantic 8,452 6,098 72% 2,354 28%
East North Central 11,196 7,452 67% 3,744 33%
West North Central 5,938 3,507 59% 2,432 41%
South Atlantic 10,911 7,286 67% 3,625 33%
East South Central 4,390 2,848 65% 1,542 35%
West South Central 5,490 3,397 62% 2,093 38%
Mountain 4,282 2,821 66% 1,461 34%
Pacific 8,504 6,570 77% 1,933 23%
Age
16-17 1,504 961 64% 543 36%
18-24 2,694 1,626 60% 1,068 40%
25-34 8,137 4,773 59% 3,364 41%
35-44 14,101 8,590 61% 5,511 39%
45-54 13,899 9,603 69% 4,296 31%
55-64 10,084 7,162 71% 2,922 29%
65+ 12,511 10,051 80% 2,460 20%
Sex
Male 28,825 15,367 53% 13,458 47%
Female 34,103 27,399 80% 6,704 20%
Ethnicity
Hispanic 2,486 1,990 80% 495 20%
Non-Hispanic 60,443 40,776 68% 19,667 33%
Race
White 59,877 40,377 67% 19,500 33%
Black 1,939 1,532 79% 407 21%
Asian 593 559 94% ** **
All Others 519 299 58% *220 *42.%
continues
The Relationship between Wildlife Watchers, Hunters, and Anglers 37
Table C-2. Selected Characteristics of Around-the-Home Wildlife Watchers by Sportsperson Classification
(Population 16 Years of Age and Older. Numbers in Thousands.)
All Around
the Home
Non-
Sportspersons
Percent
of All Sportspersons
Percent
of All
Annual Household Income
Under $10,000 2,344 1,842 79% 501 21%
$10-$19,999 3,728 2,973 80% 755 20%
$20-$24,999 2,765 2,061 75% 703 25%
$25-$29,999 3,304 2,245 68% 1,059 32%
$30-$34,999 3,799 2,405 63% 1,394 37%
$35-$39,999 2,950 1,754 60% 1,196 41%
$40-$49,999 6,070 3,892 64% 2,177 36%
$50-$74,999 11,564 7,410 64% 4,154 36%
$75-$99,999 7,349 4,767 65% 2,582 35%
$100,000 or More 7,705 5,061 66% 2,644 34%
Not Reported 11,351 8,354 74% 2,997 26%
Education
11 years or less 6,849 4,796 70% 2,052 30%
12 years 20,255 13,431 66% 6,823 34%
1-3 years of college 15,199 9,717 64% 5,481 36%
4 years of college 11,931 8,651 73% 3,280 28%
5 years or more of college 8,696 6,171 71% 2,525 29%
*Estimate based on small sample size.
**Sample Size too small to report data reliably
38 The Relationship between Wildlife Watchers, Hunters, and Anglers
Appendix D. Expenditures for Wildlife
Watching and Sporting Activities
Table D-1. Wildlife-Watching Expenditures by Sportsperson Classification: 2001
(Population 16 years of age and older. Numbers in thousands except averages.)
All
Non-
Sportspersons
Average Non-
Sportsperson Sportspersons
Average
Sportsperson
Total, all items 38,414,486 24,481,139 735 13,933,352 804
Trip-Related Expenditures
Total trip-related 8,162,439 4,520,120 436 3,642,319 464
Food and lodging, total 4,818,843 2,770,299 318 2,048,544 309
Food 2,835,868 1,535,602 178 1,300,266 196
Lodging 1,982,975 1,234,697 340 748,278 371
Transportation, total 2,595,542 1,502,425 156 1,093,118 147
Public 702,231 531,225 373 171,007 305
Private 1,893,311 971,200 106 922,111 126
Other trip costs, total 748,054 247,396 66 500,657 192
Guide fees, pack trip or package fees 113,034 50,917 60 62,117 174
Public land use fees 114,813 73,192 28 41,621 33
Private land use fees 50,430 13,428 27 37,002 102
Equipment rental 105,198 57,196 75 48,002 122
Boating costs 326,461 38,025 97 288,435 434
Heating and cooking fuel 38,118 14,638 18 23,480 30
Equipment and Other Expenses
Total 30,252,047 19,961,019 649 10,291,033 657
Wildlife-watching equipment, total 7,353,977 4,564,821 150 2,789,158 182
Binoculars, spotting scopes 507,387 305,553 107 201,834 111
Photographic equipment 1,656,755 1,075,910 367 580,845 382
Film and developing 910,423 537,411 63 373,012 75
Commercially prepared bird food 2,034,825 1,363,569 57 671,257 57
Other bulk foods to feed birds 569,867 349,944 42 219,923 49
Feed for other wildlife 503,006 217,753 38 285,253 73
Nest boxes, bird houses, feeders 732,671 469,623 44 263,049 50
Day packs, carrying cases, and special clothing 323,043 173,057 104 149,986 117
Other equipment 116,000 72,001 31 43,999 38
Auxiliary equipment 716,899 319,264 165 397,637 191
Tents, tarps 185,552 70,385 91 115,167 98
Frame packs and backpacking equipment 129,382 56,919 94 72,464 149
Other camping equipment 266,382 111,159 107 155,223 168
Other auxiliary equipment 135,583 80,801 *673 54,783 291
Special equipment 15,468,714 10,446,204 13,531 5,022,512 7,872
Off-the-road vehicle 6,677,688 4,345,544 13,884 2,332,144 10,140
Travel or tent trailer, motor home 6,272,294 4,387,965 17,910 1,884,329 11,216
Boats, boat accessories 996,463 360,152 1,801 636,312 2,419
Cabins ** ** ** ** **
Other Special *572,396 *553,847 *11,077 ** **
Magazines, books 331,955 177,021 36 154,934 46
Land leasing and ownership 4,761,010 3,325,727 10,458 1,435,283 6,056
Membership dues and contributions 920,183 674,276 124 245,907 106
Plantings 699,309 453,706 118 245,602 137
*Estimate based on small sample size.
**Sample Size too small to report data reliably
The Relationship between Wildlife Watchers, Hunters, and Anglers 39
Table D-2. Sporting Expenditures by Wildlife-Watching Classification: 2001
(Population 16 years of age and older. Numbers in thousands except averages.)
All Non-Watchers
Average
Non-Watcher Wildlife Watchers
Average
Wildlife Watcher
Total, all items 69,976,330 22,153,608 1,491 47,822,722 2,270
Trip-Related Expenditures
Total trip-related 19,908,392 6,755,896 492 13,152,495 670
Food and lodging, total 8,330,938 2,843,705 237 5,487,234 315
Food 6,121,645 2,094,846 176 4,026,800 233
Lodging 2,209,293 748,859 277 1,460,434 288
Transportation, total 5,305,077 1,679,980 142 3,625,097 209
Public 586,422 201,928 300 384,494 394
Private 4,718,654 1,478,052 126 3,240,602 189
Other trip costs, total 6,272,377 2,232,212 203 4,040,165 256
Guide fees, pack trip or package fees 1,064,137 338,945 279 725,192 392
Public land use fees 174,772 63,950 43 110,822 43
Private land use fees 463,819 133,710 174 330,109 243
Equipment rental 289,909 104,546 118 185,364 138
Boating costs 2,716,341 974,448 315 1,741,893 324
Heating and cooking fuel 167,131 60,842 38 106,289 33
Bait 1,105,350 444,396 50 660,954 52
Ice 290,917 111,376 22 179,541 24
Equipment and Other Expenses
Total 50,067,938 15,397,711 1,203 34,670,227 1,798
Hunting equipment 4,866,399 1,437,191 396 3,429,207 493
Fishing equipment 4,640,715 1,592,844 195 3,047,872 229
Auxillary equipment 2,627,686 684,658 218 1,943,028 252
Camping equipment 739,967 241,742 205 498,225 160
Binoculars, spotting scopes 296,318 56,952 105 239,366 127
Special fishing and hunting clothing, boots,
foul weather gear
924,554 232,692 127 691,862 153
Other 666,846 153,271 245 513,575 246
Special equipment 28,819,402 9,564,151 7,567 19,255,252 7,174
Off-the-road vehicle 5,734,891 1,863,008 9,362 3,871,882 7,224
Travel or tent trailer, motor home 13,299,315 4,565,675 13,752 8,733,640 13,233
Boats, boat accessories 6,311,427 2,280,173 3,744 4,031,255 2,999
Cabins 3,161,500 ** ** *2,328,988 *31,903
Other Special 312,270 22,784 92 289,486 462
Magazines, books 307,981 74,500 36 233,481 42
Land leasing and ownership 7,128,486 1,536,556 2,466 5,591,930 3,278
Membership dues and contributions 515,282 109,741 85 405,541 103
Licenses, stamps, tags, and permits 1,161,988 398,072 42 763,915 52
*Estimate based on small sample size.
**Sample Size too small to report data reliably
40 The Relationship between Wildlife Watchers, Hunters, and Anglers
U.S. Fish & Wildlife Service
Division of Federal Aid
Washington, DC 20240
http://federalaid.fws.gov
March 2005
Cover: USFWS/Thomas Taylor
Click tabs to swap between content that is broken into logical sections.
| Rating | |
| Title | The Relationship between Wildlife Watchers, Hunters, and Anglers Addendum to the 2001 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation Report 2001-7 |
| Description | nat_survey2001_relationships.pdf |
| FWS Resource Links | http://library.fws.gov |
| Subject | Document |
| Publisher | U.S. Fish and Wildlife Service |
| Date of Original | March 2005 |
| Type | Text |
| Format | |
| Source |
NCTC Conservation Library Wildlife and Sport Fish Restoration Program Library |
| Rights | Public Domain |
| File Size | 1326585 Bytes |
| Original Format | Document |
| Full Resolution File Size | 1326585 Bytes |
| Transcript | U.S. Fish & Wildlife Service The Relationship between Wildlife Watchers, Hunters, and Anglers Addendum to the 2001 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation Report 2001-7 The Relationship between Wildlife Watchers, Hunters, and Anglers Addendum to the 2001 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation Report 2001-7 U.S. Fish & Wildlife Service March 2005 Jerry Leonard Division of Federal Assistance U.S. Fish and Wildlife Service Arlington VA This report is intended to complement the National and State Reports for the 2001 National Survey of Fishing, Hunting and Wildlife-Associated Recreation. The conclusions in this report are the author’s and do not represent official positions of the U.S. Fish and Wildlife Service. The author thanks Sylvia Cabrera, Richard Aiken, Natalia Perez, Jim Greer, and Dave Buschena for valuable input into this report. 2 The Relationship between Wildlife Watchers, Hunters, and Anglers Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Report Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Data and Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Part One—Wildlife-Watching Participation by Sportsperson Classification . . . . . . . . . . . 5 Wildlife Watching Nationally . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Wildlife Watching by State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Part Two—Socioeconomic Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Comparison of Wildlife Watchers and Sportspersons . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Characteristics of Different Recreationist Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Implication of Demographic Change on Wildlife-Related Recreation . . . . . . . . . . . . . 16 Part Three—Expenditures by Type of Recreationist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Part Four—Historical Fishing and Hunting Activity of Wildlife Watchers . . . . . . . . . . . . 20 Part Five—Wildlife-Watching Participation Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Calculated Probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 A. Wildlife-Watching Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 B. Wildlife-Watching Days by State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 C. Selected Characteristics of Wildlife Watchers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 D. Expenditures for Wildlife Watching and Sporting Activities . . . . . . . . . . . . . . . . . . 38 Contents The Relationship between Wildlife Watchers, Hunters, and Anglers 3 Introduction In 2001 there were 82 million U.S. residents 16 years old and older who participated in wildlife-related recreation. This total of wildlife-related recreationists is often split into two different types: non-consumptive and consumptive. Non-consumptive recreation includes activities such as feeding, observing, or photographing wildlife. Consumptive recreation includes both hunting and fishing. In 2001 participants in non-consumptive activities, who are often referred to as wildlife watchers, totaled 66.1 million, and participants in consumptive activities, who are often referred to as sportspersons, totaled 37.8 million. A graphical representation of consumptive and non-consumptive recreationists is presented in Figure 1. 54% of wildlife-related recreationists were wildlife watchers only, 19% were sportspersons only, and 27% were both wildlife watchers and sportspersons. The populations of consumptive and non-consumptive recreationists are certainly interrelated. Both share a mutual concern and appreciation for the outdoors and wildlife resources. Moreover, there are a relatively large number who participate in both non-consumptive and consumptive recreation. Of the 37.8 million sportspersons (anglers and hunters) nearly 22 million were also wildlife watchers in 2001. To some that feel sportspersons and watchers have few common interests, this statistic may come as a surprise. Pick a sportsperson at random and there is nearly a 60% chance that he or she will also be a wildlife watcher. Or, put another way, only about 4 in 10 sportspersons will not participate in any wildlife watching. Despite the interrelationship, the two groups are sometimes considered or treated as separate and distinct by professionals involved with wildlife recreation from a management, marketing, advocacy, or academic perspective. The notion of separate and distinctive groups of recreationists is due in part to the existence of interest groups who represent each group nearly exclusively. These interest groups sometimes have divergent opinions about resource management objectives; and, when conflict arises, both sides can become emphatically opposed to one another. To be sure, besides their sometimes differing resource management objectives, there are other important differences between the two groups. For example, there are some notable differences in their socioeconomic characteristics. The proportion of the U.S. population who participates in wildlife watching tends to go up with age, whereas the proportion who participates in sporting activities, i.e., hunting or fishing, tends to go down. When considered in conjunction with information about ongoing demographic changes in the U.S., these socioeconomic characteristics have important implications about recreation participation in the future. This report seeks to broaden the understanding of the interrelationship between consumptive and non-consumptive recreationists through the following objectives. Analyze sportspersons participation in wildlife watching. In other words, segment total wildlife-watching participants by sportsperson classification i.e., whether they also participated in hunting and fishing. After segmenting wildlife-watching participants by Figure 1. Wildlife-Related Recreationists, by Type of Activity: 2001 (Population 16 years of age and older.) Note: Sportspersons are hunters and anglers. Wildlife watchers are observers, photographers, and feeders of wildlife. �� ���� 4 The Relationship between Wildlife Watchers, Hunters, and Anglers sportsperson classification, compare the types of wildlife-watching activities enjoyed by both groups. Compare the socioeconomic characteristics of the three different groups of recreationists shown in Figure 1: wildlife watchers exclusively, sportspersons exclusively, and those who are both sportspersons and wildlife watchers. The socioeconomic characteristics compared include population size of residence, geographic region of residence, age, sex, ethnicity, race, income, and education. Examine wildlife-related recreation spending by the three different groups. Examine the relationship between historical hunting/fishing participation and wildlife watching. Lastly, examine the change in an individual’s likelihood of wildlife-watching participation given that he or she participated in hunting or fishing. Knowledge obtained through this analysis could be useful for a variety of reasons. Differing participation patterns among the two groups by age and ethnicity could indicate how aging baby boomers and increasing urbanization in the U.S. may affect recreation participation in the future. Knowledge of expenditures by the different groups could give manufacturers a better understanding of total sales potential for different types of products. Knowledge of the relationship between prior hunting and fishing activity and wildlife watching may foster greater consensus about the appropriate stewardship of resources among interest groups or give resource managers guidance in designing resource plans that are capable of bringing the greatest satisfaction to all recreationists. Report Organization The report is organized into five parts: Part One: The “Wildlife Watching Participation by Sportsperson Classification” section examines the size and geographic dispersion of the wildlife-watching population by type of activity and by sportsperson classification. Estimates of total participation levels and days of participation are made for numerous aspects of around-the-home and away-from-home wildlife watching. Part Two: The “Socioeconomic Characteristics” section compares the characteristics of the three different groups of recreationists who appear in Figure 1: wildlife watchers exclusively, sportspersons exclusively, and those who are both sportspersons and wildlife watchers. Part Three: The “Expenditures by Type of Recreationist” section provides a detailed analysis of all wildlife recreation spending by recreationist type. Recreationists are treated as either watchers exclusively, sportspersons exclusively, or sportspersons and wildlife watchers. Part Four: The “Historical Fishing and Hunting Activity of Wildlife Watchers” section examines the percent of all wildlife watchers who have participated in hunting or fishing in the past. Part Five: Lastly, in the “Wildlife- Watching Participation Model” section a logit regression model is used to examine the impact that numerous variables have on the probability that an individual will participate in wildlife watching. Data and Definitions All reported data contained herein are from the 2001 National Survey of Fishing, Hunting, and Wildlife- Associated Recreation (FHWAR).1 Consequently, all participation, dollar expenditures, and hunting behavior statistics are representative of 2001. Additionally, all data represents persons age 16 years and older. The exact questions used to identify wildlife watchers appear in Appendix A; but, in summary, the following definitions are applicable. An away-from-home wildlife watcher is one who took trips or outings at least one mile from home for the primary purpose of observing, photographing, or feeding wildlife. Trips do not include those to zoos, circuses, aquariums, museums, nor those for hunting, fishing, or scouting. An around-the-home wildlife watcher is one who participated in one or more of the following activities within a one mile radius of home: photographing any type of wildlife; feeding any type of wildlife; visiting public parks or publicly owned natural areas for the purpose of observing, photographing, or feeding wildlife; taking a special interest in wildlife other than simply noticing wildlife while doing other activities; or maintaining natural areas or plantings for the benefit of wildlife. For the sake of brevity wildlife watchers are often referred to simply as watchers. The activity of wildlife watching is referred to simply as watching. Sportsperson activities, i.e., hunting and fishing, are referred to simply as sporting activities. Recreationists that do not participate in sporting activities are referred to as non-sportspersons. The three recreationist groups shown in Figure 1 are referred to as follows: watchers only participate in wildlife watching only; sportspersons only participate in sporting activities only; watchers-sportspersons participate in both watching and sporting activities. 1 FHWAR documents are available on the U.S. Fish and Wildlife Service webpage: http://federalaid.fws.gov/surveys/ surveys.html. The Relationship between Wildlife Watchers, Hunters, and Anglers 5 Part One–Wildlife-Watching Participation by Sportsperson Classification Analysis of wildlife watching by sportsperson classification reveals the portion of nonconsumptive recreation attributable to sportspersons and differences in the nonconsumptive recreation activities between sportspersons and non-sportspersons. Wildlife Watching Nationally Table 1 reveals the number of participants and days of wildlife watching by type of activity and sportsperson classification. It reveals that a substantial portion of all nonconsumptive recreationists in 2001, 33%, were also sportspersons. The remaining percentages in column five can be used to gauge which activities have a comparatively higher proportion attributable to sportspersons. For example, a comparison of row two and row six reveals that sportspersons make up a substantially higher share of participants in away-from-home than around-the-home wildlife watching. They make up 44% of away-from-home watchers and 32% of around-the-home watchers. Comparisons of percentages are useful in determining how wildlife watching activities of sportspersons differ in emphasis from non-sportspersons. Table 1 indicates little variation in sportspersons’ share of wildlife watching activities within the broader around-the-home and away-from-home classifications. The proportion of sportspersons within all activities classified as away from home are close to 44%. There is a slight increase in share for feeding wildlife, 46%, and a slight decrease in share for photographing, 42%. Interestingly, within the around-the- home activities, the share of sportspersons is slightly higher for photographing wildlife. Table 1. Wildlife-Watching Participants and Days by Type of Activity and Sportsperson Classification: 2001 (Population 16 years of age and older. Numbers in thousands.) All Non- Sportspersons Percent of All Sportspersons Percent of All Participants All Wildlife Watching 66,105 44,263 67% 21,842 33% Away from Home 21,823 12,190 56% 9,633 44% Observe Wildlife 20,080 11,594 58% 8,487 42% Photograph Wildlife 9,427 5,423 58% 4,004 43% Feed Wildlife 7,078 3,798 54% 3,279 46% Around the Home 62,928 42,766 68% 20,162 32% Observe Wildlife 42,111 28,385 67% 13,726 33% Photograph Wildlife 13,937 8,825 63% 5,113 37% Feed Wildlife 53,988 36,757 68% 17,231 32% Visit Public Parks or Areas 10,981 7,326 67% 3,655 33% Maintain Plantings or Natural Areas 13,073 8,769 67% 4,304 33% Average Days of Participation All Wildlife Watching 83 83 84 Away from Home 17 17 18 Observe Wildlife 15 14 16 Photograph Wildlife 8 8 9 Feed Wildlife 15 14 15 Around the Home 81 81 82 Observe Wildlife 123 124 119 Photograph Wildlife 14 14 14 Visit Public Parks or Areas 4 4 5 Total Days All Wildlife Watching 5,488,866 3,659,767 67% 1,829,099 33% Away from Home 372,006 201,582 54% 170,425 46% Observe Wildlife 295,345 162,190 55% 133,155 45% Photograph Wildlife 76,324 41,436 54% 34,888 46% Feed Wildlife 103,307 53,043 51% 50,264 49% Around the Home 5,116,860 3,458,186 68% 1,658,674 32% Observe Wildlife 5,159,259 3,532,392 69% 1,626,867 32% Photograph Wildlife 190,120 119,255 63% 70,865 37% Visit Public Parks or Areas 225,324 141,599 63% 83,725 37% 6 The Relationship between Wildlife Watchers, Hunters, and Anglers Table 1 also shows the total days and average days of wildlife watching around the home and away from home. The total number of days around the home and away from home was 5.5 billion, and the proportion attributable to sportspersons is identical to that for participants, 33%. The average days of wildlife watching of sportspersons and non-sportspersons are very similar. The average of sportspersons is one to two days higher for most types of wildlife watching. However, it is notably 5 days lower for observing wildlife around the home. Table 2 displays the distribution of away-from-home and around-the-home watchers by species of wildlife observed. Sportspersons and non-sportspersons do have some apparent differences in species viewed. For around the home, sportspersons have an appreciably higher concentration of watchers who observe fish and other wildlife, large land mammals, and reptiles or amphibians. Sportspersons’ shares of total participation for these species are 45%, 40%, and 39% respectively, which is higher than their overall around-the-home share of 32%. Sportspersons also have a relatively higher than average share of participants observing large land mammals and fish away from home, where their shares of total participants are 47% and 48% respectively. Additionally, at 47%, sportspersons have a higher share of away-from-home watchers of “Other Birds.” In summary, whether from a days or total participants perspective, sportspersons comprise a substantial portion of wildlife watching. Further, the information in Tables 1 and 2 reveals that sportspersons and non-sportspersons have very slight differences in the average number of days across all types of watching, but there are some apparent differences in species observed. Sportspersons have a relatively higher proportion of participants who observe large land mammals and fish. Table 2. Participants in Wildlife Watching by Species and Sportsperson Classification: 2001 (Population 16 years of age and older. Numbers in thousands.) All Non- Sportspersons Percent of All Sportspersons Percent of All Away from Home, Total 21,823 12,190 56% 9,633 44% Total Birds 18,580 10,987 59% 7,593 41% Birds of Prey 12,495 7,176 57% 5,319 43% Waterfowl 14,432 8,477 59% 5,955 41% Water Birds 10,314 6,089 59% 4,225 41% Songbirds 12,878 7,633 59% 5,245 41% Other Birds 7,907 4,211 53% 3,695 47% Total Land Mammals 15,506 8,612 56% 6,894 45% Large Land Mammals 12,226 6,485 53% 5,741 47% Small Land Mammals 12,958 7,500 58% 5,458 42% Fish 6,330 3,290 52% 3,040 48% Marine Mammals 3,013 2,016 67% 997 33% Other Wildlife 9,409 5,604 60% 3,805 40% Around the Home, Total 62,928 42,766 68% 20,162 32% Birds 40,306 27,377 68% 12,929 32% Large Land Mammals 17,481 10,548 60% 6,933 40% Small Land Mammals 32,747 22,254 68% 10,494 32% Reptiles or Amphibians 9,773 5,975 61% 3,798 39% Insects 13,835 9,195 66% 4,640 34% Fish or Other Wildlife 7,932 4,324 55% 3,609 45% The Relationship between Wildlife Watchers, Hunters, and Anglers 7 Wildlife Watching by State Tables 3, 4, and 5 reveal the number of watchers by sportsperson classification and state where watching occurred. Table 3 presents the state distribution of away-from-home watchers, and Table 4 presents the state distribution of around-the- home watchers. Table 5 presents the total recreationists by type shown in Figure 1: watchers only, sportspersons only, and watchers-sportspersons. Generally, the tables reveal a wide variation in the proportional distribution of watchers with respect to sportsperson classification. Table 3 reveals that the proportional distribution of away-from-home watchers between non-sportspersons and sportspersons varies substantially by state. At 80% Mississippi has the highest sportsperson share. Minnesota, Oklahoma, and Georgia follow with 63%, 59%, and 57% sportspersons. Altogether, sportspersons account for 50% or more of away-from-home watchers in 14 states. States with the least sportsperson share of away-from-home watchers are California, Delaware, Connecticut, and Massachusetts, with 21%, 26%, 26%, and 28% respectively. Table 3. Away-from-Home Wildlife Watchers by Sportsperson Classification and State Where Activity Occurred: 2001 (Population 16 years of age and older. Numbers in thousands.) All Away-from- home Non- Sportspersons Percent of All Sportspersons Percent of All AK 292 141 48% 151 52% AL 276 145 53% 132 47% AR 211 94 45% 117 55% AZ 638 446 70% 191 30% CA 2270 1804 79% 466 21% CO 838 493 59% 346 41% CT 279 207 74% 73 26% DE 96 71 74% 25 26% FL 1503 889 59% 614 41% GA 411 178 43% 234 57% HI 141 88 62% 53 38% IA 310 141 45% 169 55% ID 451 277 61% 174 39% IL 638 347 54% 291 46% IN 474 262 55% 212 45% KS 297 147 49% 150 51% KY 385 192 50% 193 50% LA 314 151 48% 163 52% MA 542 388 72% 154 28% MD 533 315 59% 218 41% ME 419 261 62% 158 38% MI 884 479 54% 405 46% MN 634 233 37% 400 63% MO 738 357 48% 381 52% MS 131 ** ** *105 *80% MT 511 327 64% 184 36% NC 588 327 56% 261 44% ND 93 58 62% 35 38% NE 186 102 55% 84 45% NH 425 291 68% 134 32% NJ 688 484 70% 204 30% NM 387 263 68% 124 32% NV 309 201 65% 107 35% NY 1330 860 65% 469 35% OH 898 529 59% 370 41% OK 403 166 41% 237 59% OR 910 625 69% 285 31% PA 1279 786 61% 493 39% RI 98 54 55% 44 45% SC 331 157 47% 174 53% SD 181 80 44% 101 56% TN 683 413 60% 270 40% TX 1002 566 56% 435 44% UT 530 266 50% 263 50% VA 772 517 67% 255 33% VT 307 210 68% 97 32% WA 1065 700 66% 365 34% WI 1000 527 53% 473 47% WV 219 134 61% 85 39% WY 416 233 56% 182 44% *Estimate based on small sample size. **Sample Size too small to report data reliably 8 The Relationship between Wildlife Watchers, Hunters, and Anglers Table 4 reveals that the distribution of around-the-home watchers between non-sportspersons and sportspersons also varies substantially by state. At 61% Wyoming has the highest sportsperson share. Alaska, Utah, and Montana follow with 56%, 48%, and 48% respectively. At 15% California has the lowest sportsperson share for around-the-home watchers just as it does for away-from-home. Massachusetts, Nevada, and Rhode Island all follow with 22%. Table 4. Around-the-Home Wildlife Watchers by Sportsperson Classification and State of Residence: 2001 (Population 16 years of age and older. Numbers in thousands.) All Around-the- Home Non- Sportspersons Percent of All Sportspersons Percent of All AK 221 98 44% 123 56% AL 925 588 64% 337 36% AR 762 455 60% 308 40% AZ 1,063 822 77% 241 23% CA 4,853 4,111 85% 742 15% CO 1,127 729 65% 398 35% CT 859 631 73% 228 27% DE 168 119 71% 48 29% FL 2,635 1,617 61% 1,017 39% GA 1,305 781 60% 524 40% HI 120 71 59% 49 41% IA 939 601 64% 338 36% ID 333 196 59% 137 41% IL 2,379 1,512 64% 866 36% IN 1,727 1,161 67% 566 33% KS 718 433 60% 285 40% KY 1,234 769 62% 466 38% LA 802 520 65% 282 35% MA 1,443 1,126 78% 316 22% MD 1,261 905 72% 357 28% ME 501 345 69% 156 31% MI 2,361 1,564 66% 797 34% MN 1,932 1,024 53% 908 47% MO 1,514 941 62% 572 38% MS 576 357 62% 219 38% MT 341 178 52% 163 48% NC 1,815 1,321 73% 494 27% ND 125 66 53% 59 47% NE 469 301 64% 168 36% NH 445 319 72% 126 28% NJ 1,640 1,205 73% 435 27% NM 449 335 75% 114 25% NV 300 234 78% 66 22% NY 3,442 2,528 73% 914 27% OH 2,653 1,905 72% 748 28% OK 997 588 59% 409 41% OR 1,204 838 70% 366 30% PA 3,371 2,365 70% 1,005 30% RI 237 184 78% 53 22% SC 1,045 652 62% 393 38% SD 241 140 58% 101 42% TN 1,655 1,134 69% 520 31% TX 2,930 1,835 63% 1,095 37% UT 515 267 52% 248 48% VA 2,105 1,484 71% 620 29% VT 280 181 65% 99 35% WA 2,105 1,452 69% 653 31% WI 2,076 1,310 63% 766 37% WV 492 345 70% 147 30% WY 154 60 39% 93 61% The Relationship between Wildlife Watchers, Hunters, and Anglers 9 Figure 2 displays a graphical representation of sportspersons’ share of away-from-home wildlife watchers by state. Figure 3 displays a graphical representation of the sportsperson share of around-the-home wildlife watchers by state. Table 5 indicates similarly that the share of recreationists that are watchers-sportspersons varies dramatically by state. Those that participate in both activities ranges from a low of 16% for California to a high of 47% for Montana. Other states with notably low proportions of watchers-sportspersons are Massachusetts, New Jersey, and Arizona, which all have less than 20%. At the other extreme, Minnesota and Utah both have greater than 41% watchers-sportspersons. ��� ������������ Figure 2. Percent Away-from-Home Wildlife Watchers Who Were also Sportspersons < 30 percent 30–39 percent 40–49 percent ≥ 50 percent �� ���������� �� Figure 3. Percent Around-the-Home Wildlife Watchers Who Were also Sportspersons < 25 percent 25–34 percent 35–39 percent ≥ 40 percent 10 The Relationship between Wildlife Watchers, Hunters, and Anglers Table 5. Participation in Wildlife-Related Recreation by Recreationist Type and State of Residence: 2001 (Population 16 years of age and older. Numbers in thousands.) All Recreationists Watchers Only Percent of All Sportspersons Only Percent of All Watchers- Sportspersons Percent of All AK 320 115 36% 79 25% 126 39% AL 1,323 597 45% 358 27% 368 28% AR 1,038 417 40% 260 25% 361 35% AZ 1,296 859 66% 189 15% 248 19% CA 6,873 4,387 64% 1,382 20% 1,104 16% CO 1,518 839 55% 305 20% 374 25% CT 996 665 67% 113 11% 218 22% DE 220 126 57% 50 23% 44 20% FL 3,857 1,699 44% 1,001 26% 1,157 30% GA 1,932 796 41% 606 31% 530 28% HI 195 81 42% 69 35% 45 23% IA 1,212 632 52% 229 19% 351 29% ID 507 201 40% 119 23% 187 37% IL 3,148 1,641 52% 656 21% 851 27% IN 2,179 1,265 58% 393 18% 521 24% KS 942 451 48% 207 22% 284 30% KY 1,547 844 55% 283 18% 420 27% LA 1,326 497 37% 486 37% 343 26% MA 1,726 1,205 70% 233 13% 288 17% MD 1,546 975 63% 235 15% 336 22% ME 607 351 58% 87 14% 169 28% MI 2,950 1,625 55% 526 18% 799 27% MN 2,388 951 40% 395 16% 1,042 44% MO 2,010 934 46% 398 20% 678 34% MS 851 318 37% 272 32% 261 31% MT 438 159 36% 76 17% 203 47% NC 2,330 1,348 58% 446 19% 536 23% ND 228 58 25% 93 41% 77 34% NE 623 315 51% 125 20% 183 29% NH 506 331 65% 56 11% 119 24% NJ 1,993 1,324 66% 299 15% 370 19% NM 595 339 57% 124 21% 132 22% NV 439 245 56% 105 24% 89 20% NY 3,990 2,497 62% 466 12% 1,027 26% OH 3,407 1,894 55% 639 19% 874 26% OK 1,308 578 44% 266 20% 464 36% OR 1,545 934 60% 259 17% 352 23% PA 4,169 2,521 60% 647 16% 1,001 24% RI 280 184 66% 38 13% 58 21% SC 1,375 701 51% 296 22% 378 27% SD 326 150 46% 75 23% 101 31% TN 2,109 1,206 57% 403 19% 500 24% TX 4,515 1,770 39% 1,427 32% 1,318 29% UT 736 268 37% 164 22% 304 41% VA 2,535 1,565 62% 367 14% 603 24% VT 319 194 61% 32 10% 93 29% WA 2,537 1,605 63% 303 12% 629 25% WI 2,489 1,348 54% 330 13% 811 33% WV 694 341 49% 177 26% 176 25% WY 223 85 38% 51 23% 87 39% The Relationship between Wildlife Watchers, Hunters, and Anglers 11 This section compares the socioeconomic characteristics of wildlife watchers and sportspersons from several perspectives. The aim is to show how socioeconomic characteristics of different groups or sets of recreationists differ from one another. The comparisons made in this section can best be explained through the use of Figure 1. First, the socioeconomic characteristics of the set of all wildlife watchers are compared to the characteristics of the set of all sportspersons. In Figure 1 the group of recreationists in areas A and C are compared to the group of recreationists in C and B. This is a simplistic comparison that ignores the overlap or intersection of the two groups. Second, the characteristics of those who are watchers-sportspersons, area C, are compared to those who are watchers only, area B, and sportspersons only, area A. The socioeconomic characteristics addressed include the following: population size of residence, Bureau of Census geographic region, age, sex, ethnicity, race, household income, and education. As will be shown below, an understanding of the distinctiveness of the different recreationist groups yields information about how each will likely be affected by ongoing demographic trends in the U.S. such as population urbanization, increasing average age, and minority growth. Comparison of Wildlife Watchers and Sportspersons Table 6 summarizes the socioeconomic characteristics of wildlife watchers and sportspersons. The first row in Table 6 indicates 31% of all U.S. residents 16 years of age and older are wildlife watchers, and 18% are sportspersons. Deviations from this overall distribution yield information about how socioeconomic characteristics of wildlife watchers differ from sportspersons. This overall distribution is referred to as an “average.” The discussion that follows addresses each of the socioeconomic characteristics presented in Table 6. Population Size of Residence The population size of residence is measured in terms of metropolitan statistical area (MSA). “The general concept of a metropolitan . . . statistical area is that of a core area containing a substantial population nucleus, together with adjacent communities having a high degree of economic and social integration with that core . . . Each metropolitan statistical area must have at least one urbanized area of 50,000 or more inhabitants.” Consequently, classification by MSA type provides information on the population of recreationist residences. The categories of MSA listed in Table 6 indicate whether the recreationist lived in a MSA of various sizes or lived outside of a MSA, which indicates a more rural residency. The table indicates that the percent of the population who participates (participation rate) falls for both wildlife watching and sporting activities as the population size of residence rises. The participation rate in wildlife watching falls from 41% for those residing outside MSAs to 29% for those residing inside MSAs. Similarly, the participation rate in sporting activities falls from 27% for those residing outside MSAs to 16% for those residing inside MSAs. Moreover, the rate also tends to fall as the size of MSA increases. When considering the change in the participation rate between recreationists residing outside MSAs and those inside MSAs, it is important to note that the proportional decrease is greater for sporting activities. The participation rate for sporting activities falls from 27% to 16%, which represents a proportional change of -43%, compared to a -29% change in wildlife watching. Census Geographic Regions The participation rate of both wildlife watchers and sportspersons varies substantially by geographic region. The participation rate for both groups is highest in the West North Central region with rates of 43% and 29% respectively. The lowest participation rate for watching occurs in the West South Central with 25%. The Middle Atlantic and Pacific tie for the lowest Part Two–Socioeconomic Characteristics 12 The Relationship between Wildlife Watchers, Hunters, and Anglers Table 6. Selected Characteristics of Wildlife Watchers and Sportspersons: 2001 (Population 16 years of age and older. Numbers in thousands.) U.S. Population Wildlife Watchers Percent of Population Sportspersons Percent of Population Total All Persons 212,298 66,105 31% 37,805 18% Population Size of Residence Metropolitan statistical area (MSA) 171,147 49,414 29% 26,564 16% 1,000,000 or more 112,984 29,724 26% 14,739 13% 250,000 to 999,999 41,469 12,880 31% 7,638 18% 50,000 to 249,999 16,693 6,811 41% 4,186 25% Outside MSA 41,151 16,691 41% 11,241 27% Census Geographic Region New England 10,575 3,875 37% 1,504 14% Middle Atlantic 29,806 8,740 29% 3,810 13% East North Central 34,082 11,631 34% 6,400 19% West North Central 14,430 6,206 43% 4,239 29% South Atlantic 39,286 11,395 29% 6,957 18% East South Central 12,976 4,514 35% 2,865 22% West South Central 23,337 5,747 25% 4,924 21% Mountain 13,308 4,619 35% 2,757 21% Pacific 34,498 9,377 27% 4,349 13% Age 16-17 7,709 1,678 22% 1,497 19% 18-24 22,234 3,051 14% 3,303 15% 25-34 35,333 8,869 25% 7,136 20% 35-44 44,057 14,939 34% 9,966 23% 45-54 40,541 14,491 36% 7,826 19% 55-64 25,601 10,326 40% 4,629 18% 65+ 36,823 12,752 35% 3,447 9% Sex Male 101,916 30,695 30% 28,462 28% Female 110,381 35,409 32% 9,343 8% Ethnicity Hispanic 21,910 2,699 12% 1,743 8% Non-Hispanic 190,388 63,409 33% 36,063 19% Race White 181,129 62,781 35% 35,300 19% Black 21,708 2,029 9% 1,666 8% Asian 7,141 654 9% 365 5% All Others 2,320 641 28% 474 20% continues The Relationship between Wildlife Watchers, Hunters, and Anglers 13 percent of sportspersons with 13%. While the participation rate varies substantially for both watching and sporting activities, there is relatively more variation in sporting participation. Age Participation rates for watching and sporting activities vary substantially with respect to age. The participation rate for sporting activities is rather stable by age categories, except for the recreationists 65 years of age and older. Beyond 64 the participation rate for sporting activities declines substantially. However, there is a positive correlation with the rate of wildlife watching by age. The percent of the population who participates climbs from 22% for those 16-17 to 40% for those 55-64. It then declines to 35% for those over 64, but overall the positive correlation persists. Sex The participation rate for watching and sporting activities also differ substantially with respect to gender. The rate of participation in watching is relatively stable around 31% for both males and females. However, for sporting activities the participation rate of males is substantially higher than that of females. Ethnicity Hispanics have a substantially lower participation rate than Non-Hispanics in both wildlife watching and sporting activities. 12% of Hispanics participate in watching compared to 33% of Non- Hispanics. Similarly, 8% of Hispanics participate in sporting activities compared to 19% of Non-Hispanics. Race The participation rate for both wildlife watching and sporting activities is substantially higher for Whites than Blacks and Asians. While 35% of Whites are watchers, Blacks and Asians participate at a 9% rate. Similarly, the participation rate of Whites in sporting activities is 19%, while Blacks and Asians participate at rates of 8% and 5% respectively. Annual Household Income The participation rates of both watching and sporting activities generally increase as incomes increase. The rate for watching climbs from 23% for those with incomes of under $10,000 to 44% for those with incomes of $75,000-$99,999. Similarly, the rate for sporting activities climbs from 9% for those with incomes of under $10,000 to 25% for those with incomes of $50,000-$99,999. Education The participation rate for watching has a positive correlation with years of education, whereas the participation rate for sporting activities is positively correlated over a portion of the range. The rate for watching climbs from 22% for those with 11 years of education or less to 43% for those with 5 or more years of college. The rate for sporting activities climbs from 14% for those with 11 years of education or less to 20% for those with 1-3 years of college, and then falls slightly to 18% for those with 5 or more years of college. Characteristics of Different Recreationist Groups Rather than compare all wildlife watchers with all sportspersons, this section compares the socioeconomic characteristics of the three different groups of recreationists in Figure 1: watchers only, sportspersons only, watchers-sportspersons. In other words it compares the socioeconomic characteristics of those in regions A, B, and C in Figure 1. Comparison by type of recreationist reveals additional information about how the composition of wildlife recreationists will likely change due to demographic shifts. Table 6. Selected Characteristics of Wildlife Watchers and Sportspersons: 2001 – continued (Population 16 years of age and older. Numbers in thousands.) U.S. Population Wildlife Watchers Percent of Population Sportspersons Percent of Population Annual Household Income Under $10,000 10,594 2,387 23% 978 9% $10-$19,999 15,272 3,837 25% 1,831 12% $20-$24,999 10,902 2,879 26% 1,659 15% $25-$29,999 11,217 3,461 31% 2,000 18% $30-$34,999 11,648 4,069 35% 2,349 20% $35-$39,999 9,816 3,142 32% 2,186 22% $40-$49,999 16,896 6,402 38% 4,116 24% $50-$74,999 31,383 12,359 39% 7,893 25% $75-$99,999 17,762 7,735 44% 4,413 25% $100,000 or More 19,202 8,010 42% 4,521 24% Not Reported 57,606 11,823 21% 5,858 10% Education 11 years or less 32,820 7,201 22% 4,705 14% 12 years 73,719 21,154 29% 13,039 18% 1-3 years of college 49,491 16,013 32% 9,980 20% 4 years of college 34,803 12,603 36% 5,994 17% 5 years or more of college 21,464 9,133 43% 3,817 18% 14 The Relationship between Wildlife Watchers, Hunters, and Anglers Table 7. Socioeconomic Characteristics of Different Types of Wildlife-Related Recreationists: 2001 (Population 16 years of age and older. Numbers in thousands.) All Wildlife Recreationists Watchers Only Percent of All Sportspersons Only Percent of All Watchers- Sportspersons Percent of All Total All Persons 82,068 44,263 54% 15,963 20% 21,842 27% Population Size of Residence Metropolitan statistical area (MSA) 60,876 34,312 56% 11,462 19% 15,102 25% 1,000,000 or more 36,087 21,348 59% 6,363 18% 8,376 23% 250,000 to 999,999 16,164 8,526 53% 3,284 20% 4,354 27% 50,000 to 249,999 8,625 4,439 51% 1,814 21% 2,372 28% Outside MSA 21,192 9,951 47% 4,501 21% 6,740 32% Census Geographic Region New England 4,428 2,924 66% 553 12% 951 22% Middle Atlantic 10,133 6,323 62% 1,393 14% 2,417 24% East North Central 14,129 7,729 55% 2,498 18% 3,903 27% West North Central 7,717 3,478 45% 1,511 20% 2,728 35% South Atlantic 14,485 7,528 52% 3,090 21% 3,867 27% East South Central 5,804 2,939 51% 1,290 22% 1,575 27% West South Central 8,174 3,250 40% 2,427 30% 2,497 30% Mountain 5,744 2,987 52% 1,125 20% 1,632 28% Pacific 11,455 7,106 62% 2,078 18% 2,271 20% Age 16-17 2,641 1,144 43% 963 37% 534 20% 18-24 4,963 1,660 33% 1,912 39% 1,391 28% 25-34 12,267 5,131 42% 3,398 28% 3,738 30% 35-44 19,033 9,067 48% 4,094 21% 5,873 31% 45-54 17,350 9,524 55% 2,859 16% 4,967 29% 55-64 11,926 7,297 61% 1,600 14% 3,029 25% 65+ 13,888 10,441 75% 1,136 8% 2,311 17% Sex Male 43,257 14,795 34% 12,562 29% 15,900 37% Female 38,810 29,467 76% 3,401 9% 5,942 15% Ethnicity Hispanic 3,824 2,081 55% 1,125 29% 619 16% Non-Hispanic 78,249 42,186 54% 14,840 19% 21,223 27% Race White 77,202 41,902 54% 14,421 19% 20,879 27% Black 3,130 1,464 47% 1,101 35% 565 18% Asian 882 517 59% 228 26% 137 15% All Others 855 381 45% 214 25% 260 30% continues The Relationship between Wildlife Watchers, Hunters, and Anglers 15 Table 7 summarizes the socioeconomic characteristics of the different recreationist groups. The first row indicates 54% of all recreationists are watchers only, 19% are sportspersons only, and 27% are watchers-sportspersons. As discussed for the tables above, deviations from these percentages yield information about how the different types of recreationists differ from one another. Population Size of Residence Table 7 indicates that recreationists who live outside MSAs are more likely to be watchers-sportspersons than those who live inside MSAs. 32% of recreationists who live outside MSAs are watchers-sportspersons, which compares to 25% of those who live inside MSAs. There is also an apparent negative correlation between the size of MSA and the proportion of watchers-sportspersons. The proportion goes from a low of 23% for MSAs of one million or more residents to 27% for MSAs of less than a million. Census Geographic Regions The share of watchers-sportspersons varies dramatically by geographic region. The highest proportion occurs in the West North Central Region with 35%. The West South Central region follows close behind with 31%. At the other extreme are the Pacific Region with 20% and New England with 22%. If there is some conflict between the resource management objectives of wildlife watchers and sportspersons, then potential conflict could be greater in regions with a lower share of watchers-sportspersons. A lower share of watchers-sportspersons indicates fewer recreationists who desire a management strategy that provides for a desirable mix of both activities. The individuals that participate in both activities are likely to favor ��middle-of-the road�� management practices. To be sure, individuals who participate in both activities will likely differ in their optimal “mix” of management practices to satisfy both interests, but they all will desire preservation of resource amenities useful for both. In the West North Central and West South Central a relatively large portion of watchers are also sportspersons and vice versa. Alternatively, in the Pacific region there is a substantially smaller intersection in recreation practices. If it is true that conflict is greater in regions with a smaller intersection of recreationists, one implication is that resource managers in the Pacific region may have a more difficult task of satisfying the desires of both. Age Age has a dramatic impact on the type of recreation in which individuals participate. The proportion of all recreationists who are watchers only is positively correlated with age. For recreationists 18-24, only 33% are watchers only. However, as age increases this share climbs consistently up to 75% for those 65 and older. Conversely, those who participate in only sporting activities fall from 39% in the 18-24 category to 8% for those 65 and older. Sex 37% of males are watchers-sportspersons, which compares to only 15% of females. Ethnicity Hispanics are notably less likely than Non-Hispanics to participate in watching and sporting activities. The share of watchers-sportspersons for Hispanics is 16%, while for Non-Hispanics the share climbs to 27%. Race The results for race indicate some noteworthy differences in recreationist type. For sportspersons only, Whites participate at notably lower rate than the other races. Whites also have a substantially higher share of watchers-sportspersons. Compared to the variation in sportspersons only and watchers-sportspersons there is relatively little racial variation in the proportion of recreationists who are watchers only. Table 7. Socioeconomic Characteristics of Different Types of Wildlife-Related Recreationists: 2001 – continued (Population 16 years of age and older. Numbers in thousands.) All Wildlife Recreationists Watchers Only Percent of All Sportspersons Only Percent of All Watchers- Sportspersons Percent of All Annual Household Income Under $10,000 2,912 1,934 66% 525 18% 453 16% $10-$19,999 4,749 2,918 62% 912 19% 919 19% $20-$24,999 3,614 1,955 54% 735 20% 924 26% $25-$29,999 4,327 2,327 54% 866 20% 1,134 26% $30-$34,999 5,012 2,663 53% 943 19% 1,406 28% $35-$39,999 4,120 1,934 47% 978 24% 1,208 29% $40-$49,999 8,104 3,988 49% 1,702 21% 2,415 30% $50-$74,999 15,564 7,671 49% 3,205 21% 4,688 30% $75-$99,999 9,447 5,034 53% 1,712 18% 2,701 29% $100,000 or More 9,620 5,099 53% 1,610 17% 2,911 30% Not Reported 14,599 8,741 60% 2,776 19% 3,082 21% Education 11 years or less 9,712 5,007 51% 2,511 26% 2,194 23% 12 years 26,766 13,727 51% 5,612 21% 7,427 28% 1-3 years of college 19,926 9,946 50% 3,913 20% 6,067 30% 4 years of college 14,986 8,992 60% 2,383 16% 3,611 24% 5 years or more of college 10,406 6,589 63% 1,273 12% 2,544 24% 16 The Relationship between Wildlife Watchers, Hunters, and Anglers Annual Household Income There is some variation in the proportion of recreationists who are watchers-sportspersons at the very low end of the income distribution. The lowest income brackets have a notably lower share. Those with incomes of less than $10,000 and $10,000-$19,999 have shares of 16% and 19% respectively. This percent climbs sharply for those with incomes of $20,000 or more. Education There is some variation in recreationist type by years of education. The share of watchers only increases sharply for those with 4 years of college or more. Their share climbs from around 50% for those with less than 4 years of college to around 61% for those with more. Implication of Demographic Change on Wildlife Recreation Under certain conditions, the socioeconomic information discussed above can be used to gauge the likely effect of ongoing demographic trends on participation in the different types of wildlife recreation. If certain assumptions hold, current demographic trends have implications on the future participation rate of individuals in wildlife watching and sporting activities. They also have implications about the proportion of all recreationists who will likely participate in both watching and sporting activities. Major Demographic Trends in the U.S. There are several demographic trends in the U.S. that will likely impact wildlife-related recreation in the years ahead. It is beyond the scope of this report to analyze each trend in detail, but a short summary is warranted. The percent of the U.S. population living in rural housing continues to fall. In 1960 approximately 30% of U.S. residents lived in rural areas. This percent has since fallen to 27% in 1970, 25% in 1995, and 22% in 2000.2 The percent of the U.S. population of Hispanic ethnicity is on the rise. In 1980, 6.4% of U.S. residents were Hispanic. This percent has since risen to 9.0% in 1990 and 12.0% in 2000. It is expected to rise to 14.6% by 2010.3 The percent of the population who are of White and not of Hispanic origin is declining. In 1980, 79.6% of U.S. residents were White and not Hispanic, and this has since fallen to 75.6% in 1990 and 69.5% in 2000. This percent is expected to fall further to 67.3% by 20103. Finally, there is the trend of an aging population in the U.S., due to maturing baby boomers. In 1990 the percent of the population over 55 years of age was 20.9%. This percent rose to 21.1% in 2000 and 22.6% in 2005. This percent is expected to continue climbing to 24.7% in 2010 and 28.9% in 20203. Impact on Wildlife Watching and Sporting Activities Under the assumption of relative stability in the participation percentages in Table 6 for population size of residence and age, the demographic trends discussed above provide some indication of how the overall participation rate for wildlife watching will change relative to that of sporting activities. The assumption of relative stability in the participation percentages is best explained using an example. Table 6 indicates that 35% of the U.S. population 65 and over participates in wildlife watching, 40% of those between 55-64 participate, and 36% of those between 45-54 participate. The assumption is that these percentages will not change, or if they do change, they will change only slightly. This is an important assumption to keep in mind in the following discussion. There may be reason to believe that this assumption will not hold. For example, Table 6 indicates that 9% of those 65 and over participate in sporting activities. However, advances in medical care and nutrition continue to improve the health of older Americans. Consequently, it is possible that in the future a greater share of people 65 and older will participate in sporting activities. If there are relatively stable participation rates for population size of residence and age, current demographic trends imply that the overall participation rate for wildlife watching will increase relative to sporting activities. As discussed above, the decline in participation that occurs because individuals reside inside an MSA as opposed to outside is greater for sporting activities than for wildlife watching. The implication is that increased urbanization will have a relatively greater impact on sporting activities than on wildlife watching. Additionally, the wildlife watching participation rate is positively correlated with age, and the participation rate for sporting activities is negatively correlated with age. Consequently, the continued aging of the U.S. population likely portends growth in wildlife watching relative to hunting and fishing. Impact on Share of Recreationists that Participate in Both Wildlife Watching and Sporting Activities Current demographic trends also imply that the share of recreationists who participate in both wildlife watching and sporting activities will likely decline. This conclusion is based on an assessment of how trends will affect those recreationists that are represented in the “Watchers- Sportspersons” column of Table 7, and it could have important political and resource management implications. Essentially, changes in the share of recreationists that participate in both wildlife watching and sporting activities indicate whether the population of recreationists will become increasingly united or divided. A smaller share of participants in both activities indicates that the composition of wildlife recreationists will become increasingly divided. All of the demographic trends discussed above portend increasing division of wildlife recreationists. Table 7 indicates that the proportion of those who are both watchers-sportspersons falls as age increases. Consequently, the aging population of baby boomers suggests that the share of all recreationists that participate in both watching and sporting activities will likely decline in the future. Table 7 also indicates that the share of watchers-sportspersons falls as the population size of residence increases, and the ongoing demographic trend is one of increased urbanization. Hispanics are substantially less likely to participate in both watching and sporting activities than Non-Hispanics, and the Hispanic population is rapidly increasing. Lastly, Whites are more likely to participate in both types of recreation than all other races taken together, and the White population is growing slower than others. 2 “Factors Related to Hunting and Fishing Participation Among the Nation’s Youth,” Responsive Management (2003). 3 “Statistical Abstract of the United States 2004-2005,” U.S. Census Bureau. The Relationship between Wildlife Watchers, Hunters, and Anglers 17 This section examines wildlife recreation spending by type of recreationist: watchers only, sportspersons only, and watchers-sportspersons. The analysis of spending by type of recreationist differs from the conventional analysis by type of activity. Examining wildlife recreation spending by type of recreationist reveals that the majority of spending on wildlife recreation is made by individuals that participate in both watching and sporting activities. This finding helps dispel the notion that spending is made by two separate groups of recreationists. The 2001 FHWAR queried respondents about their spending attributable to wildlife recreation, and it distinguished non-consumptive spending from consumptive spending. In other words, it distinguished spending made pursuant to wildlife watching from that made pursuant to either hunting or fishing. In the published data tables of the 2001 FHWAR, these expenditures are presented in detail. However, publishing estimates by type of activity alone conceals the substantial crossover of recreationists from one type of activity into the other. In a sense, estimates by type of activity alone foster an impression that the two types of recreationists belong to separate cliques or factions. However, the analysis presented above indicates that this is clearly not the case, as substantial crossover does occur. Although not presented in the published tables, data available from the 2001 FHWAR CD can be used to analyze spending from numerous other perspectives. Total wildlife-watching expenditures can be apportioned between sportspersons and non-sportspersons. Total hunting and fishing spending can be apportioned between those who participate in wildlife watching and those who do not. Average expenditures of sportspersons who are wildlife watchers can be calculated and compared to those who are not. Average expenditures of wildlife watchers who are sportspersons can be calculated and compared to those who are not. Total wildlife recreation spending can be apportioned between recreationists of different types. Table 8 and tables in Appendix D address wildlife-recreation spending in every perspective listed here. However, this discussion is focused on the last perspective, as it is the most instructive in highlighting the interrelationship of the different types of recreationists. Figure 4 displays total wildlife-related recreation spending in two ways. The graph on the top displays spending by type of activity. It indicates that 65% of all wildlife recreation spending is made pursuant to hunting or fishing and 35% to wildlife watching. This is the historical method in which spending has been displayed. The graph on the bottom displays spending by type of recreationist. It indicates that the majority of spending on wildlife recreation is done by persons who participate in both wildlife watching and sporting activities. 57% of all recreation expenditures are made by recreationists in both “camps.” Expenditures made by recreationists who participate in only sporting activities or wildlife watching are nearly equal and respectively comprise 20% and 23% of all spending. From this perspective, it is clear that the majority of recreation spending is not made by two mutually exclusive groups. Table 8 presents spending by recreationist type in greater detail. Expenditures are categorized by type of good purchased. “Hunting equipment” includes purchases of rifles, ammunition, and hunting dogs. “Fishing equipment” includes purchases of rods, reels, tackle boxes, and lures. “Auxiliary hunting and fishing equipment” includes spending made pursuant to either hunting or fishing such as camping equipment, clothing, and taxidermy costs. Wildlife-watching equipment includes binoculars, photographic equipment, film, bird food, bird houses, etc. “Auxiliary wildlife-watching equipment” is similar to auxiliary hunting and fishing equipment and includes camping equipment, tents, Part Three–Expenditures by Type of Recreationist USFWS/Debbie McCrensky 18 The Relationship between Wildlife Watchers, Hunters, and Anglers tarps, and backpacking equipment, but the primary intended use of these items was to support wildlife-watching activity, not hunting or fishing. Special equipment includes purchases of big ticket items such as boats, campers, trucks, and cabins that are primarily purchased for use in wildlife-related recreation. For trip-related expenditures, 60% is attributable to watchers-sportspersons, 24% is attributable to sportspersons only, and 16% is attributable to watchers only. The relatively lower share for watchers only is due to substantially lower spending on “Other trip costs.” Watchers only account for 4% of other trip costs, and in the largest category of expenditures within other trip costs, boating costs, they account for only 1%. The only category within other trip costs where watchers only account for a higher than average proportion of spending is public land use fees, where their share is 25%. This likely results from their relatively high use of public parks that charge admission fees. Two-thirds of all spending on fishing equipment and more than two-thirds of all spending on hunting equipment is attributable to watchers-sportspersons. This is a potentially valuable piece of information for manufacturers of hunting and fishing equipment. Almost two-thirds of wildlife-watching equipment is attributable to watchers only. This is generally in line with the proportion of wildlife-watching participants that do not participate in sporting activities, which is seen in Table 1. In summary, there are items where the proportional distribution of wildlife recreation expenditures differs from the 23%, 20%, and 57% for all items presented in Figure 4. Nevertheless, there is not one type of good where spending from only one of the recreationist categories dominates all spending. Spending for every good is attributable to more than one recreationist classification, which underscores the interrelationship that recreationists have in the marketplace. Figure 4. Expenditures for Wildlife-Related Recreation (Total expenditures $108 billion.) ������ ������ ���� �������� �� ��� The Relationship between Wildlife Watchers, Hunters, and Anglers 19 Table 8. Expenditures for all Wildlife-Related Recreation by Recreationist Type: 2001 (Population 16 years of age and older. Numbers in thousands of dollars.) All Watchers Only Percent of All Sportspersons Only Percent of All Watchers- Sportspersons Percent of All Total, All Items 108,390,816 24,481,139 23% 22,153,608 20% 61,756,074 57% Trip-Related Expenditures Total trip-related 28,070,831 4,520,120 16% 6,755,896 24% 16,794,814 60% Food and lodging, total 13,149,781 2,770,299 21% 2,843,705 22% 7,535,778 57% Food 8,957,513 1,535,602 17% 2,094,846 23% 5,327,066 60% Lodging 4,192,268 1,234,697 29% 748,859 18% 2,208,712 53% Transportation, total 7,900,619 1,502,425 19% 1,679,980 21% 4,718,215 60% Public 1,288,653 531,225 41% 201,928 16% 555,501 43% Private 6,611,965 971,200 15% 1,478,052 22% 4,162,713 63% Other trip costs, total 7,020,431 247,396 3% 2,232,212 32% 4,540,822 65% Guide fees, pack trip or package fees 1,177,171 50,917 4% 338,945 29% 787,309 67% Public land use fees 289,585 73,192 25% 63,950 22% 152,443 53% Private land use fees 514,249 13,428 3% 133,710 26% 367,111 71% Equipment rental 395,107 57,196 14% 104,546 27% 233,366 59% Boating costs 3,042,802 38,025 1% 974,448 32% 2,030,328 67% Heating and cooking fuel 205,249 14,638 7% 60,842 30% 129,769 63% Bait 1,105,350 N.A. N.A. 444,396 40% 660,954 60% Ice 290,917 N.A. N.A. 111,376 38% 179,541 62% Equipment and Other Expenses Total 80,319,985 19,961,019 25% 15,397,711 19% 44,961,260 56% Hunting equipment 4,866,399 N.A. N.A. 1,437,191 30% 3,429,207 70% Fishing equipment 4,640,715 N.A. N.A. 1,592,844 34% 3,047,872 66% Auxiliary hunting and fishing equipment 2,627,686 N.A. N.A. 684,658 26% 1,943,028 74% Wildlife-watching equipment 7,353,977 4,564,821 62% N.A. N.A. 2,789,158 38% Auxiliary wildlife-watching equipment 716,899 319,264 45% N.A. N.A. 397,637 55% Special equipment 44,288,116 10,446,204 23% 9,564,151 22% 24,277,764 55% Magazines, books 639,936 177,021 28% 74,500 11% 388,415 61% Land leasing and ownership 11,889,496 3,325,727 28% 1,536,556 13% 7,027,213 59% Membership dues and contributions 1,435,465 674,276 47% 109,741 8% 651,448 45% Plantings 699,309 453,706 65% N.A. N.A. 245,602 35% Licenses, stamps, tags, and permits 1,161,988 N.A. N.A. 398,072 34% 763,915 66% (Z) less than 0.5%. N.A. Not Applicable Note: “Hunting equipment” includes purchases of rifles, ammunition, and hunting dogs. “Fishing equipment” includes purchases of rods, reels, tackle boxes, and lures. “Auxiliary hunting and fishing equipment” includes spending made pursuant to either hunting or fishing such as camping equipment, clothing, and taxidermy costs. Wildlife-watching equipment includes binoculars, photographic equipment, film, bird food, bird houses, etc. “Auxiliary wildlife-watching equipment” is similar to auxiliary hunting and fishing equipment and includes camping equipment, tents, tarps, and backpacking equipment, but the primary intended use of these items was to support wildlife-watching activity, not hunting or fishing. Special equipment includes purchases of big ticket items such as boats, campers, trucks, and cabins that are primarily purchased for use in wildlife-related recreation 20 The Relationship between Wildlife Watchers, Hunters, and Anglers Heretofore, this analysis has shown that there are numerous wildlife recreationists who participate in both wildlife watching and hunting or fishing in the same year: a third of all watchers in 2001 participated in sporting activities, and more than half of all sportspersons in 2001 participated in wildlife watching. Consequently, the notion of two mutually exclusive groups of recreationists is not tenable, and it is more difficult to distinguish two groups of recreationists than one might suppose. The distinctiveness of two separate groups is even more obscure when recreation activity is considered for more than the span of one year. If someone did not participate in hunting or fishing in 2001, but did in prior years, should he or she still be considered a sportsperson? If so, how many years of inactivity in hunting or fishing must pass before one is no longer considered a sportsperson? These are certainly subjective questions that elicit different responses. Some may consider a recreationist a viable sportsperson if he or she participated in hunting or fishing within the last three years; whereas, others may consider participation within the last five years to be sufficient. Fortunately, data from the 2001 screen phase of the FHWAR can be used to satisfactorily answer this question from different perspectives. The 2001 FHWAR was conducted in two phases by the U.S. Census Bureau. The first was the screen phase in which the Census Bureau interviewed a sample of 80,000 households nationwide to determine who in the household had fished, hunted, or engaged in wildlife-watching activities in years 2000 and before, and who planned to engage in those activities in 2001. In most cases, one adult household member provided information for all household members. The second was the detailed interview phase in which those selected as likely anglers, hunters, and wildlife watchers from the screen were given detailed interviews about their recreation activities in 2001. Heretofore, all the data discussed in this analysis was from the detailed interview phase because it provides the most information about recreationist activities in 2001. The screen data could not have been used because respondents answer only a limited set of questions about prior activity and expected future activity, and it has a longer recall period, so it is more prone to suffer from recall bias. However, because the screen does query respondents about sporting activities for years prior to 2000, it is uniquely suited to analyze the relationship between wildlife watching in 2000 and prior sporting activities. Figures 5 and 6 display the distribution of away-from-home and around-the-home watchers based on prior sporting activities. The distributions presented rely on only that portion of the screen sample that answered questions about his or her own activities. All observations where the survey respondent was queried about the activity of another household member were excluded for reliability considerations. Lastly, those who are considered watchers in each figure indicated that they participated in wildlife watching in the year 2000. Figure 5 indicates that the proportion of all away-from-home watchers who are also sportspersons is substantially greater than the 44% previously indicated in Table 1 if historical sporting activities are considered valid criteria for one’s inclusion into the set of all sportspersons. It indicates that within two years prior to the time of the survey, 57% of all away-from- home watchers hunted or fished. More than half of all respondents who indicated that they had participated in away-from-home wildlife watching in 2000 also participated in either hunting Part Four–Historical Fishing and Hunting Participation of Wildlife Watchers The Relationship between Wildlife Watchers, Hunters, and Anglers 21 or fishing from 1998 to 2000. The proportion of away-from-home watchers who participated in hunting or fishing within 5 years of the time of the survey goes up to 63%. Lastly, and perhaps most surprising, Figure 5 indicates that 80% of away-from-home watchers have hunted or fished at some point. Similarly, Figure 6 indicates that the proportion of all around-the-home watchers who are considered sportspersons is substantially greater than the 32% previously indicated in Table 1 if historical sporting activities are considered valid criteria for one’s inclusion into the set of all sportspersons. It indicates that within the two years prior to the time of the survey, 44% of all around-the-home watchers either hunted or fished. The proportion of around-the- home watchers who participated in hunting or fishing within 5 years of the time of the survey goes up to 49%. Lastly, Figure 6 indicates that 72% of around-the- home watchers have hunted or fished at some point. Given the findings here that more than 60% of away-from-home and 49% of around-the-home watchers have participated in either hunting or fishing within 5 years from the time of the survey, this analysis supports the notion that it is more difficult to distinguish two separate groups of recreationists if respondents’ prior sporting activities are taken into account. It underscores just how interrelated the different types of wildlife recreationists really are. Figure 6. Distribution of Around-the-Home Wildlife Watchers by Hunting and Fishing Activity Figure 5. Distribution of Away-from-Home Wildlife Watchers by Hunting and Fishing Activity �� ��������� ���� �� ��� ���� ���� ��� ������������ 22 The Relationship between Wildlife Watchers, Hunters, and Anglers Figures 5 and 6 indicate that the majority of both around-the-home and away-from-home wildlife watchers have participated in sporting activities at some point. However, these tables alone do not assess the increase in the probability that someone will be a wildlife watcher given he or she has hunted or fished in the past. This section presents a wildlife-watching regression model to estimate this effect. To appropriately assess the increase in probability that someone will be a wildlife watcher if he or she has hunted in the past, the regression model should also include several other variables that are significantly correlated with wildlife-watching participation. Table 6 indicates that there are numerous other variables that are likely correlated with wildlife watching. The participation rate appears to vary with respect to all the variables that appear in Table 6: population size and geographic region of residence, age, gender, ethnicity, race, income, and education. Logit regression is an appropriate method to assess the change in the probability in watching participation attributable to all of these variables. Logit regression helps eliminate the confounding effects of cross correlation among these variables. For example, the participation rate increases as income increases and as age increases. However, income also tends to increase with age. This cross correlation acts to conceal the independent impact that age and income have on participation. By using regression, the effect of each on the probability of wildlife watching can be isolated more effectively. Additionally, regression permits assessment of whether the correlations of the different variables with wildlife watching are significant. In other words it permits an assessment of the probability that the observed relationship occurred by chance. The logit regression used here models the logarithm of the odds ratio that an individual participated in wildlife watching in 2000 as a function of a set of explanatory variables or hunter characteristics. All wildlife watching, both around-the-home and away-from-home, is grouped together in this model.4 The logit regression is described by the following two equations. (1) (2) where: Pi = Probability that the ith individual wildlife watched in 2000 (i.e., “yes”) Xi = Vector of explanatory variables β = Vector of coefficients to be estimated Variables The explanatory variables that are used in the logit regression model are contained in Table 9. Many of the variables are nominal variables. Each nominal variable used in the logit has a base or reference case. The reference case is given a value of 0 in the estimated equation. Consequently, the calculated coefficient for the reference case is embodied in the coefficient for the intercept term. The reference case for each nominal variable is given by the first level for each in Table 9. Thus, the reference case is as follows: Neither Hunted nor Fished from 1995-2000 White race Not Hispanic Male Lives in MSA of more than one million people More than 5 years of college education Never married or widowed Lives in Pacific or Middle Atlantic or East North Central regions5 Every variable value other than the reference case has a coefficient. Each of these coefficients indicate the change in the log odds ratio from equation 2 that occurs when the value of the respective nominal variable is different than the reference case. For example, since “Neither Hunted nor Fished from 1995-2000” is the reference case for HUNT_FISH, each of the other levels (Both Hunted and Fished, Fished Only, Hunted Only) will have a coefficient. The coefficient for “Fished Only” will indicate the change in the log odds that results because a wildlife watcher in 2000 went fishing but not hunting from 1995-2000. The same will also be the case for the “Both Hunted and Fished” and “Hunted Only” coefficients. These results for the HUNT_FISH variable are the primary focus of this analysis. Results The results from the logistic regression procedure are presented in Table 10. A negative number in the Estimation column indicates that the variable in question has a negative relationship with the likelihood that one participated in wildlife watching in 2000. Additionally, the Pr > ChiSq column indicates the probability that the relationship between each variable and the target variable (likelihood of wildlife watching) occurs by chance. A Pr > ChiSq of less than 0.05 is considered strongly statistically significant, while a value of less than 0.1 is considered significant. An example will serve to explain the particulars of Table 10. The table indicates that the estimate for “Fished Only” is 0.975. Since the base case for HUNT_FISH is “Neither Hunted nor Fished,” the positive result indicates that, all other things equal, individuals that went fishing but not hunting from 1995-2000 were more likely to participate in wildlife watching in 2000. Part Five–Wildlife-Watching Participation Model 4 Independent models for away-from-home and around-the-home watching were also estimated by the author, and the results are available by request. 5 These regions were grouped together because differences in likelihood of wildlife watching between them were found insignificant. The Relationship between Wildlife Watchers, Hunters, and Anglers 23 Additionally, the Pr > ChiSq indicates a probability of <.0001, which is strongly significant. This significance indicates that there is greater than a 99.99% probability that the relationship between “Fished Only” and wildlife watching did not occur by chance. The results here confirm the statistical significance of several of the relationships that appear in Table 6. All other things equal, as income increases and as age increases the likelihood of participation in wildlife watching also increases. Being Hispanic indicates lower likelihood of participation in wildlife watching. The negative coefficients for all the values of RACE indicate that each has a lower likelihood of participation in wildlife watching than Whites, which is the reference case value. The reference case for MSA is metropolitan areas of one million people or more. Consequently, the positive coefficients for all the values of MSAs of less than one million people indicate that all individuals that reside in smaller MSAs and outside MSAs are more likely to participate in wildlife watching. Moreover, the coefficients for “50,000-249,999” and “Outside MSA” are notably larger than that of “250,000- 999,999,” which indicates that those who reside in the smallest MSAs and outside MSAs are the most likely to participate in wildlife watching.6 The positive coefficient for “Female” indicates that women are more likely to participate than men. Those who are either “Divorced” or “Married” are more likely to participate than those who have never married or are widowed. It is possible that those who are divorced or married are more likely to participate in wildlife watching because they are also more likely have children, and those with children are more likely to participate in wildlife watching. Residents of several regions have significantly lower likelihood of participation in wildlife watching than the base case of Pacific, East North Central, and Middle Atlantic, and residents in only one region are significantly more likely. Individuals in the East South Central, Mountain, South Atlantic, West North Central, and West South Central are all 6 Linear hypotheses tests on the regression coefficients indicate that the differences between ���Outside MSA” and “250,000- 999,999” are significant at the 0.01 level. Likewise, the differences between “50,000- 249,999” and “250,000-999,999” are also significant at the 0.01 level. Table 9. Logit Regression Explanatory Variables Age Age of recreationist in years for those older than 15 INCOME Ordinal variable with 10 levels, treated as continuous Under $10,000 $10,000-$19,999 $20,000-$24,999 $25,000-$29,999 $30,000-$34,999 $35,000-$39,999 $40,000-$49,999 $50,000-$74,999 $75,000-$99,999 $100,000 or More HUNT_FISH Nominal variable with 4 levels that indicate hunting and fishing activity from 1995-2000 Neither hunted or fished Both hunted and fished Fished only Hunted only RACE Nominal variable with 3 levels to indicate race White Asian Black Other HISPANIC Indicator variable with 2 values to indicate ethnicity Not Hispanic Hispanic SEX Indicator variable with 2 values to indicate respondent gender Male Female MSA Nominal variable with 4 levels to indicate size of residence 1,000,000 or more 250,000-999,999 50,000-249,999 Outside MSA EDUC Nominal variable with 5 levels to indicate years of education 5 years or more of college 4 years of college 1-3 years of college 12 years 11 Years or less MARITAL Nominal variable with 3 levels to indicate marital status Never Married or Widowed Married or Divorced CENDIV Nominal variable with 9 levels to indicate geographic region of residence Pacific/East North Central/Middle Atlantic East South Central Mountain New England South Atlantic West North Central West South Central 24 The Relationship between Wildlife Watchers, Hunters, and Anglers significantly less likely to participate in wildlife watching than those in the Pacific, East North Central, or Middle Atlantic. Only individuals in New England are significantly more likely to participate. Individuals who participated in hunting or fishing from 1995-2000 are significantly more likely to have participated in wildlife watching in 2000 than those who did not. This is indicated by the positive coefficients for “Hunted and Fished,” “Fished Only,” and “Hunted Only.” Moreover, those who both “Hunted and Fished” have the highest likelihood of participation in wildlife watching, followed by those who “Fished Only,” and then those who “Hunted Only.”7 These results suggests that even after controlling for other factors that are also correlated, there is still a statistically significant increase in likelihood of wildlife watching participation given participation in hunting or fishing within five years prior to the survey. Calculated Probabilities The results in Table 10 can be used to directly calculate the probability that an individual participated in wildlife watching in 2000 if appropriate values of the explanatory variables are known. To refrain from a discussion about how to use the results, several tables are created that exhibit the results of the regression procedure. Tables 11 and 12 show the probability, expressed as a percent, that individuals participated in wildlife watching in 2000. Table 11 shows the probabilities for individuals who have never married or are widowed. Table 12 shows the probabilities for individuals who are either married or divorced. Each cell in Tables 11-12 contains the probability that an individual participated in wildlife watching in 2000. For example, the first row and first column of Table 11 indicates the following: a White male who lives in the Pacific region in a metropolitan statistical area with greater than one million residents has a probability of wildlife watching participation of 33%. If the individual is otherwise the same, but did participate in both hunting and fishing within 5 years prior to 2000, the probability of wildlife watching rises to 68%. This is displayed in the second row and first column from the left in Table 11. The probabilities are calculated using the mean value of income, age, and education. The probabilities shown will certainly change for individuals that do not have mean income, age, and education. The means are used to convey an understanding of how 7 Linear hypotheses tests indicate that all pairwise comparisons for differences between coefficients for “Fish Only,” Hunt Only,” and “Hunt and Fish” are all significant at the 0.05 level. Table 10. Analysis of Maximum Likelihood Estimates of Logit Regression Variable Value Estimate Standard Error Chi-Square Pr > ChiSq Intercept -1.558 0.070 490.7 <.0001 AGE 0.018 0.001 614.0 <.0001 INCOME 0.044 0.005 84.5 <.0001 HUNT_FISH Fished Only 0.975 0.027 1285.1 <.0001 HUNT_FISH Hunted Only 0.798 0.078 105.9 <.0001 HUNT_FISH Hunted and Fished 1.439 0.038 1411.6 <.0001 RACE Asian -1.259 0.080 249.7 <.0001 RACE Black -0.989 0.045 476.4 <.0001 RACE Other -0.355 0.089 15.7 <.0001 HISPANIC Hispanic -0.572 0.049 134.8 <.0001 SEX Female 0.432 0.025 309.5 <.0001 MSA 250,000-999,999 0.091 0.032 8.3 0.004 MSA 50,000-249,999 0.291 0.042 49.0 <.0001 MSA Outside MSA 0.260 0.031 72.7 <.0001 EDUC 0-11 years -0.674 0.050 182.3 <.0001 EDUC 1-3 years of college -0.296 0.040 55.8 <.0001 EDUC 12 years -0.582 0.039 218.0 <.0001 EDUC 4 years of college -0.277 0.041 45.1 <.0001 MARITAL Married/Divorced 0.242 0.027 80.1 <.0001 CENDIV East South Central -0.226 0.047 23.0 <.0001 CENDIV Mountain -0.174 0.037 22.4 <.0001 CENDIV New England 0.152 0.037 16.6 <.0001 CENDIV South Atlantic -0.108 0.034 10.0 0.001 CENDIV West North Central -0.112 0.040 7.7 0.005 CENDIV West South Central -0.445 0.050 80.8 <.0001 The Relationship between Wildlife Watchers, Hunters, and Anglers 25 different categorical variables affect the probability of wildlife watching. The mean values used in these calculations are income of $30,000-39,9999, age of 50, and education of 1-3 years of college. There is no implication of causality in the probabilities. In the example previously mentioned, it was indicated that the probability that a White male individual who lives in the Pacific region in a metropolitan statistical area with greater than one million residents has a probability of wildlife watching participation of 33%, and if he also participated in hunting and fishing this probability rises to 68%. It should not be interpreted that participating in hunting and fishing causes the probability of wildlife watching to increase 35%. The modeling performed here makes use of what data are available from the FHWAR screen. The reality is that there are likely variables excluded from the modeling that affect both the likelihood of participation in wildlife watching and the likelihood of participation in hunting and fishing. This is referred to as a confounding variables impact. One variable that is often discussed as having a substantial impact on participation in wildlife recreation is exposure to the activity at an early age. The real cause of the high association of non-consumptive recreation (wildlife watching) and consumptive recreation (hunting and fishing) could be childhood exposure to both types of activities. The data available do not permit an analysis of this impact. What is known is that, whatever the cause, individuals who participate in hunting and fishing have a higher probability of participation in wildlife watching than those who do not. With these clarifications in mind, there are several interesting aspects of Tables 11 and 12 that merit some discussion. The tables clearly indicate that the impact of urbanization on the probability of wildlife watching is relatively small when compared to that of hunting and fishing activity, race, and sex. The previous example indicated that the probability that a White male who lives in the Pacific region in a MSA with greater than one million residents has a probability of wildlife watching participation of 33%. If the only change is that the individual resides outside of a MSA, this probability rises to 39%. All other things equal, income, sex, marital status, education, etc., the change in probability resulting from a change in metropolitan status alone is relatively small. By comparison, if the individual is Asian rather than White, then the probability falls from 33% to 12%. The change in probability resulting from variation in race is on par with that of prior hunting and fishing activity. The largest relative changes in wildlife watching participation are observed when race and prior hunting and fishing activity are varied. There is relatively little variation in wildlife watching probability from changes in geographic region. Lastly, relatively moderate changes in wildlife watching probabilities are observed when gender and marital status are changed. 26 The Relationship between Wildlife Watchers, Hunters, and Anglers continues Table 11. Probability of Never Married/Widowed Individuals with Mean Income, Age, and Education Participating in Wildlife Watching in 2000 MSA of 1 million or more MSA of 250,000-999,999 MSA of 50,000-249,999 Outside MSA Gender Region Hunt/Fish White Asian Black Other White Asian Black Other White Asian Black Other White Asian Black Other Male Pac./Mid Atl./East N. Cent. Did not Hunt or Fish 33% 12% 16% 26% 35% 13% 17% 27% 40% 16% 20% 32% 39% 15% 19% 31% Hunted and Fished 68% 37% 44% 59% 69% 39% 46% 61% 74% 44% 51% 66% 73% 43% 50% 65% Fished Only 57% 27% 33% 48% 59% 29% 35% 50% 64% 33% 39% 55% 63% 32% 39% 54% Hunted Only 52% 24% 29% 43% 55% 25% 31% 46% 59% 29% 35% 51% 59% 29% 35% 50% East South Central Did not Hunt or Fish 28% 10% 13% 22% 30% 11% 14% 23% 34% 13% 16% 27% 34% 13% 16% 26% Hunted and Fished 62% 32% 38% 54% 64% 34% 40% 56% 69% 39% 45% 61% 68% 38% 44% 60% Fished Only 51% 23% 28% 42% 53% 24% 30% 44% 58% 28% 34% 49% 57% 28% 33% 49% Hunted Only 47% 20% 25% 38% 49% 21% 26% 40% 54% 25% 30% 45% 53% 24% 30% 44% Mountain Did not Hunt or Fish 29% 11% 13% 23% 31% 11% 14% 24% 36% 14% 17% 28% 35% 13% 17% 27% Hunted and Fished 64% 33% 39% 55% 66% 35% 42% 57% 70% 40% 47% 62% 69% 39% 46% 61% Fished Only 52% 24% 29% 44% 55% 25% 31% 46% 60% 29% 35% 51% 59% 29% 35% 50% Hunted Only 48% 21% 26% 39% 50% 22% 27% 41% 55% 26% 31% 46% 54% 25% 31% 46% New England Did not Hunt or Fish 36% 14% 18% 29% 39% 15% 19% 31% 43% 18% 22% 35% 43% 17% 22% 34% Hunted and Fished 71% 41% 47% 63% 73% 43% 50% 65% 76% 48% 55% 69% 76% 47% 54% 69% Fished Only 60% 30% 36% 52% 62% 32% 38% 54% 67% 37% 43% 59% 66% 36% 42% 58% Hunted Only 56% 27% 32% 47% 58% 28% 34% 49% 63% 33% 39% 54% 62% 32% 38% 54% South Atlantic Did not Hunt or Fish 31% 11% 14% 24% 33% 12% 15% 25% 37% 14% 18% 29% 36% 14% 18% 29% Hunted and Fished 65% 35% 41% 57% 67% 37% 43% 59% 71% 41% 48% 64% 71% 41% 47% 63% Fished Only 54% 25% 30% 45% 56% 27% 32% 47% 61% 31% 37% 52% 60% 30% 36% 52% Hunted Only 50% 22% 27% 41% 52% 23% 29% 43% 57% 27% 33% 48% 56% 27% 32% 47% West North Central Did not Hunt or Fish 31% 11% 14% 24% 33% 12% 15% 25% 37% 14% 18% 29% 36% 14% 18% 29% Hunted and Fished 65% 35% 41% 57% 67% 37% 43% 59% 71% 41% 48% 64% 71% 41% 47% 63% Fished Only 54% 25% 30% 45% 56% 27% 32% 47% 61% 31% 37% 52% 60% 30% 36% 52% Hunted Only 49% 22% 27% 41% 52% 23% 29% 43% 57% 27% 33% 48% 56% 27% 32% 47% West South Central Did not Hunt or Fish 24% 8% 11% 18% 26% 9% 11% 20% 30% 11% 14% 23% 29% 10% 13% 22% Hunted and Fished 57% 27% 33% 48% 59% 29% 35% 51% 64% 34% 40% 56% 63% 33% 39% 55% Fished Only 46% 19% 24% 37% 48% 21% 25% 39% 53% 24% 29% 44% 52% 24% 29% 43% Hunted Only 41% 17% 21% 33% 43% 18% 22% 35% 48% 21% 26% 40% 48% 21% 25% 39% The Relationship between Wildlife Watchers, Hunters, and Anglers 27 Table 11. Probability of Never Married/Widowed Individuals with Mean Income, Age, and Education Participating in Wildlife Watching in 2000 – continued MSA of 1 million or more MSA of 250,000-999,999 MSA of 50,000-249,999 Outside MSA Gender Region Hunt/Fish White Asian Black Other White Asian Black Other White Asian Black Other White Asian Black Other Female Pacific Did not Hunt or Fish 43% 18% 22% 35% 45% 19% 24% 37% 50% 22% 27% 42% 50% 22% 27% 41% Hunted and Fished 76% 48% 54% 69% 78% 50% 57% 71% 81% 55% 61% 75% 81% 54% 61% 74% Fished Only 67% 36% 43% 59% 69% 38% 45% 61% 73% 43% 50% 65% 72% 43% 49% 65% Hunted Only 63% 32% 39% 54% 65% 34% 41% 56% 69% 39% 46% 61% 69% 38% 45% 61% East South Central Did not Hunt or Fish 38% 15% 18% 30% 40% 16% 20% 32% 45% 19% 23% 36% 44% 18% 23% 36% Hunted and Fished 72% 42% 49% 64% 74% 44% 51% 66% 77% 49% 56% 71% 77% 48% 55% 70% Fished Only 62% 31% 37% 53% 64% 33% 40% 55% 68% 38% 44% 60% 68% 37% 44% 59% Hunted Only 57% 28% 33% 49% 60% 29% 35% 51% 64% 34% 40% 56% 64% 33% 39% 55% Mountain Did not Hunt or Fish 39% 15% 19% 31% 41% 17% 21% 33% 46% 20% 24% 37% 45% 19% 24% 37% Hunted and Fished 73% 43% 50% 65% 75% 46% 52% 67% 78% 51% 57% 72% 78% 50% 56% 71% Fished Only 63% 32% 39% 54% 65% 34% 41% 57% 69% 39% 46% 61% 69% 38% 45% 61% Hunted Only 59% 29% 35% 50% 61% 31% 37% 52% 65% 35% 41% 57% 65% 34% 41% 56% New England Did not Hunt or Fish 47% 20% 25% 38% 49% 22% 26% 40% 54% 25% 31% 45% 53% 25% 30% 45% Hunted and Fished 79% 51% 58% 72% 80% 54% 60% 74% 83% 59% 65% 78% 83% 58% 64% 77% Fished Only 70% 40% 47% 62% 72% 42% 49% 64% 76% 47% 54% 69% 75% 46% 53% 68% Hunted Only 66% 36% 42% 58% 68% 38% 44% 60% 72% 43% 49% 65% 72% 42% 49% 64% South Atlantic Did not Hunt or Fish 41% 16% 20% 32% 43% 18% 22% 34% 48% 21% 25% 39% 47% 20% 25% 38% Hunted and Fished 74% 45% 52% 67% 76% 47% 54% 69% 79% 52% 59% 73% 79% 51% 58% 72% Fished Only 64% 34% 40% 56% 66% 36% 42% 58% 71% 41% 47% 63% 70% 40% 47% 62% Hunted Only 60% 30% 36% 51% 62% 32% 38% 54% 67% 37% 43% 59% 66% 36% 42% 58% West North Central Did not Hunt or Fish 40% 16% 20% 32% 43% 17% 22% 34% 48% 21% 25% 39% 47% 20% 25% 38% Hunted and Fished 74% 45% 52% 67% 76% 47% 54% 69% 79% 52% 59% 73% 79% 51% 58% 72% Fished Only 64% 34% 40% 56% 66% 36% 42% 58% 71% 41% 47% 63% 70% 40% 46% 62% Hunted Only 60% 30% 36% 51% 62% 32% 38% 54% 67% 36% 43% 59% 66% 36% 42% 58% West South Central Did not Hunt or Fish 33% 12% 15% 25% 35% 13% 17% 27% 39% 16% 19% 31% 39% 15% 19% 31% Hunted and Fished 67% 37% 43% 59% 69% 39% 46% 61% 73% 44% 51% 66% 73% 43% 50% 65% Fished Only 56% 27% 32% 47% 59% 29% 34% 50% 63% 33% 39% 55% 63% 32% 38% 54% Hunted Only 52% 23% 29% 43% 54% 25% 31% 45% 59% 29% 35% 50% 58% 28% 34% 50% 28 The Relationship between Wildlife Watchers, Hunters, and Anglers continues Table 12. Probability of Married/Divorced Individuals with Mean Income, Age, and Education Participating in Wildlife Watching in 2000 MSA of 1 million or more MSA of 250,000-999,999 MSA of 50,000-249,999 Outside MSA Gender Region Hunt/Fish White Asian Black Other White Asian Black Other White Asian Black Other White Asian Black Other Male Pac./Mid Atl./East N. Cent. Did not Hunt or Fish 39% 15% 19% 31% 41% 16% 20% 33% 46% 19% 24% 37% 45% 19% 23% 36% Hunted and Fished 73% 43% 50% 65% 74% 45% 52% 67% 78% 50% 57% 71% 77% 49% 56% 71% Fished Only 62% 32% 38% 54% 65% 34% 40% 56% 69% 39% 45% 61% 68% 38% 45% 60% Hunted Only 58% 28% 34% 49% 60% 30% 36% 52% 65% 35% 41% 57% 64% 34% 40% 56% East South Central Did not Hunt or Fish 33% 12% 16% 26% 35% 13% 17% 28% 40% 16% 20% 32% 39% 16% 19% 31% Hunted and Fished 68% 37% 44% 60% 70% 40% 46% 62% 74% 45% 51% 66% 73% 44% 50% 66% Fished Only 57% 27% 33% 48% 59% 29% 35% 50% 64% 34% 40% 55% 63% 33% 39% 55% Hunted Only 53% 24% 29% 44% 55% 26% 31% 46% 60% 30% 36% 51% 59% 29% 35% 50% Mountain Did not Hunt or Fish 35% 13% 16% 27% 37% 14% 18% 29% 41% 17% 21% 33% 41% 16% 20% 32% Hunted and Fished 69% 39% 45% 61% 71% 41% 48% 63% 75% 46% 53% 68% 74% 45% 52% 67% Fished Only 58% 28% 34% 50% 61% 30% 36% 52% 65% 35% 41% 57% 64% 34% 40% 56% Hunted Only 54% 25% 30% 45% 56% 27% 32% 47% 61% 31% 37% 52% 60% 30% 36% 52% New England Did not Hunt or Fish 42% 17% 21% 34% 44% 19% 23% 36% 49% 22% 27% 41% 49% 21% 26% 40% Hunted and Fished 76% 47% 53% 68% 77% 49% 56% 70% 81% 54% 61% 74% 80% 53% 60% 74% Fished Only 66% 35% 42% 58% 68% 38% 44% 60% 72% 42% 49% 65% 72% 42% 48% 64% Hunted Only 62% 32% 38% 53% 64% 34% 40% 55% 68% 38% 45% 60% 68% 37% 44% 60% South Atlantic Did not Hunt or Fish 36% 14% 17% 28% 38% 15% 19% 30% 43% 18% 22% 35% 42% 17% 21% 34% Hunted and Fished 70% 40% 47% 63% 72% 42% 49% 65% 76% 47% 54% 69% 76% 47% 53% 68% Fished Only 60% 30% 36% 51% 62% 32% 38% 53% 67% 36% 43% 58% 66% 35% 42% 58% Hunted Only 56% 26% 32% 47% 58% 28% 34% 49% 63% 32% 38% 54% 62% 32% 38% 53% West North Central Did not Hunt or Fish 36% 14% 17% 28% 38% 15% 19% 30% 43% 18% 22% 34% 42% 17% 21% 34% Hunted and Fished 70% 40% 47% 62% 72% 42% 49% 65% 76% 47% 54% 69% 75% 47% 53% 68% Fished Only 60% 30% 36% 51% 62% 32% 38% 53% 67% 36% 43% 58% 66% 35% 42% 57% Hunted Only 55% 26% 32% 47% 58% 28% 34% 49% 63% 32% 38% 54% 62% 31% 38% 53% West South Central Did not Hunt or Fish 29% 10% 13% 22% 31% 11% 14% 24% 35% 13% 17% 27% 34% 13% 16% 27% Hunted and Fished 63% 33% 39% 54% 65% 35% 41% 57% 69% 39% 46% 61% 69% 38% 45% 61% Fished Only 52% 23% 28% 43% 54% 25% 30% 45% 59% 29% 35% 50% 58% 28% 34% 49% Hunted Only 47% 20% 25% 39% 49% 22% 27% 41% 54% 25% 31% 46% 54% 25% 30% 45% The Relationship between Wildlife Watchers, Hunters, and Anglers 29 Table 12. Probability of Married/Divorced Individuals with Mean Income, Age, and Education Participating in Wildlife Watching in 2000 – continued MSA of 1 million or more MSA of 250,000-999,999 MSA of 50,000-249,999 Outside MSA Gender Region Hunt/Fish White Asian Black Other White Asian Black Other White Asian Black Other White Asian Black Other Female Pacific Did not Hunt or Fish 49% 22% 26% 40% 51% 23% 28% 43% 56% 27% 32% 48% 56% 26% 32% 47% Hunted and Fished 80% 54% 60% 74% 82% 56% 62% 76% 85% 61% 67% 79% 84% 60% 66% 79% Fished Only 72% 42% 49% 64% 74% 44% 51% 66% 77% 49% 56% 71% 77% 49% 55% 70% Hunted Only 68% 38% 44% 60% 70% 40% 47% 62% 74% 45% 52% 67% 74% 44% 51% 66% East South Central Did not Hunt or Fish 44% 18% 22% 35% 46% 19% 24% 37% 51% 23% 28% 42% 50% 22% 27% 41% Hunted and Fished 76% 48% 55% 70% 78% 50% 57% 71% 81% 55% 62% 75% 81% 54% 61% 75% Fished Only 67% 37% 43% 59% 69% 39% 45% 61% 73% 44% 50% 66% 73% 43% 50% 65% Hunted Only 63% 33% 39% 55% 65% 35% 41% 57% 70% 39% 46% 62% 69% 39% 45% 61% Mountain Did not Hunt or Fish 45% 19% 23% 36% 47% 20% 25% 38% 52% 24% 29% 43% 51% 23% 28% 43% Hunted and Fished 77% 49% 56% 71% 79% 52% 58% 72% 82% 57% 63% 76% 82% 56% 62% 76% Fished Only 68% 38% 44% 60% 70% 40% 47% 62% 74% 45% 52% 67% 74% 44% 51% 66% Hunted Only 64% 34% 40% 56% 66% 36% 42% 58% 71% 41% 47% 63% 70% 40% 47% 62% New England Did not Hunt or Fish 53% 24% 30% 44% 55% 26% 31% 46% 60% 30% 36% 51% 59% 29% 35% 51% Hunted and Fished 83% 57% 64% 77% 84% 60% 66% 78% 86% 64% 70% 82% 86% 64% 70% 81% Fished Only 75% 46% 53% 68% 77% 48% 55% 70% 80% 53% 60% 74% 79% 52% 59% 73% Hunted Only 71% 42% 48% 64% 73% 44% 50% 66% 77% 49% 55% 70% 76% 48% 55% 69% South Atlantic Did not Hunt or Fish 46% 20% 24% 38% 49% 21% 26% 40% 54% 25% 30% 45% 53% 24% 30% 44% Hunted and Fished 79% 51% 58% 72% 80% 53% 60% 74% 83% 58% 65% 77% 83% 57% 64% 77% Fished Only 70% 40% 46% 62% 72% 42% 48% 64% 75% 47% 53% 68% 75% 46% 53% 68% Hunted Only 66% 35% 42% 57% 68% 37% 44% 60% 72% 42% 49% 64% 71% 42% 48% 64% West North Central Did not Hunt or Fish 46% 20% 24% 38% 49% 21% 26% 40% 54% 25% 30% 45% 53% 24% 29% 44% Hunted and Fished 78% 51% 58% 72% 80% 53% 60% 74% 83% 58% 64% 77% 83% 57% 64% 77% Fished Only 70% 39% 46% 62% 71% 42% 48% 64% 75% 47% 53% 68% 75% 46% 52% 68% Hunted Only 66% 35% 42% 57% 68% 37% 44% 60% 72% 42% 49% 64% 71% 41% 48% 64% West South Central Did not Hunt or Fish 38% 15% 19% 30% 40% 16% 20% 32% 45% 19% 24% 37% 45% 19% 23% 36% Hunted and Fished 72% 43% 49% 65% 74% 45% 52% 67% 78% 50% 57% 71% 77% 49% 56% 70% Fished Only 62% 32% 38% 54% 64% 34% 40% 56% 69% 38% 45% 61% 68% 38% 44% 60% Hunted Only 58% 28% 34% 49% 60% 30% 36% 51% 65% 34% 41% 56% 64% 34% 40% 56% 30 The Relationship between Wildlife Watchers, Hunters, and Anglers Often the populations of all wildlife recreationists are divided into groups of either wildlife watchers or sportspersons. Sometimes these two groups of recreationists are perceived as mutually exclusive or nearly exclusive. However, they are really interrelated from numerous perspectives. This report analyzes several aspects of their interrelationship. Perhaps the most tangible evidence against the notion of two mutually exclusive groups of recreationists is the magnitude of their intersection. The majority of sportspersons also participate in wildlife watching. Alternatively, 32% of all around-the-home and 44% of all away-from-home wildlife watchers are also sportspersons. Moreover, these percentages rise substantially if an individual’s prior historical participation in sporting activities is considered. If a recreationist is still considered a sportsperson if he or she participated in either hunting or fishing within the last five years, sportsperson share of around-the- home and away-from-home watchers increases to 49% and 63% respectively. Further, this report uses regression analysis to show the increase in the probability of wildlife watching participation given information on prior hunting and fishing activity. The results suggests that even after controlling for other factors that are also correlated, there is still a statistically significant increase in likelihood of wildlife watching given participation in hunting or fishing within five years prior to the survey. Additionally, the probabilities generated from the regression indicate that, compared to other variables, there are relatively large changes in wildlife-watching participation due to changes in prior hunting and fishing activity. From the perspective of spending in the marketplace and subsequent impact on the economy, there is substantial interrelationship between consumptive and non-consumptive recreationists. This report shows that the majority of wildlife-recreation expenditures are made by those who participate in both wildlife watching and sporting activities. Those who participate in both watching and sporting activities account for 57% of all spending, while those who participate in only wildlife watching and only sporting activities each account for around 21%. In the years ahead the interrelationship of consumptive and non-consumptive recreationists will likely experience change due to the distinctive socioeconomic characteristics of each. Demographic trends in the U.S. portend several changes in the participation rates for different types of wildlife recreation. Relatively fast growth in metropolitan populations, relatively slow growth in the population of Whites compared to other races, rapid population growth in Hispanics, and an aging populace will likely have two effects: the overall participation rate for wildlife watching will increase relative to sporting activities, and the share of recreationists who participate in both wildlife watching and sporting activities will likely decline. Summary The Relationship between Wildlife Watchers, Hunters, and Anglers 31 The analysis for this report is based on information collected by the 2001 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation. The questions used to collect the information are provided below. An away-from-home wildlife watcher is someone who answered yes to the following question: “From January 1, 2001 to December 31, 2001 did you take any trips or outings in the United States of at least one mile from home for the primary purpose of observing, photographing, or feeding wildlife? Do not include trips to zoos, circuses, aquariums, museums, or trips for hunting, fishing, or scouting.” An around-the-home wildlife watcher is someone who answered yes to one of the following questions: “From January 1, 2001 to December 31, 2001 did you take any special interest in wildlife around your home (area within a one-mile radium of your home), other than simply noticing wildlife while doing other activities? By this I mean, did you closely observe wildlife or try to identify types of wildlife you did not know? “From January 1, 2001 to December 31, 2001 did you photograph any type of wildlife around your home?” “From January 1, 2001 to December 31, 2001 did you feed wild birds around your home?” “From January 1, 2001 to December 31, 2001 did you feed any kind of fish or wildlife, other than birds, around your home?” “From January 1, 2001 to December 31, 2001 did you visit any public parks or publicly-owned natural areas within a one-mile radius of your home, for the purpose of observing photographing, or feeding wildlife?” “During 2001, did you maintain in the area around your home any plantings, such as food or cover plants, for the PRIMARY PURPOSE of benefiting fish or wildlife? Include areas in agricultural crops.” Appendix A. Wildlife-Watching Questions 32 The Relationship between Wildlife Watchers, Hunters, and Anglers Appendix B. Wildlife-Watching Days by State Table B-1. Wildlife-Watching Days Away from Home by Sportsperson Classification and State Where Watching Occurred: 2001 (Population 16 years of age and older. Numbers in thousands.) All Non-Residential Non-Sportspersons Percent of All Sportspersons Percent of All AK 3,892 1,693 44% 2,199 57% AL 3,643 1,708 47% 1,936 53% AR 1,562 605 39% 957 61% AZ 4,584 2,705 59% 1,879 41% CA 23,807 19,455 82% 4,352 18% CO 9,510 5,119 54% 4,391 46% CT 7,241 4,448 61% 2,793 39% DE 722 311 43% 411 57% FL 21,388 9,026 42% 12,362 58% GA 4,868 1,172 24% 3,696 76% HI 1,718 970 57% 748 44% IA 6,393 2,883 45% 3,511 55% ID 3,610 2,350 65% 1,260 35% IL 7,656 5,051 66% 2,605 34% IN 11,999 5,790 48% 6,209 52% KS 2,416 1,144 47% 1,272 53% KY 5,689 3,293 58% 2,396 42% LA 2,432 679 28% 1,753 72% MA 10,198 6,670 65% 3,528 35% MD 6,809 4,049 60% 2,759 41% ME 4,981 2,749 55% 2,232 45% MI 13,999 5,525 40% 8,473 61% MN 13,234 4,600 35% 8,634 65% MO 12,448 6,451 52% 5,997 48% MS 3,288 ** ** *3,133 *95% MT 4,612 2,627 57% 1,984 43% NC 5,947 3,605 61% 2,342 39% ND 523 255 49% 268 51% NE 2,240 1,062 47% 1,177 53% NH 3,178 2,061 65% 1,117 35% NJ 9,873 5,987 61% 3,886 39% NM 6,381 4,607 72% 1,774 28% NV 1,567 1,032 66% 534 34% NY 21,583 9,829 46% 11,754 55% OH 19,814 11,414 58% 8,399 42% OK 4,058 1,395 34% 2,663 66% OR 8,517 5,984 70% 2,533 30% PA 18,990 13,062 69% 5,928 31% RI 1,414 694 49% 720 51% SC 4,616 1,006 22% 3,610 78% SD 1,923 1,082 56% 840 44% TN 6,144 3,770 61% 2,374 39% TX 7,711 3,327 43% 4,384 57% UT 4,414 1,660 38% 2,754 62% VA 8,906 6,015 68% 2,891 33% VT 3,717 2,885 78% 832 22% WA 11,256 7,039 63% 4,218 38% WI 16,499 6,287 38% 10,212 62% WV 2,619 851 33% 1,768 68% WY 3,924 1,972 50% 1,952 50% *Estimate based on small sample size. **Sample Size too small to report data reliably The Relationship between Wildlife Watchers, Hunters, and Anglers 33 Table B-2. Wildlife-Watching Days Around the Home by Sportsperson Classification and State of Residence: 2001 (Population 16 years of age and older. Numbers in thousands.) All Around the Home Non-Sportspersons Percent of All Sportspersons Percent of All AK 11,921 5,634 47% 6,287 53% AL 72,899 50,496 69% 22,403 31% AR 51,652 29,999 58% 21,653 42% AZ 110,828 89,094 80% 21,735 20% CA 266,148 224,568 84% 41,580 16% CO 76,580 57,537 75% 19,043 25% CT 89,931 67,313 75% 22,617 25% DE 11,028 8,041 73% 2,987 27% FL 162,652 115,772 71% 46,880 29% GA 98,987 53,415 54% 45,572 46% HI 8,815 3,359 38% *5,456 *62% IA 115,051 70,870 62% 44,181 38% ID 22,854 9,801 43% 13,052 57% IL 193,555 128,307 66% 65,247 34% IN 206,598 138,179 67% 68,419 33% KS 49,325 29,595 60% 19,730 40% KY 70,426 52,967 75% 17,459 25% LA 67,055 46,042 69% 21,012 31% MA 127,510 104,150 82% 23,360 18% MD 81,304 53,650 66% 27,654 34% ME 51,707 35,316 68% 16,391 32% MI 192,186 122,855 64% 69,332 36% MN 128,152 56,471 44% 71,681 56% MO 101,873 65,326 64% 36,547 36% MS 52,032 31,211 60% 20,821 40% MT 41,660 22,376 54% 19,284 46% NC 112,606 67,630 60% 44,976 40% ND 8,612 6,447 75% 2,165 25% NE 37,939 24,544 65% 13,395 35% NH 34,369 24,909 73% 9,460 28% NJ 132,869 100,523 76% 32,346 24% NM 49,236 38,248 78% 10,988 22% NV 23,894 18,254 76% *5,639 *24% NY 308,032 215,959 70% 92,073 30% OH 212,353 139,980 66% 72,372 34% OK 87,639 51,232 59% 36,407 42% OR 104,403 77,807 75% 26,596 26% PA 354,204 235,304 66% 118,901 34% RI 17,064 13,759 81% 3,305 19% SC 64,760 40,183 62% 24,577 38% SD 21,101 14,459 69% 6,642 32% TN 126,188 88,188 70% 38,000 30% TX 217,276 125,915 58% 91,362 42% UT 39,115 18,478 47% 20,638 53% VA 203,983 132,863 65% 71,120 35% VT 27,934 20,666 74% 7,267 26% WA 171,757 119,695 70% 52,062 30% WI 226,381 157,428 70% 68,953 31% WV 46,014 33,475 73% 12,539 27% WY 14,049 7,540 54% 6,509 46% *Estimate based on small sample size. 34 The Relationship between Wildlife Watchers, Hunters, and Anglers Appendix C. Selected Characteristics of Wildlife Watchers Table C-1. Selected Characteristics of Away-from-Home Wildlife Watchers by Sportsperson Classification (Population 16 years of age and older. Numbers in thousands.) All Away from Home Non- Sportspersons Percent of All Sportspersons Percent of All Total All Persons 21,823 12,190 56% 9,633 44% Population Size of Residence Metropolitan statistical area (MSA) 16,536 9,906 60% 6,630 40% 1,000,000 or more 10,126 6,354 63% 3,773 37% 250,000 to 999,999 4,191 2,410 58% 1,781 43% 50,000 to 249,999 2,218 1,142 52% 1,077 49% Outside MSA 5,287 2,284 43% 3,003 57% Census Geographic Region New England 1,155 744 64% 411 36% Middle Atlantic 2,849 1,731 61% 1,118 39% East North Central 3,571 1,859 52% 1,712 48% West North Central 2,059 863 42% 1,196 58% South Atlantic 3,469 1,849 53% 1,621 47% East South Central 1,086 556 51% 530 49% West South Central 1,822 787 43% 1,035 57% Mountain 2,020 1,135 56% 885 44% Pacific 3,793 2,667 70% 1,127 30% Age 16-17 688 366 53% 321 47% 18-24 1,364 657 48% 707 52% 25-34 3,770 1,963 52% 1,806 48% 35-44 5,701 2,964 52% 2,738 48% 45-54 4,991 2,918 59% 2,073 42% 55-64 2,929 1,762 60% 1,167 40% 65+ 2,381 1,560 66% 822 35% Sex Male 11,388 4,922 43% 6,466 57% Female 10,436 7,268 70% 3,167 30% Ethnicity Hispanic 890 710 80% 180 20% Non-Hispanic 20,933 11,480 55% 9,453 45% Race White 20,890 11,595 56% 9,295 45% Black 535 327 61% 209 39% Asian 178 *153 *86% ** ** All Others *220 *115 *52% *105 *48% continues The Relationship between Wildlife Watchers, Hunters, and Anglers 35 Table C-1. Selected Characteristics of Away-from-Home Wildlife Watchers by Sportsperson Classification – continued (Population 16 years of age and older. Numbers in thousands.) All Away from Home Non- Sportspersons Percent of All Sportspersons Percent of All Annual Household Income Under $10,000 491 289 59% 202 41% $10,000-$19,999 867 567 66% 299 35% $20,000-$24,999 854 515 60% 339 40% $25,000-$29,999 1,109 625 56% 484 44% $30,000-$34,999 1,459 752 52% 707 49% $35,000-$39,999 1,109 543 49% 567 51% $40,000-$49,999 2,365 1,255 53% 1,110 47% $50,000-$74,999 4,585 2,449 53% 2,136 47% $75,000-$99,999 2,910 1,664 57% 1,247 43% $100,000 or More 2,872 1,705 59% 1,167 41% Not Reported 3,202 1,825 57% 1,377 43% Education 11 years or less 1,845 943 51% 901 49% 12 years 5,938 2,891 49% 3,047 51% 1-3 years of college 5,796 2,934 51% 2,861 49% 4 years of college 4,464 2,787 62% 1,678 38% 5 or more years of college 3,781 2,635 70% 1,146 30% *Estimate based on small sample size. **Sample Size too small to report data reliably 36 The Relationship between Wildlife Watchers, Hunters, and Anglers Table C-2. Selected Characteristics of Around-the-Home Wildlife Watchers by Sportsperson Classification (Population 16 Years of Age and Older. Numbers in Thousands.) All Around the Home Non- Sportspersons Percent of All Sportspersons Percent of All Total All Persons 62,928 42,766 68% 20,162 32% Population Size of Residence Metropolitan statistical area (MSA) 46,889 33,274 71% 13,615 29% 1,000,000 or more 28,152 20,634 73% 7,518 27% 250,000 to 999,999 12,210 8,305 68% 3,905 32% 50,000 to 249,999 6,527 4,335 66% 2,192 34% Outside MSA 16,040 9,492 59% 6,548 41% Census Geographic Region New England 3,765 2,787 74% 978 26% Middle Atlantic 8,452 6,098 72% 2,354 28% East North Central 11,196 7,452 67% 3,744 33% West North Central 5,938 3,507 59% 2,432 41% South Atlantic 10,911 7,286 67% 3,625 33% East South Central 4,390 2,848 65% 1,542 35% West South Central 5,490 3,397 62% 2,093 38% Mountain 4,282 2,821 66% 1,461 34% Pacific 8,504 6,570 77% 1,933 23% Age 16-17 1,504 961 64% 543 36% 18-24 2,694 1,626 60% 1,068 40% 25-34 8,137 4,773 59% 3,364 41% 35-44 14,101 8,590 61% 5,511 39% 45-54 13,899 9,603 69% 4,296 31% 55-64 10,084 7,162 71% 2,922 29% 65+ 12,511 10,051 80% 2,460 20% Sex Male 28,825 15,367 53% 13,458 47% Female 34,103 27,399 80% 6,704 20% Ethnicity Hispanic 2,486 1,990 80% 495 20% Non-Hispanic 60,443 40,776 68% 19,667 33% Race White 59,877 40,377 67% 19,500 33% Black 1,939 1,532 79% 407 21% Asian 593 559 94% ** ** All Others 519 299 58% *220 *42.% continues The Relationship between Wildlife Watchers, Hunters, and Anglers 37 Table C-2. Selected Characteristics of Around-the-Home Wildlife Watchers by Sportsperson Classification (Population 16 Years of Age and Older. Numbers in Thousands.) All Around the Home Non- Sportspersons Percent of All Sportspersons Percent of All Annual Household Income Under $10,000 2,344 1,842 79% 501 21% $10-$19,999 3,728 2,973 80% 755 20% $20-$24,999 2,765 2,061 75% 703 25% $25-$29,999 3,304 2,245 68% 1,059 32% $30-$34,999 3,799 2,405 63% 1,394 37% $35-$39,999 2,950 1,754 60% 1,196 41% $40-$49,999 6,070 3,892 64% 2,177 36% $50-$74,999 11,564 7,410 64% 4,154 36% $75-$99,999 7,349 4,767 65% 2,582 35% $100,000 or More 7,705 5,061 66% 2,644 34% Not Reported 11,351 8,354 74% 2,997 26% Education 11 years or less 6,849 4,796 70% 2,052 30% 12 years 20,255 13,431 66% 6,823 34% 1-3 years of college 15,199 9,717 64% 5,481 36% 4 years of college 11,931 8,651 73% 3,280 28% 5 years or more of college 8,696 6,171 71% 2,525 29% *Estimate based on small sample size. **Sample Size too small to report data reliably 38 The Relationship between Wildlife Watchers, Hunters, and Anglers Appendix D. Expenditures for Wildlife Watching and Sporting Activities Table D-1. Wildlife-Watching Expenditures by Sportsperson Classification: 2001 (Population 16 years of age and older. Numbers in thousands except averages.) All Non- Sportspersons Average Non- Sportsperson Sportspersons Average Sportsperson Total, all items 38,414,486 24,481,139 735 13,933,352 804 Trip-Related Expenditures Total trip-related 8,162,439 4,520,120 436 3,642,319 464 Food and lodging, total 4,818,843 2,770,299 318 2,048,544 309 Food 2,835,868 1,535,602 178 1,300,266 196 Lodging 1,982,975 1,234,697 340 748,278 371 Transportation, total 2,595,542 1,502,425 156 1,093,118 147 Public 702,231 531,225 373 171,007 305 Private 1,893,311 971,200 106 922,111 126 Other trip costs, total 748,054 247,396 66 500,657 192 Guide fees, pack trip or package fees 113,034 50,917 60 62,117 174 Public land use fees 114,813 73,192 28 41,621 33 Private land use fees 50,430 13,428 27 37,002 102 Equipment rental 105,198 57,196 75 48,002 122 Boating costs 326,461 38,025 97 288,435 434 Heating and cooking fuel 38,118 14,638 18 23,480 30 Equipment and Other Expenses Total 30,252,047 19,961,019 649 10,291,033 657 Wildlife-watching equipment, total 7,353,977 4,564,821 150 2,789,158 182 Binoculars, spotting scopes 507,387 305,553 107 201,834 111 Photographic equipment 1,656,755 1,075,910 367 580,845 382 Film and developing 910,423 537,411 63 373,012 75 Commercially prepared bird food 2,034,825 1,363,569 57 671,257 57 Other bulk foods to feed birds 569,867 349,944 42 219,923 49 Feed for other wildlife 503,006 217,753 38 285,253 73 Nest boxes, bird houses, feeders 732,671 469,623 44 263,049 50 Day packs, carrying cases, and special clothing 323,043 173,057 104 149,986 117 Other equipment 116,000 72,001 31 43,999 38 Auxiliary equipment 716,899 319,264 165 397,637 191 Tents, tarps 185,552 70,385 91 115,167 98 Frame packs and backpacking equipment 129,382 56,919 94 72,464 149 Other camping equipment 266,382 111,159 107 155,223 168 Other auxiliary equipment 135,583 80,801 *673 54,783 291 Special equipment 15,468,714 10,446,204 13,531 5,022,512 7,872 Off-the-road vehicle 6,677,688 4,345,544 13,884 2,332,144 10,140 Travel or tent trailer, motor home 6,272,294 4,387,965 17,910 1,884,329 11,216 Boats, boat accessories 996,463 360,152 1,801 636,312 2,419 Cabins ** ** ** ** ** Other Special *572,396 *553,847 *11,077 ** ** Magazines, books 331,955 177,021 36 154,934 46 Land leasing and ownership 4,761,010 3,325,727 10,458 1,435,283 6,056 Membership dues and contributions 920,183 674,276 124 245,907 106 Plantings 699,309 453,706 118 245,602 137 *Estimate based on small sample size. **Sample Size too small to report data reliably The Relationship between Wildlife Watchers, Hunters, and Anglers 39 Table D-2. Sporting Expenditures by Wildlife-Watching Classification: 2001 (Population 16 years of age and older. Numbers in thousands except averages.) All Non-Watchers Average Non-Watcher Wildlife Watchers Average Wildlife Watcher Total, all items 69,976,330 22,153,608 1,491 47,822,722 2,270 Trip-Related Expenditures Total trip-related 19,908,392 6,755,896 492 13,152,495 670 Food and lodging, total 8,330,938 2,843,705 237 5,487,234 315 Food 6,121,645 2,094,846 176 4,026,800 233 Lodging 2,209,293 748,859 277 1,460,434 288 Transportation, total 5,305,077 1,679,980 142 3,625,097 209 Public 586,422 201,928 300 384,494 394 Private 4,718,654 1,478,052 126 3,240,602 189 Other trip costs, total 6,272,377 2,232,212 203 4,040,165 256 Guide fees, pack trip or package fees 1,064,137 338,945 279 725,192 392 Public land use fees 174,772 63,950 43 110,822 43 Private land use fees 463,819 133,710 174 330,109 243 Equipment rental 289,909 104,546 118 185,364 138 Boating costs 2,716,341 974,448 315 1,741,893 324 Heating and cooking fuel 167,131 60,842 38 106,289 33 Bait 1,105,350 444,396 50 660,954 52 Ice 290,917 111,376 22 179,541 24 Equipment and Other Expenses Total 50,067,938 15,397,711 1,203 34,670,227 1,798 Hunting equipment 4,866,399 1,437,191 396 3,429,207 493 Fishing equipment 4,640,715 1,592,844 195 3,047,872 229 Auxillary equipment 2,627,686 684,658 218 1,943,028 252 Camping equipment 739,967 241,742 205 498,225 160 Binoculars, spotting scopes 296,318 56,952 105 239,366 127 Special fishing and hunting clothing, boots, foul weather gear 924,554 232,692 127 691,862 153 Other 666,846 153,271 245 513,575 246 Special equipment 28,819,402 9,564,151 7,567 19,255,252 7,174 Off-the-road vehicle 5,734,891 1,863,008 9,362 3,871,882 7,224 Travel or tent trailer, motor home 13,299,315 4,565,675 13,752 8,733,640 13,233 Boats, boat accessories 6,311,427 2,280,173 3,744 4,031,255 2,999 Cabins 3,161,500 ** ** *2,328,988 *31,903 Other Special 312,270 22,784 92 289,486 462 Magazines, books 307,981 74,500 36 233,481 42 Land leasing and ownership 7,128,486 1,536,556 2,466 5,591,930 3,278 Membership dues and contributions 515,282 109,741 85 405,541 103 Licenses, stamps, tags, and permits 1,161,988 398,072 42 763,915 52 *Estimate based on small sample size. **Sample Size too small to report data reliably 40 The Relationship between Wildlife Watchers, Hunters, and Anglers U.S. Fish & Wildlife Service Division of Federal Aid Washington, DC 20240 http://federalaid.fws.gov March 2005 Cover: USFWS/Thomas Taylor |
| Tag | Library-Source-pubs |
| Date created | 2012-08-08 |
|
|