Are Wildlife Recreationists Conservationists?
Linking Hunting, Birdwatching, and
Cornell Lab of Ornithology, 159 Sapsucker Woods Road, Ithaca, NY 14850, USA
Cornell Lab of Ornithology, 159 Sapsucker Woods Road, Ithaca, NY 14850, USA
ASHLEY DAYER, Cornell Lab of Ornithology, 159 Sapsucker Woods Road, Ithaca, NY 14850, USA
RICHARD STEDMAN, Department of Natural Resources, Cornell University, Fernow Hall, Ithaca, NY 14850, USA
DANIEL DECKER, Department of Natural Resources, Cornell University, Fernow Hall, Ithaca, NY 14850, USA
ABSTRACT There is a widely held assumption that outdoor experiences are a key precursor to pro-
environmental behavior (PEB). We tested the hypothesis that wildlife recreationists are more likely than
non-recreationists to voluntarily engage in different types of PEB, grouped as conservation behaviors and
environmental lifestyle behaviors. Via mail and web-based surveys of rural New York residents (n¼941), we
compared the self-reported PEBs of 4 types of recreationists: hunters, birdwatchers, hunter–birdwatchers
(i.e., individuals who regularly engaged in both activities), and non-nature-based recreationists. We
statistically controlled for group differences in socio-demographic characteristics and environmental beliefs.
We found wildlife recreationists—both hunters and birdwatchers—were 4–5 times more likely than non-
recreationists to engage in conservation behaviors, which included a suite of activities such as
donating to support local conservation efforts, enhancing wildlife habitat on public lands, advocating
for wildlife recreation, and participating in local environmental groups. Moreover, effects were
additive; hunter–birdwatchers had the greatest likelihood of engaging in all types of conservation
behaviors. On the other hand, engagement in environmental lifestyle behaviors such as recycling, energy
conservation, and green purchasing were roughly comparable among all types of wildlife recreationists and
non-recreationists. Our ﬁndings of elevated rates of conservation behaviors among hunters and
birdwatchers despite different demographic attributes and environmental beliefs highlight the similar
conservation potential associated with different types of wildlife recreation. Diversiﬁed strategies that
include programs to encourage both hunting and birdwatching are likely to bring about long-term gains for
conservation. Ó2015 The Wildlife Society.
KEY WORDS birding, birdwatching, citizen science, conservation behavior, human dimensions, hunters, recreation,
rural lands, wildlife-based recreation.
Pro-environmental behaviors (PEB) are actions that gener-
ate positive environmental impacts, promote environmental
quality, and result in sustainable use of natural resources
(Stern 2000, Monroe 2003, Steg et al. 2014). Studies
investigating factors associated with PEB have highlighted
the importance of positive human–environment interactions
and nature-based experiences (Cook and Berrenberg 1981,
Dwyer et al. 1993, Kaplan 2000, Ehrlich and Kennedy 2005,
Nisbet et al. 2009). With its enduring popularity and capacity
to facilitate meaningful direct experiences within nature,
wildlife-based recreation (e.g., hunting, birdwatching) may
represent a particularly important precursor to PEB. Despite
this potential, studies exploring links between wildlife
recreation, environmental concern, and PEB have yielded
inconclusive results, emphasizing the need for additional
research to better understand the relationships between PEB
and speciﬁc recreation activities (Dunlap and Heffernan
1975, Teisl and O’Brien 2003, Thapa 2010, Glowinski and
Moore 2014). The purpose of this study was to characterize
associations between participation in 2 different wildlife
recreation activities (hunting and birdwatching) and engage-
ment in a variety of types of voluntary PEB, including behaviors
speciﬁcally focused on wildlife and habitat conservation.
Considering the sheer numbers of wildlife recreationists
across the United States, their impact on conservation efforts
could be substantial. Results of the most recent National
Survey of Fishing, Hunting, and Wildlife-Associated Recreation
revealed that about 90 million Americans age 16 or older
participated in some form of wildlife recreation during
2011 (U.S. Fish and Wildlife Service 2012a). Trends in
Received: 18 June 2014; Accepted: 1 January 2015
Present address: Biodiversity Lab, North Carolina Museum of Natural
Sciences, Raleigh, NC 27601, USA
Present address: Department of Parks, Recreation, & Tourism
Management, Clemson University, Clemson, SC 29634, USA
The Journal of Wildlife Management; DOI: 10.1002/jwmg.855
Cooper et al. Are Wildlife Recreationists Conservationists? 1
participation, however, vary by recreation activity. For
example, despite a recently documented increase in hunting
at the national level (U.S. Fish and Wildlife Service 2012a),
participation in traditional forms of hunting has generally
been declining for decades (Cordell et al. 2008, U.S. Fish and
Wildlife Service 2013a, Outdoor Foundation 2014). On the
other hand, evidence suggests that participation in non-
consumptive bird-based recreation (e.g., watching, feeding)
over that same time period is relatively stable (U.S. Fish and
Wildlife Service 2013b) or rising (Cordell et al. 2008,
Outdoor Foundation 2014). Depending on the degree to
which these forms of wildlife recreation lead to PEB and
conservation-oriented actions, the trends in participation
may have important implications for wildlife management
(Jacobson et al. 2010).
To date, little empirical research has explored links between
participation in wildlife recreation, such as hunting and
birdwatching, and adoption of PEB (Theodori et al. 1998,
Teisl and O’Brien 2003, Thapa 2010). Nevertheless,
assertions about the conservation value of hunting form
the foundation of the North American Model of Wildlife
Conservation (Mahoney and Jackson 2013), which empha-
sizes the ﬁnancial contributions (e.g., license fees, duck
stamps), management assistance, habitat conservation ethic,
and general advocacy support that hunters provide for natural
resource conservation (Heffelﬁnger et al. 2013, Vrtiska et al.
2013). Assumptions about the conservation value of bird-
watching are based on a variety of factors including citizen
science participation (Hvenegaard 2002, Scott 2013),
positive economic impacts of birdwatchers and birding
(Kerlinger 1993), and bird conservation advocates’ allocation
of money and time to environmental organizations
(McFarlane and Boxall 1996, Scott 2013).
Although evidence suggests that different types of wildlife
recreationists express different attitudes and beliefs about
activity outcomes (Daigle et al. 2002), some scholars have
noted that frameworks segregating non-consumptive and
consumptive forms of wildlife recreation may not be
particularly useful when considering motivations and
ultimate conservation goals (Connelly et al. 1985, Schreyer
et al. 1989). In fact, similarities among hunters and
birdwatchers abound. In the aforementioned study by Daigle
et al. (2002), all 3 groups studied (hunters, wildlife watchers,
and other outdoor recreationist) placed a very high value on
wildlife enjoyment. Additional research has shown that both
hunters and birdwatchers are primarily motivated by being
close to nature (Decker et al. 1980, McFarlane 1994, Adams
et al. 1997, Reis 2009), and both hunters and birdwatchers
are invested in preserving wildlife habitat and ecosystems
that support their favorite recreation activities (U.S. Fish and
Wildlife Service 2012b). Teisl and O’Brien (2003) discov-
ered that wildlife watchers and hunters expressed similar
levels of concern and behaviors for variables such as “interest
in forest management” or “belonging or contributing to
environmental organizations,” challenging earlier assump-
tions that consumptive and appreciate forms of wildlife
recreation were associated with different conservation
orientations (Dunlap and Heffernan 1975). Is it possible
that the similar interests and motivations that cultivate
participation in birdwatching and hunting also lead to similar
adoption of PEB? If so, what are the implications for wildlife
management and conservation?
Public involvement in different forms of PEB can generate
outcomes that beneﬁt wildlife management and conservation
in multiple ways. For example, behaviors such as voluntarily
participating in habitat restoration and improvements may
positively affect local ecosystems. Social activities such as
active participation in environmental groups and informal
wildlife advocacy (e.g., talking about the beneﬁts of wildlife
with friends and family) can also generate positive
environmental impacts. Actions such as voting to support
conservation-oriented policies and donating money to
environmental organizations can beneﬁt conservation efforts
on broader scales. In addition to these conservation
behaviors, another sphere of PEB includes lifestyle behaviors
that are more generic and typically less focused on tangible
impacts on local environmental quality (e.g., recycling,
energy conservation, green purchasing; see Stern 2000,
Nordlund and Garvill 2002, Steg and Vlek 2009). Although
all forms of PEB undoubtedly have important conservation
implications, conservation behaviors are generally most
relevant to wildlife managers. Environmental lifestyle
behaviors, on the other hand, have typically garnered the
most attention from researchers. Few studies have
simultaneously considered the full spectrum of PEB
(L.R. Larson, R. Stedman, C.B. Cooper, and D. Decker,
Cornell Lab of Ornithology, unpublished report), and
even fewer have examined the inﬂuence of wildlife recreation
on these behaviors (Teisl and O’Brien 2003). We hypothe-
sized that people who regularly participate in either
hunting or birdwatching would be more likely than non-
recreationists to participate in all forms of PEB, including
both conservation behaviors and environmental lifestyle
behaviors. Furthermore, we hypothesized an additive
effect, namely that individuals who participated in both
hunting and birdwatching would be the most likely to engage
Our study focused primarily on rural areas of 2 economically
struggling counties of upstate New York. Because of
insufﬁcient numbers of birdwatchers in the 2 focal counties,
we expanded the geographical range to include 8 additional
rural counties in upstate New York with similar demographic
trends such as relatively low population density (<70 people
per square mile) and declining population size (<0%
population growth) over the past 20 years (U.S. Census
Bureau 2013). Although urban areas are growing and now
support more than half of the global population (United
Nations 2010), rural communities are a critical yet poorly
understood component of the conservation landscape. A
growing body of research has challenged traditional
assumptions, revealing a strong and potentially expanding
presence of rural environmentalism (McBeth and Foster
1994, Jones et al. 1999), but many questions remain. For
example, what factors inﬂuence the expression of PEB in
2 The Journal of Wildlife Management 9999
rural communities? On one hand, rural regions contain
substantial wildlife habitat and therefore support many
diverse forms of wildlife recreation (U.S. Fish and Wildlife
Service 2012a), which could foster a pro-environmental ethic
and subsequent PEB. On the other hand, residents of rural
areas experiencing economic and social decline may perceive
conﬂicts between conservation and economic growth
(Marvier et al. 2006), perhaps leading to diminished
expression of PEB. This conservation-recreation dilemma
led to our focus on individuals living in economically
struggling rural communities; therefore, we excluded
residents of the larger towns in each county (3 incorporated
areas had populations over 5,000) from the sample.
To examine the hypothesized links between wildlife
recreation and PEB, we constructed a survey instrument
that assessed participation in wildlife-based recreation,
engagement in different types of PEB, and several other
key behavioral correlates such as socio-demographic char-
acteristics and environmental belief structures. The research
protocols were approved by Cornell Institutional Review
We devised a 2-step process to classify individuals into 1 of 4
categories (hunter, birdwatcher, birdwatcher-hunter, and
non-recreationist) based on 1) self-identiﬁed preferences
and 2) self-reported activity levels. First, we asked respondents
to “choose the ONE nature-based recreation activity that they
enjoyed the most” from the following options: hunting,
birdwatching, other nature-based activity, or no nature-based
activity. This allowed respondents to identify with a particular
group, with an emphasis on wildlife-based recreation
categories. The mutually exclusive self-identiﬁcation approach
alone was inadequate in some cases, however, because it did
not account for 1) respondents who participated in hunting
AND birdwatching on a regular basis or 2) respondents who
did not indicate it was their most enjoyable activity but still
avidly engaged in hunting and/or birdwatching.
To account for alternative scenarios where the primary
self-identiﬁcation criterion was inadequate, we selected a
threshold level of participation above which a birdwatcher or
hunter might become classiﬁed as a dual activity participant
(i.e., a hunter–birdwatcher) or above which a self-identiﬁed
non-recreationist might be classiﬁed as an avid hunter,
birdwatcher, or hunter–birdwatcher. We selected the avid
participation thresholds for each activity based on the
medians of self-reported participation in hunting, bird-
watching, and other nature-based recreation within our
sample (measured as the number of days in the past
12 months a respondent had spent at least some time
participating in activity). Threshold levels for classiﬁcation as
a hunter or birdwatcher independent of the self-identiﬁca-
tion criterion were therefore the median values for the self-
identiﬁed hunters (19 or more days of hunting per year) and
birdwatchers (190 or more days of birdwatching per year).
These median participation rates reported by respondents
were nearly equivalent to the mean participation rates for
hunters (18 days per year for big game hunters, which
represented 97.1% of the hunters in our sample) and
somewhat higher than the mean participation rate for
birdwatchers (110 days per year) in the most recent iteration
of the National Survey of Fishing, Hunting, & Wildlife-
Associated Recreation in the United States (U.S. Fish and
Wildlife Service 2012a). Such asymmetry in participation
frequencies for hunting and birdwatching are not uncom-
mon, particularly when the deﬁnition of birdwatching
includes feeder watching from home. In this study, we
used the term birdwatcher to refer to any form of bird
viewing (deﬁned as taking a trip 1 or more miles from home
for the primary purpose of observing birds and/or closely
observing birds around the home; U.S. Fish and Wildlife
Service 2012a). By adopting the median cutoff point to
identify avid birdwatchers and avid hunters who did not
identify as such, we intentionally sought to minimize the
inﬂuence of casual participants who may not be as invested in
a particular activity.
Using these criteria, if a self-identiﬁed hunter also engaged
in 190 or more days of birdwatching, we classiﬁed him/her as
a hunter–birdwatcher. Similarly, if a self-identiﬁed bird-
watcher also engaged in 19 or more days of hunting, we
classiﬁed him/her as a hunter–birdwatcher. If a respondent
who did not select a most enjoyable activity (i.e., no nature-
based activity) participated in hunting and/or birdwatching
at levels at or above the median thresholds, we classiﬁed him/
her as a hunter, a birdwatcher, or both. We excluded from the
analysis respondents who self-identiﬁed as other types of
nature-based recreationists (e.g., anglers, hikers) and did not
engage in avid hunting or birdwatching (n¼36). We
classiﬁed the remaining individuals as non-recreationists.
It should be noted that although there are many types of
hunters based on level of specialization (Needham et al.
2007), equipment used, and types of species hunted (U.S.
Fish and Wildlife Service 2012a), we did not partition
hunters in this study. Similarly, we did not distinguish
among the many types of recreational birdwatchers (Scott
et al. 2005, Cooper and Smith 2010).
We collected data on the following socio-demographic
characteristics to understand better which are associated with
individuals in each wildlife recreation group: gender, age,
education (college degree or no college degree), and political
orientation (scale: 1 ¼liberal, 4 ¼moderate, 7 ¼conserva-
tive). Previous research has shown that socio-demographic
variables are strongly associated with pro-environmental
beliefs, attitudes, and actions (Vaske et al. 2001, Theodori
and Luloff 2002, Larson et al. 2011).
We also included 3 cognitive antecedents as covariates in
models predicting PEB as a function of wildlife-based
recreation: environmental concern, self-efﬁcacy, and norms
(Stern et al. 1999, Kaiser et al. 2005, Ajzen and Albarracin
2007). Each of these variables has been shown to play an
Cooper et al. Are Wildlife Recreationists Conservationists? 3
important role in behavior prediction, particularly in an
environmental context (Fishbein and Ajzen 2010).
Environmental concern is closely linked to underlying
values (Schultz 2001), and expression of concern may
facilitate individuals’ abilities to assess and evaluate
consequences associated with particular actions (Poortinga
et al. 2004, Schultz et al. 2005). Consequently, environmen-
tal concern is often an important precursor to PEB. We used
items adapted from the “ecological crisis” and “balance of
nature” constructs on the New Ecological Paradigm Scale
(Dunlap et al. 2000) to assess participants’ concerns about
their local environment (2 items, Cronbach’s a¼0.742,
scale: 2¼strongly disagree to 2 ¼strongly agree; e.g., “My
local environment is currently suffering ecological damage”).
Self-efﬁcacy, also called locus of control or perceived
behavioral control, is another essential element in behavior
models (Hines et al. 1986, Oreg and Katz-Gerro 2006,
Fishbein 2008), and may be particularly relevant when one is
assessing the environmental impacts of a particular behavior.
If an individual does not believe that he/she possesses the
skills or ability to complete a task and achieve a desired
outcome that beneﬁts the natural environment, then it is
unlikely he/she will participate in that behavior. We
measured this environmental efﬁcacy using items adapted
from existing instruments assessing perceived behavioral
control in an environmental context (Oreg and Katz-Gerro
2006; 2 items, Cronbach’s a¼0.667, scale: 2¼strongly
disagree to 2 ¼strongly agree; e.g., “My actions can make a
difference when it comes to preserving local environmental
Norms depict social inﬂuence or the amount of pressure
that people perceive they are under from signiﬁcant others to
perform a speciﬁc behavior (Smith and Louis 2008). Norms
emerge from social networks and interactions and typically
include injunctive (i.e., perceptions about how people ought
to act) and descriptive (i.e., perceptions about how people
actually act) components (Cialdini et al. 1991, Minato et al.
2010), including with respect to the natural environment
(Kaiser et al. 2005). We measured environmental norms with
items adapted from existing scales (e.g., Kaiser et al. 2005; 2
items, Cronbach’s a¼0.832; scale: 2¼strongly disagree to
2¼strongly agree; e.g., “Most people in my community
think it is important to protect the natural environment”).
Because of concerns regarding instrument length and the
potential response-time burden for respondents, we used
only 2 items to measure each construct. Though more items
would undoubtedly lead to better construct representation,
the observed values of Cronbach’s a(a statistic that typically
underestimates true reliability on small scales) suggests a
high measurement reliability (Eisinga et al. 2013).
For PEB outcome variables, we inquired about a suite of
behaviors that promote or result in sustainable use of natural
resources (Stern 2000, Monroe 2003, Halpenny 2010). To
capture a range of PEB, we developed a scale with 9 behavior
items, many of which were adapted from existing instru-
ments (Stern 2000, Poortinga et al. 2004, Halpenny 2010,
Steg et al. 2014). Respondents rated their frequency of
carrying out each behavior on the following scale: 1 ¼never,
2¼rarely, 3 ¼occasionally, 4 ¼often, and 5 ¼very often.
Principal components analysis revealed 2 main categories: 1)
environmental lifestyle behaviors (3 items, Cronbach’s
a¼0.785), and 2) conservation behaviors (6 items,
Cronbach’s a¼0.798; Table 1). To facilitate interpretation
and statistical analysis, we converted each item into a
dichotomous scale. Because environmental lifestyle behav-
iors might reasonably be carried out daily (e.g., recycling,
energy conservation), we classiﬁed responses with a mean
score greater than or equal to 4 as frequent and less than 4 as
infrequent. Because conservation behaviors might reasonably
be carried out weekly, monthly, or at longer intervals (e.g.,
habitat enhancement, wildlife recreation advocacy), we
classiﬁed responses with a mean score greater than or equal
to 3 as frequent and responses with a mean score of less than
3 as infrequent. In addition to analyses predicting the 2
composite behavior scales, we also independently examined
predictors for the 6 speciﬁc items on the conservation
behavior subscale. We chose to focus on the speciﬁc
conservation behaviors (and not the environmental lifestyle
Table 1. Factor loadings (Aand B) based on Principal Components Analysis with Varimax rotation for items used to evaluate rural New York residents’
adoption of pro-environmental behavior based on survey results from 2013. We extracted only factors with eigenvalues >1; the 2-factor model accounted for
57.2% of the total variance.
Item code Actual item text Mean
Environmental lifestyle behaviors
Recycling Recycled paper, plastic, metal 4.62 0.67 0.04 0.77
Resource conservation Conserved water or energy in my home 4.40 0.76 0.10 0.87
Green purchasing Bought environmentally friendly and/or energy-efficient products 4.22 0.83 0.16 0.82
Private land habitat enhancement Made my yard or my land more desirable to wildlife 3.95 1.04 0.48 0.36
Conservation policy support Voted to support a policy or regulation that affects the local environment 2.70 1.29 0.66 0.25
Donation to conservation Donated money to support local environmental protection 2.43 1.21 0.69 0.22
Wildlife recreation advocacy Recruited others to participate in wildlife recreation activities 2.31 1.19 0.69 0.04
Public land habitat enhancement Volunteered to improve wildlife habitat in my community 2.12 1.16 0.78 0.06
Join environmental group Participated as an active member in an environmental group 1.89 1.08 0.77 0.02
Scale: 1 ¼never, 2 ¼rarely, 3 ¼sometimes, 4 ¼often, 5 ¼very often.
4 The Journal of Wildlife Management 9999
behaviors) because conservation-oriented actions may
be of particular interest to the wildlife management
In an effort to contact a range of nature-based recreationists
while simultaneously focusing on hunters and birdwatchers,
we used a hybrid approach implemented by mail and
web-based survey (Carrozzino-Lyon et al. 2013) to target
3 populations: hunters, birdwatchers, and landowners
(i.e., individuals who may or may not engage in hunting,
birdwatching, or any form of nature-based recreation).
We collected all survey data from April 2013 through
May 2013 using a multiple mailing or e-mailing approach
with 4 separate contacts at 1-week intervals (Dillman 2007).
On the second week after initial contact, non-respondents
received either a reminder postcard or email. On the
third week, non-respondents received another copy of
the initial questionnaire via mail or web link, followed
by either a reminder postcard or email after 1 additional
We selected hunters by randomly identifying 699
individuals living in 2 focal counties (Cattaraugus and
Chenango) from the 2012 hunting license records provided
by the New York State Department of Environmental
Conservation. We sent the questionnaire via the mail and
received replies from 227 licensed hunters (32.5% response
rate). We selected birdwatchers from the membership and
citizen-science databases at the Cornell Lab of Ornithology,
drawing from the 2 focal counties plus 8 additional rural
counties in upstate New York with similar demographic
characteristics. Then, via email, we sent a web-based
questionnaire to 1,982 birdwatchers in the 10 rural New
York counties comprising the study area. We received 758
completed surveys (38.3% response rate) and excluded 112 of
these individuals because they did not reside in the focal
counties (i.e., some were birdwatchers simply traveling
through the study area), resulting in an effective sample of
646 birdwatchers. We selected landowners in the 2 focal
counties by randomly identifying parcels in the 2010 GIS
Clearinghouse database. We sent questionnaires via mail to
1,026 landowners, and received 388 (37.8% response rate).
After aggregating the hunter, birdwatcher, and landowner
samples (n¼1,261), we deleted respondents with missing
data on the PEB items (n¼320), resulting in an effective
sample size of 941 respondents. To test for non-response
bias, we randomly selected 50 non-respondents from each
sample (hunter, birdwatcher, landowner) for follow-up
telephone contact in June 2013. The telephone follow-up
focused speciﬁcally on activity participation and demograph-
ics and represented a subset of the larger questionnaire. We
found no statistically signiﬁcant differences between
respondents and non-respondents in terms of participation
rates in the respective wildlife recreation activities. Demo-
graphic ratios among respondents and non-respondents in
the hunter and landowner categories were comparable; in the
birder sample, non-respondents were slightly older and
signiﬁcantly more likely to be male than respondents.
We developed logistic regression models to examine factors
predicting the likelihood of individuals carrying out PEB. In
these models, we controlled for socio-demographic variables
and environmental beliefs to isolate the effects of wildlife-
based recreation on PEB. We examined speciﬁc comparisons
between each type of wildlife-based recreationist and non-
recreationists using odds ratios with a statistical signiﬁcance
level of a¼0.05. We calculated the probability of adoption
of PEB for the average individual in each recreation group
using the basic logistic transformation (Menard 2002):
is the probability of the behavior for group iand
(aþb1X1þb2X2…) are the value of log(odds)
calculated based on logit model coefﬁcients and mean X
values for average respondent in group i.
We calculated the relative likelihood of wildlife recre-
ationists’ adoption of various behaviors (compared to non-
recreationists) using the following equation developed by
Zhang and Yu (1998) to estimate relative risk:
is the relative likelihood (i.e., relative risk) of
PEB for group i(compared to control group of non-
is the odds ratio for group i, and P
the probability of condition (i.e., PEB) for average individual
in control group (i.e., non-recreationists) using the calcula-
Wildlife Recreation Groups
Our 2-step method for classifying individuals into mutually
exclusive groups of wildlife recreationists was effective
(Table 2). For example, 96% of hunters, and 96% of
birdwatchers spent at least some time hunting and bird-
watching in the past 12 months, respectively, with a mean of
29 hunting days per year and 201 birdwatching days per year.
Hunters tended not to birdwatch, and birdwatchers tended
not to hunt (with the small group of hunter–birdwatchers
constituting a notable exception). Participation rates for
hunting and birdwatching were highest among hunter–
birdwatchers. Nearly 2 out of 3 hunter–birdwatchers listed
hunting as the activity they enjoy most. On the other end of
the spectrum, only a few people in the non-recreationist
category spent any time birdwatching (14%) or hunting (5%)
in the past year, providing additional support for the wildlife
recreation classiﬁcation system based on a combination of
self-reported identity and a threshold of days participating.
Although the study did not attempt to estimate recreation
activity participation rates among the general rural popula-
tion (i.e., landowners), some inferences can be made based on
the landowner-speciﬁc sample. When the population of
randomly selected landowners was asked about the “ONE
nature-based recreation activity they enjoyed the most,” 40%
listed hunting, 24% listed birdwatching 13% listed other
Cooper et al. Are Wildlife Recreationists Conservationists? 5
activities, and 22% indicated no activity as the preferred
choice. When asked directly about activity participation in
the past 12 months, 48% of rural landowners had hunted,
46% had participated in birdwatching, 53% had participated
in other nature-based recreation activities (e.g., ﬁshing,
hiking), and 19% indicated they had not participated in
The socio-demographic characteristics of respondents
(Table 3) who did not regularly participate in wildlife-based
recreation generally reﬂected rural populations across much
of upstate New York and the United States (U.S.
Department of Agriculture Economic Research Service
2011). These non-recreationists tended to be relatively old
(mean age ¼63.5 years), well educated (42% had attained a
college degree), somewhat conservative, and slightly more
likely to be male (58%). Birdwatchers, though typically
around the same age as non-participants (mean ¼60.7
years), were even more educated (73% had attained a college
degree), more liberal, and predominantly female (67%). On
the other hand, hunters were younger (mean ¼53.0 years),
less educated (26% had attained a college degree), more
conservative, and predominantly male (93%; Table 3). Socio-
demographic attributes for hunter–birdwatchers were very
similar to those in the hunter-only group. In terms of
environmental beliefs, birdwatchers showed higher levels of
environmental concern and environmental efﬁcacy, suggest-
ing they were more concerned about environmental quality
and more likely to believe personal actions could make a
difference with respect to the local environmental. However,
birdwatchers scored lower on the environmental norm scale,
indicating they were less likely to believe that environmental
protection was valued by people in their local community.
Table 2. Metrics of participation in hunting and birdwatching corroborate the classification of survey respondents in rural New York, 2013, into the 4
wildlife recreation groups assigned by the combination of self-identification and exceeding threshold levels of avid participation. Sample size for each group is
listed in parentheses.
Non-recreationist (74) Hunter (290) Birdwatcher (513) Hunter–birdwatcher (64)
Favorite activity ¼hunting (%) 0 98 0 66
1 day/yr hunting (%) 5 96 8 98
19 days/yr hunting (%) 0 55 0 79
Mean hunting per year (days) 0.5 29.3 0.6 44.1
Median hunting per year (days) 0 0 19 29
Favorite activity ¼birdwatching (%) 0 0 97 30
1 day/yr birdwatching (%) 14 25 96 100
190 days/yr birdwatching (%) 0 0 55 86
Mean birdwatching per year (days) 3.5 9.7 201.1 296.5
Median birdwatching per year (days) 0 0 190 365
Table 3. Mean values by wildlife-based recreation group from residents of rural New York surveyed in 2013.
Variable Non-recreationist Hunter Birdwatcher Hunter–birdwatcher
Gender (male) 0.58 0.93 0.33 0.89
Age (mean in years) 63.50 53.00 60.70 60.70
Education (college degree) 0.42 0.26 0.73 0.36
3.19 3.70 2.74 3.88
Environmental efficacy 3.51 3.62 3.82 3.59
Environmental concern 3.16 3.02 3.43 3.09
Environmental norms 3.55 3.43 3.20 3.45
Environmental lifestyle behaviors 0.61 0.52 0.77 0.61
Recycling 0.92 0.89 0.98 0.94
Resource conservation 0.85 0.84 0.94 0.94
Green purchasing 0.73 0.70 0.90 0.78
Conservation behaviors 0.08 0.21 0.45 0.47
Private land habitat enhancement 0.74 0.86 0.97 0.98
Conservation policy support 0.46 0.46 0.70 0.70
Donation to conservation 0.23 0.36 0.61 0.56
Wildlife recreation advocacy 0.14 0.52 0.43 0.56
Public land habitat enhancement 0.11 0.30 0.42 0.47
Join environmental group 0.12 0.13 0.35 0.34
Scale: 1 ¼liberal to 5 ¼conservative.
Scale: 1 ¼strongly disagree to 5 ¼strongly agree.
Reﬂects binary behavior variable where 0 ¼rare behavior and 1 ¼regular behavior.
6 The Journal of Wildlife Management 9999
Scores among the other groups were similar on all belief
measures except level of concern for the condition of
the environment, where hunters and hunter–birdwatchers
scored lower than the birdwatchers and non-recreationists
The 4 types of wildlife recreationists varied in terms of self-
reported adoption of PEB, with birdwatchers generally
reporting higher levels of PEB than any of the other groups
(Table 3). Although these numbers highlight bivariate
relationships between wildlife recreation and PEB, they do
not account for other variables, such as socio-demographic
attributes and environmental beliefs. Logistic regression
models helped to control for these known inﬂuences and
isolated speciﬁc links between wildlife-based recreation and
Factors Associated With Pro-Environmental Behavior
On average, only 35% of respondents frequently engaged
in conservation behaviors and 67% frequently engaged
in environmental lifestyle behaviors. Logistic regression
models accounted for variation in conservation behaviors
10 ¼185:1, P<0.001; Hosmer–
8¼13:3, P¼0.103) and environmental life-
style behaviors (Nagelkerke R
P<0.001; Hosmer–Lemeshow x2
8¼4:4, P¼0.816). Wild-
life recreation was strongly and positively associated with
conservation behaviors but not signiﬁcantly associated with
environmental lifestyle behaviors (Table 4). Compared to
non-recreationists, hunters (odds ratio ¼4.47, P<0.01) and
birdwatchers (odds ratio ¼6.93, P<0.001) were 4–5 times
more likely to participate in conservation behaviors (Fig. 1).
In distinction to participation in just 1 of the wildlife
recreation activities, we observed strong synergistic effects
of hunting and birdwatching. Hunter–birdwatchers were 8
times more likely to engage in conservation behaviors than
non-recreationists (odds ratio ¼15.07, P<0.001; Fig. 1).
These models showed that environmental concern and self-
efﬁcacy, but not environmental norms, were important
antecedents to both environmental lifestyle and conservation
behaviors (Table 4). Demographic variables were also linked
to certain types of PEB (Tables 4 and 5). For example,
education level was positively associated with both the
aggregate environmental lifestyle behaviors (Table 4) and
the subscale of conservation behaviors (Table 5).
Recreation status was also related to several speciﬁc
conservation behaviors. On average, half of the respondents
(50%) donated to conservation, and the model explained a
signiﬁcant portion of the variation (R
Table 4. Parameter estimates, standard errors, and odds ratios (OR) from binary logistic regression models examining factors predicting rural New York
residents’ adoption of 2 categories of pro-environmental behavior in 2013: conservation behaviors and environmental lifestyle behaviors.
Environmental lifestyle behaviors
bSE OR bSE OR
Intercept 8.09 0.96 2.18 0.77
Age 0.01 0.01 1.01 0.01 0.01 1.01
Gender (male) 0.11 0.18 0.90 0.45 0.18 0.64
Education (college) 0.58 0.18 1.79 0.41 0.17 1.51
0.06 0.07 0.94 0.05 0.06 0.95
0.79 0.11 2.20 0.33 0.10 1.39
0.51 0.10 1.66 0.23 0.09 1.26
0.11 0.10 1.11 0.07 0.09 1.08
1.94 0.46 6.93 0.44 0.28 1.55
1.50 0.49 4.47 0.00 0.29 1.00
2.71 0.54 15.07 0.22 0.37 1.25
,, and denote signiﬁcance of odds ratios at a¼0.05, 0.01, and 0.001, respectively.
Conservation behavior scale denotes regular levels of aggregate mean engagement in the following behaviors: private land habitat enhancement, conservation
policy support, donation to conservation, wildlife recreation advocacy, public land habitat enhancement, involvement in an environmental group.
Environmental lifestyle behavior scale denotes regular levels of aggregate mean engagement in the following behaviors: recycling, energy/water conservation,
Scale: 1 ¼liberal to 5 ¼conservative.
Scale: 1 ¼strongly disagree to 5 ¼strongly agree.
Dummy variable for wildlife-related recreation group relative to non-recreationist.
Figure 1. Wildlife-based recreationists’ relative likelihood of participating
in pro-environment behaviors (PEBs) compared to non-recreationists in
rural New York, 2013. We derived relative likelihoods from odds ratios in
logistic regression models. A ratio of 1 indicates no difference.
Cooper et al. Are Wildlife Recreationists Conservationists? 7
P<0.001; Hosmer–Lemeshow x2
Those participating in wildlife recreation were 2–3 times
more likely to donate than non-recreationists (Table 5 and
Fig. 1). Private land habitat enhancement was common
(carried out by 92.1% of respondents), and the model
10 ¼87:7, P<0.001; Hosmer–Lemeshow
8¼11:6, P¼0.171) indicated that wildlife recreationists
were 1.2–1.3 times more likely to engage in private land
habitat enhancement (Table 5). About 36% of respondents
engaged in public land habitat enhancement, and the model
accounting for variation in this behavior (R
10 ¼85:1, P<0.001; Hosmer–Lemeshow x2
P¼0.084; Table 5) showed that wildlife recreationists
were 3–5 times more likely to participate. On average, 45% of
respondents engaged in wildlife recreation advocacy
10 ¼125:8, P<0.001; Hosmer–Lemeshow
8¼10:1, P¼0.257), and wildlife recreationists were
3–5 times more likely to do so than non-recreationists
(Table 5 and Fig. 1). Models predicting the likelihood of
joining an environmental group (self-reported by 26% of
10 ¼149:4, P<0.001; Hosmer–Lemeshow
8¼8:9, P¼0.349; R
¼0.216) and supporting con-
servation policy (self-reported by 61% of respondents;
10 ¼134:5, P<0.001; Hosmer–Lemeshow x2
¼0.181) showed that birdwatchers and
hunter–birdwatchers, but not hunters, were signiﬁcantly
more likely than non-recreationists to adopt these particular
conservation behaviors (Table 5). Across all conservation
behavior variables, effects appeared to be additive; hunter–
birdwatchers were more likely to participate in each type of
conservation behavior than any of the other groups (Fig. 2).
Subscale scores revealed that respondents who were female,
older, and well-educated were more likely to participate in
environmental lifestyle behaviors (Table 4). Demographic
differences in overall conservation behavior were observed
Table 5. Parameter estimates, standard errors, and odds ratios (OR) from binary logistic regression models examining factors predicting rural New York
residents’ adoption of specific conservation behaviors with implications for wildlife conservation and management in 2013.
Intercept 3.88 (0.79) 3.01 (1.28) 5.45 (0.85) 5.04 (0.82) 8.28 (0.99) 4.87 (0.80)
NA NA NA NA NA NA
Age 0.01 (0.01) 0.01 (0.01) 0.00 (0.01) 0.02 (0.01) 0.02 (0.01) 0.02 (0.01)
1.01 0.99 1.00 0.98 1.02 1.02
Gender (male) 0.46 (0.18) 0.13 (0.36) 0.02 (0.18) 0.07 (0.18) 0.47 (0.19) 0.09 (0.18)
0.63 0.88 1.02 0.93 1.600.91
Education (college) 0.34 (0.16) 0.01 (0.30) 0.19 (0.16) 0.42 (0.17) 0.58 (0.19) 0.57 (0.16)
1.401.01 1.20 1.521.79 1.76
0.22 (0.06) 0.80 0.13 (0.11) 1.14 0.02 (0.06) 0.06 (0.06) 0.11 (0.07) 0.09 (0.06)
0.98 1.06 0.90 0.92
0.61 (0.10) 0.32 (0.18) 0.57 (0.11) 0.68 (0.11) 0.72 (0.12) 0.63 (0.10)
1.83 1.38 1.77 1.98 2.06 1.89
0.30 (0.09) 0.48 (0.16) 0.24 (0.09) 0.31 (0.09) 0.42 (0.10) 0.37 (0.09)
1.34 1.60 1.28 1.36 1.52 1.45
0.02 (0.09) 0.49 (0.17) 0.13 (0.09) 0.11 (0.09) 0.25 (0.10) 0.06 (0.09)
0.98 1.63 1.14 1.12 1.281.06
1.19 (0.31) 2.60 (0.43) 1.59 (0.40) 1.25 (0.37) 1.18 (0.39) 0.61 (0.28)
3.30 13.4 4.91 3.50 3.24 1.85
1.02 (0.37) 0.76 (0.37) 1.31 (0.42) 1.97 (0.39) 0.26 (0.43) 0.35 (0.29)
2.79 2.133.69 7.14 1.30 1.41
1.85 (0.40) 3.14 (1.06) 2.07 (0.47) 2.21 (0.45) 1.47 (0.48) 1.25 (0.39)
6.39 23.1 7.95 9.10 4.36 3.47
,, and denote signiﬁcance of odds ratios at a¼0.05, 0.01, and 0.001, respectively.
Scale: 1 ¼liberal to 5 ¼conservative.
Scale: 1 ¼strongly disagree to 5 ¼strongly agree.
Dummy variable for wildlife-related recreation group relative to non-recreationist.
Figure 2. Predicted probability of participating (%) in different types of pro-
environmental behaviors (PEBs) for individuals in each type of wildlife-
based recreation group in rural New York, 2013. We calculated predicted
probabilities from log(odds) in the logit model.
8 The Journal of Wildlife Management 9999
only for the education variable (Table 4), though differences
were evident for speciﬁc conservation behavior items
(Table 5). For example, females and individuals with higher
education levels were more likely to donate to conservation.
Males were more likely to participate in environmental
groups. Political ideology was signiﬁcantly linked to only
1 variable—donation to conservation—with liberals more
likely to contribute. Demographic variables did not appear to
affect habitat enhancement on either private or public lands
We extended past research that examined associations
between wildlife recreation and PEB by incorporating a
wider range of conservation-oriented behaviors and more
concrete measures of recreation (Teisl and O’Brien 2003,
Thapa 2010, Glowinski and Moore 2014). Respondents in
our rural sample reported high rates of environmental
lifestyle behaviors such as recycling, energy conservation, and
green purchasing, but analyses did not reveal a signiﬁcant
link between wildlife recreation and these lifestyle behaviors.
Although self-reported engagement in various forms of
conservation behaviors (e.g., habitat enhancement, joining
an environmental group, donation to conservation) occurred
much more infrequently, our ﬁndings supported the
hypothesized positive association between wildlife recreation
and engagement in conservation-oriented activities. As
concerns regarding low levels of public adoption of PEB—
and conservation behaviors speciﬁcally—escalate, scholars
attempting to identify interventions that effectively encour-
age PEB have uncovered a range of useful strategies
including education, marketing, incentives, and other
approaches aimed at building enduring commitment and
self-efﬁcacy (Hungerford and Volk 1990, De Young 1993,
Heimlich and Ardoin 2008, Steg and Vlek 2009). Our data
suggest that the promotion of wildlife-based recreation
activities such as birdwatching and hunting could be an
additional strategy. In rural areas where outdoor recreation
opportunities abound (e.g., approx. 81% of our sample had
engaged in some type of nature-based activity in the past 12
months) and conservation behavior participation rates are
low (e.g., predicted participation rates for non-recreationists
in our sample was at or below 10% for many behaviors),
efforts to increase the number of avid wildlife recreationists
might yield signiﬁcant increases in PEB.
Results also provide evidence to support an additive effect
of consumptive and non-consumptive wildlife recreation.
Individuals who regularly go birdwatching and hunting
were more likely to engage in conservation behaviors than
individuals who did only 1 or neither of those activities.
These ﬁndings advance understanding of the relationship
between conservation and recreation, building upon
previous studies that have revealed experience with nature
is fundamental in inﬂuencing nature-related values (Kellert
1996), emotional afﬁnity towards nature (Kals et al. 1999),
environmental concern (Dunlap and Heffernan 1975), and
PEB (Theodori et al. 1998, Teisl and O’Brien 2003, Zaradic
et al. 2009, Halpenny 2010, Scannell and Gifford 2010,
Larson et al. 2011).
We found that, in some cases, wildlife recreation can offset
the strong inﬂuence of certain socio-demographic attributes
(e.g., education level, political orientation) that are often
associated with a decreased likelihood of participating in
PEB. In other words, the frequency with which hunters
engaged in conservation behaviors was high relative to non-
recreationists with similar socio-demographic attributes. It is
not clear, however, why recreation may effectively nullify
some of these demographic differences. Perhaps wildlife
recreation fosters connections with local landscapes that
builds and/or reinforces attachment to place, ultimately
leading to place-protecting actions (Stedman et al. 2008,
Budruk and Wilhelm Stanis 2013). The causal nature of
the relationships identiﬁed in this study is also unclear.
For example, perhaps the signiﬁcant relationship between
conservation and recreation is driven by an unidentiﬁed,
unmeasured covariate that may emerge through evolving
behavior theory such as Fishbein and Ajzen’s (2010)
Reasoned Action Approach. Future research could explore
this possibility and examine the complex relationships
between wildlife recreation, demographic attributes, envi-
ronmental beliefs, and PEB in more detail in other types of
The synergistic effect of dual recreation was of particular
interest; for individuals who participated in hunting and
birdwatching (i.e., hunter–birdwatchers), the likelihood of
carrying out conservation behaviors increased to 8 times that
of non-recreationists. These additive effects have important
implications for a wildlife conservation community that is
constantly struggling to muster the ﬁnancial and political
support needed to make progress on urgent wildlife
conservation issues. Nevertheless, a perceived dichotomy
has persisted for decades, possibly because birdwatchers and
hunters are typically viewed as different types of people and
altogether different populations driven by distinct values and
beliefs (Duffus and Dearden 1990, Daigle et al. 2002).
Although our study supports other research showing
the 2 groups differ by gender, education, and political
orientation (Adams et al. 1997), our data also suggest that
the environmental beliefs and conservation behaviors of
birdwatchers and hunters might be more similar than many
recognize. Earlier work revealed a similar pattern, showing
substantial overlap in wildlife values among individuals
associated with conservation organizations that were game-
oriented, such as National Wild Turkey Federation and
Ducks Unlimited, and non-game oriented, such as Defend-
ers of Wildlife and National Audubon Society (Purdy et al.
1983). Later studies corroborated these ﬁndings, indicating
similar rates of involvement in or contributions to
environmental organizations for both wildlife watchers
and hunters (Teisl and O’Brien 2003). For these reasons,
as other scholars have noted, frameworks that segregate non-
consumptive and consumptive forms of wildlife recreation
may not be particularly useful—and even potentially
damaging—when considering conservation goals (Connelly
et al. 1985, Schreyer et al. 1989). In fact, our results support
Cooper et al. Are Wildlife Recreationists Conservationists? 9
earlier suggestions that wildlife recreation may transcend
socio-demographic attributes when it comes to certain types
of PEB (Theodori et al. 1998). Therefore, future efforts to
generate additional support for conservation could empha-
size the value of connecting with and fostering support for
both birdwatching and hunting.
Notable differences in the relative likelihood of engaging in
conservation-oriented actions were evident for several
behaviors that may be of particular interest to the wildlife
management community. For example, with other factors
held constant, hunters were 1.9 times more likely,
birdwatchers were 2.1 times more likely, and hunter–
birdwatchers were 2.7 times more likely than non-
recreationists to donate money to conservation. Earlier
studies focused on hunters (Mahoney and Jackson 2013) and
birdwatchers (McFarlane and Boxall 1996) have shown that
wildlife recreation is commonly associated with political
engagement in the conservation arena. Furthermore, hunters
(Benson 2010) and birdwatchers (McFarlane and Boxall
1996, Scott 2013) are often members and regular contrib-
utors to local clubs and organizations focused on natural
resource conservation. Conservation fundraising efforts
that target dual participants (i.e., birdwatcher-hunters)
may therefore be more effective than those that focus on a
particular recreation group.
Similar patterns were observed for private and public
land habitat enhancement. Although private land
habitat enhancement was a relatively common practice in
rural areas—even among respondents who were non-
recreationists—participation in any form of wildlife
recreation was associated with signiﬁcant increases in the
relative likelihood of carrying out habitat enhancement.
Hunters were 2.9 times more likely, birders were 3.5 times
more likely, and hunter–birdwatchers were 4.7 times
more likely than non-recreationists to carry out these
activities. The strong link between wildlife recreation and
local habitat enhancement is not surprising, primarily
because wildlife recreationists depend directly on healthy
habitats and ecosystems to support the wildlife populations
that sustain their recreation. Future research could investi-
gate in more depth the speciﬁc types of habitat enhance-
ment that appeal to both game- and non-game oriented
Wildlife recreationists were also more likely to engage in
wildlife recreation advocacy, with hunter–birdwatchers (5.1
times more likely than non-recreationists) and hunters (4.5)
leading the way. This behavior may play a key role in shaping
public perceptions of wildlife recreation and associated
beneﬁts. In rural areas, hunters have developed social systems
that have enabled recruitment, retention, and communica-
tion about conservation-oriented activities (Stedman and
Heberlein 2001). Our data conﬁrm that, relative to non-
recreationists and birdwatchers in rural areas, hunters tend to
advocate more often for their preferred activity and articulate
the beneﬁcial outcomes it provides to local ecosystems
and communities. These differences may be an artifact of
longstanding efforts to counter anti-hunting sentiment and
stimulate interest in hunting for wildlife management
(vs. sport), but more research is needed to explore this
Although links between wildlife recreation and conservation
behaviors were very clear, associations between hunting,
birdwatching, and environmental lifestyle behaviors such as
recycling, energy conservation, and green (eco-friendly)
purchasing were much less pronounced. All respondents
were more likely to participate in environmental lifestyle
behaviors (and do so more frequently), but when controlling
for socio-demographic characteristics their prevalence
was unrelated to involvement in wildlife recreation. Our
data therefore suggest that research focused primarily on
environmental lifestyle behaviors, a common theme in many
PEB studies (Stern 2000, Poortinga et al. 2004, Steg and Vlek
2009), may fail to detect associations between wildlife
recreation and conservation. Researchers focused on under-
standing and predicting the relationship between wildlife-
based recreation and PEB should therefore ensure that
conservation-oriented actions with speciﬁc wildlife manage-
ment implications are explicitly considered in PEB assessment.
As need for a broader appreciation of and support for
conservation among Americans grows increasingly urgent,
understanding the extent to which nature-based activities
contribute to such appreciation and awareness has become a
high priority within the wildlife conservation community
(U.S. Fish and Wildlife Service 2012b). Our data highlight
the conservation contributions of hunters and birdwatchers,
showing that both groups are more likely to engage in
conservation behaviors than individuals who do not
participate in wildlife recreation. Conservation efforts may
especially beneﬁt from a more comprehensive understanding
of the motivations and values of individuals who regularly
participate in both birdwatching and hunting. Though the
anticipated outcomes and beneﬁts associated with each
activity undoubtedly vary (Daigle et al. 2002), the broader
implications of such engagement may be similar, particularly
when these activities occur together (e.g., waterfowl
hunting). Demographically, the hunter–birdwatchers in
this study were more similar to hunters than birdwatchers,
and future work on recreation and PEB could therefore
attempt to segment hunters into groups that include those
who engage in birdwatching and those who do not.
Additional research aimed at characterizing and understand-
ing different groups of wildlife-based recreationists could
also inform conservation-oriented communication, messag-
ing, and management, thereby fostering positive interactions
that ultimately lead to productive conservation action.
Shifting patterns of wildlife-based recreation have created
challenges for wildlife managers. Although birdwatching has
reached nearly unprecedented highs (Cordell et al. 2008,
Outdoor Foundation 2014), hunting continues to decline
(U.S. Fish and Wildlife Service 2013a, Vrtiska et al. 2013).
As debate surrounding the implications of these trends
grows, the wildlife conservation community has become
increasing interested in relationships between hunting,
birdwatching, and conservation. Results of this study suggest
10 The Journal of Wildlife Management 9999
that both activities are signiﬁcantly and positively associated
with a range of pro-environmental behaviors, particularly
actions that contribute directly to natural resource conserva-
tion. This is good news for the wildlife conservation
community, where many people have concern that the
decline in hunting among Americans inevitably will lead to a
corresponding decline in conservation interest and activity. To
the extent our ﬁndings are generalizable, they indicate that
agency program investment supporting wildlife viewing has
been, as hypothesized by proponents of such programs, a wise
investment in developing citizen-conservationists. Diversiﬁed
agency program portfolios that include programs to encourage
hunting and wildlife viewing in their various forms would
seem most likely to return long-term gains for conservation.
Even in those states where wildlife agencies maintain the
traditional stance that citizens who hunt are the primary focus
of state wildlife programs, our study suggests that supporting
those with hunting and birdwatching interests in their pursuit
of both will yield greater conservation returns.
The authors wish to acknowledge the contributions of a
study advisory team composed of representatives from the
New York State Department of Environmental Conserva-
tion, the New York State Ofﬁce of Parks, Recreation and
Historic Preservation, and Cornell Cooperative Extension.
This work was supported by the United States Department
of Agriculture National Institute of Food and Agriculture,
Hatch project #147-7477. Any opinions, ﬁndings, con-
clusions, or recommendations expressed in this publication
are those of the authors and do not necessarily reﬂect the view
of the National Institute of Food and Agriculture (NIFA) or
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Associate Editor: John Daigle.
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