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White-Tailed Deer Management on Private Lands in Arkansas
Picture Credit: U.S. Fish and Wildlife Service/Washington D. C. Library, Washington, District of Columbia.
Submitted to: Wildlife Management Division
Arkansas Game and Fish Commission
Submitted by: Bret A. Collier and David G. Krementz
USGS Arkansas Cooperative Fish and Wildlife Research Unit Department of Biological Sciences
University of Arkansas Fayetteville, AR 72701
October 2003
EXECUTIVE SUMMARY
The current goal of the Arkansas Game and Fish Commission’s (AGFC) deer program is
to “maintain a healthy deer herd with a balanced sex and age structure at a level that is consistent
with long-term habitat capability and to maintain deer populations and parameters at levels that
are consistent with public satisfaction and acceptance.” To achieve this goal, the AGFC must
apply harvest management strategies that develop and sustain white-tailed deer populations,
while maximizing hunter satisfaction. Too, the AGFC must manage the deer herd at biological
and socially acceptable levels.
In the United States, about 82% of sportsmen hunt on private lands (U.S. Department of
Interior 2001) while in the southeastern United States, about 90% of the forested land is under
private ownership (Powell et al. 1994). Lack of available public lands for wildlife related
recreation and increased hunter interest in managing white-tailed deer (Woods et al. 1996) has
increased hunter involvement in hunting organizations on private lands. In Arkansas, about 95%
of annual legal harvest occurs on private lands (D. Harris, AGFC, personal communication).
Since ~90% of Arkansas is privately owned (Smith et al. 1998), the AGFC only controls the site-
specific harvest management regulations on <1% of the total state land. Because white-tailed
deer harvests on private lands are usually more intensively managed than those on public lands
(Carpenter 2000), comprehensive white-tailed deer management requires knowledge of deer
management practices in use on private lands.
STUDY OBJECTIVES
1. Provide a baseline to enable the AGFC to track and evaluate hunt camps participating
in the Arkansas Deer Camp Program (DCP).
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2. Provide an assessment of harvest and habitat management practices in use by hunt
camps registered in the Arkansas DCP.
3. Determine DCP participant’s level of interest in AGFC management assistance
programs and deer management information.
4. Identify and evaluate differences in implementation of harvest and habitat
management practices by Deer Camp Program participants.
5. Identify possible program actions for the AGFC to assist hunt camps on private lands
with white-tailed deer management.
METHODS In September 2000, we mailed a questionnaire to hunt camp contacts for each white-
tailed deer hunt camp registered in the Arkansas DCP (n=3,189). A second mailing was sent to
all non-respondents 4 weeks later. A follow-up evaluating non-response bias was not conducted.
The response rate adjusted for non-deliverable surveys was 38% (1,184 responding hunt camps).
Camp contacts were asked to provide information on: 1) their classification (land owner,
land manager, camp manager), 2) location and acreage of hunt camp, 3) property type of hunt
camp, 4) hunt camp management objective (if under Quality Deer Management (QDM)
strategy), and 5) whether their hunt camp managed for wildlife species other than white-tailed
deer. We asked respondents to rank 1) harvest management practices in excess of state
regulations in use on hunt camp property, 2) habitat management practices in use on hunt camp
property (both type and length of time), 3) types of AGFC provided management assistance that
would benefit their hunt camp, 4) opinions on future AGFC management options, and 5)
opinions on problems affecting their hunt camp. Respondents were asked: 1) to rate their level
of interest in AGFC provided information on white-tailed deer management, 2) to rate which
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delivery method provided the most value, 3) to provide information on biological data collection,
4) whether their hunt camp worked with an AGFC biologist, and 5) whether their hunt camp
would benefit from increased AGFC management assistance.
RESULTS
• Hunt camps encompassed ~ 1.75 million acres of land in Arkansas
• Hunt camps average member size varied from a low of 13 (SE = 0.88) in the Ozarks to a
high of 23 (SE = 3.15) in the Ouachitas.
• About 60% of hunt camps in Arkansas restricted white-tailed deer harvests to meet their
specific management goals, regardless of statewide management goals.
• Across Arkansas, 40% of responding camps were under a QDM program.
• The primary management objective (61%) of hunt camps under QDM was to improve
antler development/physical condition of the deer herd (deer harvest restricted to allow
more bucks to reach older age classes of ≥ 2.5 years old).
• Across Arkansas, harvest management strategies in excess of state regulations used most
frequently were restricted antlerless harvest (no button bucks) and minimum four (4)-
point rule.
• Across Arkansas, 70% of hunt camps used winter food plots as their primary habitat
management practice, while 60% and 50% of hunt camps also used supplemental feeding
and supplemental minerals, respectively.
• 50% of hunt camps actively conducted habitat management for wildlife other than white-
tailed deer.
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• Across Arkansas, 57% of hunt camps stated that they had seen an increase in the number
of bucks > 2.5 years old on their deer camps since they began using harvest and habitat
management practices on their property.
• Across Arkansas, 77% of hunt camps stated that they had not seen an increase in the
number of > 4.5 years old on their deer camps since they began using harvest and habitat
management practices on their property.
• Across Arkansas, 65% felt that they did not have a more equal ratio of bucks to does on
their deer camps property on their deer camps since they began using harvest and habitat
management practices on their property.
• Across Arkansas, 56% of hunt camps felt that the management assistance program that
would most benefit/interest their hunt camp was recommendations from a wildlife
biologist.
• Across Arkansas, hunt camps felt that expanding educational efforts for hunters and hunt
camps on deer management assistance for private lands was the most important future
management option for the AGFC.
Because much of Arkansas is privately owned, the AGFC needs information regarding
white-tailed deer management on private lands. This study provides the AGFC with an
evaluation of hunt camp harvest and habitat management practices on a sample of private lands
in Arkansas. Any comprehensive statewide management plan for white-tailed deer must provide
for practices in use on private lands.
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INTRODUCTION
Across the United States, approximately 82% of sportsmen hunt on private lands (U.S.
Department of Interior 2001). Hunt camps on private lands often manage white-tailed deer
populations for specific population goals. Because harvest regulations across the United States
follow a hierarchical structure (Fig. 1), and deer management is usually more intensive on
private lands (Carpenter 2000), knowledge of harvest and habitat management practices in use
on private lands should be useful when planning statewide management goals.
Our goal was to provide an assessment of attitudes of club members who participate in
the Arkansas Deer Camp Program (DCP). Our specific objectives were to:
1. provide a baseline to enable the AGFC to track and evaluate hunt camps participating
in the Arkansas Deer Camp Program (DCP),
2. provide an assessment of harvest and habitat management practices in use by hunt
camps registered in the Arkansas DCP,
3. determine DCP participant’s level of interest in AGFC management assistance
programs and deer management information,
4. identify and evaluate differences in implementation of harvest and habitat
management practices by Deer Camp Program participants, and
5. identify possible program actions for the AGFC to assist hunt camps on private lands
with white-tailed deer management.
With this information, the AGFC should be able to better manage white-tailed deer and
deer hunters in Arkansas.
METHODS
Sample and data collection
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In September 2000, we sent an 8 page self-administered mail-back questionnaire to the
hunt camp contact for each white-tailed deer hunt camp registered in the Arkansas DCP (n =
3,189, Appendix 1). Each deer camp survey mailing contained a cover letter, the questionnaire,
and a postage-paid business reply envelope. A second mailing was sent to all non-respondents 4
weeks later. A follow-up evaluating non-response bias was not conducted. Upon receiving each
returned survey, we entered it into a database. We conducted quality control for survey entry by
randomly selecting a number between 1 and 10 and using that value as our starting point. We
then pulled every 10th survey from the random starting point and rechecked each recorded
response in the database. We proofed approximately 10% of responding surveys (n = 119).
Based on a literature review and conversations with AGFC personnel, we developed the
questionnaire to provide information that the AGFC felt would most assist them in working with
DCP participants. Camp contacts were asked to provide information on: 1) their classification
(land owner, land manager, camp manager), 2) location and acreage of hunt camp, 3) property
type of hunt camp, 4) hunt camp management objective (if under Quality Deer Management
(QDM) strategy), and 5) whether their hunt camp managed for wildlife species other than white-
tailed deer.
Using a scale from 1 to k (k = number of response categories; 1= practice most used,
most beneficial, most important; k = practice least used, least beneficial, least important) we
asked respondents to rank: 1) harvest management practices used on hunt camp property in
excess of state regulations, 2) habitat management practices used on hunt camp property (both
type and length of time), 3) interest in management assistance programs, 4) their opinions on
future AGFC management options and 5) their opinions on problems affecting their hunt camp.
Using a scale from 5 to 1 (5 = extremely interested/valuable; 1 = not interested/valuable),
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respondents were asked 1) to rate their interest in information on white-tailed deer management,
2) to rate which delivery method would provide the most value, 3) to provide information on
biological data collection, 4) whether their hunt camp works with an AGFC biologist, and 5)
whether their hunt camp would benefit from increased AGFC management assistance.
Summary information analysis
For all questions using ranked responses, we provided 2 measures of tendency, mean
rank [standard error (SE)] and median rank, to summarize our results. Mean ranks have been
used by other authors (Woods et al. 1996, Messmer et al. 1998) to analyze survey results based
on ranked data. However, mean ranks can be influenced by extreme observations, and
dependent upon sample size, can lead to unclear relationships between response categories.
Therefore, we also included a median rank (M), which is less affected by outliers (Mood et al.
1974). The median rank is the midpoint of the response distribution, such that half the
observations fall above and below the median rank (Moore and McCabe 1993). Therefore, a
high median rank means that a large number of respondents provided a high rank. We feel that
median ranks, although they allow for no measures of variation, provide a easily understood
summary of responses. A standard error can be calculated for mean ranks and will be provided
in this report.
Data manipulation for modeling
For several of our research hypotheses of interest, we had quasi-complete separation
across predictor variables and therefore we were unable to attain necessary cell counts (≥ 1)
across classification variables to conduct ordinal logit modeling (Agresti 1996). To correct for
this problem, we ranked all scores ≤ 3 as a success (1) and all others as a failure (0). For
comparisons between response categories within a question, we estimated the odds of a
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respondent providing a rank of 1 (success). For comparisons between response categories, if the
rank in the ith response category was less than the rank in the jth category, responses were given
a rank of 1 (success) and a rank of 0 (failure) if rank in the ith category was greater than or equal
to the jth category.
Contingency Table Estimation
We estimated odds ratios on selected 2 x 2 contingency tables to test hypotheses
concerning differences in response frequencies for questions regarding quality deer management,
biological data collection, management assistance benefits, and biologist contact. Odds ratios
were estimated by deer management unit, property type, and across Arkansas. Contingency table
analysis was conducted using SAS PROC FREQ (SAS Institute, Inc. 2000).
Cumulative Logit Modeling
For questions that have a natural ordering of possible responses, we used a cumulative
logit model (proportional odds model) implemented in PROC LOGISTIC (SAS Institute, Inc.
2000) to estimate the effect of predictor variables on the levels of response. We used
proportional odds models to predict the probability of respondent providing a rank in the jth
category or higher (Agresti 1996, Allison 1999). When response categories were ordered,
proportional odds models can directly incorporate the ordering, leading to simpler interpretation
(Agresti 1996, Allison 1999). We checked goodness of fit for our proportional odds models by
evaluating the chi-square test statistic for the proportional odds assumption. A non-significant
test statistic indicated that the proportional odds model adequately fit the data (Allison 1999,
SAS Institute, Inc. 2000). We used a single set of predictors (property type, deer management
unit (DMU), and contact category) for proportional odds modeling of responses regarding
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interest levels in AGFC provided information type. If a proportional odds model did not satisfy
the proportional odds assumption, we did not interpret that model in the results section.
Model building, selection and inference
For selected questions in the survey, we used an information-theoretic approach to model
selection and inference (Burnham and Anderson 2002). For each question of interest, we began
with a global model containing all variables of interest that we thought important in explaining
the response variable (Anderson et al. 2001, Burnham and Anderson 2002). For each global
model, we initially determined if it adequately fit the data (Burnham and Anderson 2002) by
conducting residual analysis for each comparison of interest. If the global model adequately fit
the data, we proceeded to construct candidate models, or reduced parameter models (Burnham
and Anderson 2002), relative to the global model, and proceeded with interpretation.
For those models that adequately fit, we evaluated each set of candidate models
representing hypotheses that we wished to test by ranking those models based on Akaike’s
Information Criterion (AIC, Akaike (1973), Burnham and Anderson 2002) that was adjusted for
small sample size (AICc, Hurvich and Tsai 1989). Each question of interest and its resulting
candidate model set are shown in Tables 1 – 3. Models were ranked based on the difference
( ) between the ith model’s AICi∆
i∆
c value and the lowest AICc value in the candidate model set
(Burnham and Anderson 2002). The most plausible model, or model with the lowest AICc, has a
=0 (Burnham and Anderson 2002). Typically, any models with i∆ <2 have considerable
support, while models with 4< <7 have less support (Burnham and Anderson 2002).
Transformation of the values by
i∆
i∆ ( )i∆− 21exp represents the likelihood of the ith model,
given the data (Anderson et al. 2000, Burnham and Anderson 2002). We estimated Akaike
weights (wi: denoted in report as AICc wt) by rescaling the transformed i∆ values to sum to 1
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(Anderson et al. 2000, Burnham and Anderson 2002). We estimated the plausibility between
candidate models in our model set by constructing a likelihood ratio with the Akaike weights
(Anderson et al. 2000, Burnham and Anderson 2002). Royall (1997) suggested that a threshold
value of strong evidence for differences between models might be supported by an evidence ratio
of ≥ 8. Frequently, model selection results can indicate several plausible models (model
selection uncertainty) (Burnham and Anderson 2002). The typical procedure for parameter
estimation when > 1 model is plausible is to conduct model averaging (Buckland et al. 1997,
Burnham and Anderson 2002). However, it is not recommended to conduct model averaging
across non-linear candidate model sets (Burnham and Anderson 2002, W. L. Thompson, USGS
Arkansas Cooperative Fish and Wildlife Research Unit, personal communication), therefore, we
chose to base our inference only on candidate models with substantial empirical support ( i∆ <2).
Candidate Models
Across the questions of interest, we hypothesized 6 possible sources of variation affected
the odds of a hunt camp conducting a harvest or habitat management practice, or being interested
in AGFC management assistance. For each question of interest, we constructed a set of
candidate models for consideration. Each set of candidate models consisted of predictors that we
felt would allow us to evaluate sources of variation in the odds of a hunt camp selecting a
specific response category. Our predictions for the 6 sources of variation we included in our
models were:
Property Ownership: For this study, there were three possible classes of private property
ownership: 1) property privately owned by hunt camp members, 2) property privately owned that
hunt camps leased from the landowner, and 3) property privately owned by industry (e.g. timber
industry) that hunt camps leased from the industry. We hypothesized that hunt camps on non-
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industry privately owned property would use harvest management strategies based on antler
characteristics and restriction of buck harvest more frequently than those on industry property.
Because industry properties typically have wildlife biologists implementing harvest management
plans for/in conjunction with hunt camps, we expected hunt camps on industry properties to be
more likely to use harvest management based on antlerless deer more frequently than harvest
management based on antler characteristics or restrictions on buck harvests. We also
hypothesized that hunt camps on non-industry privately owned property would use habitat
management strategies such as food plots and natural vegetation management, while camps on
industry property would use habitat management such as supplemental feeding and minerals due
to restrictions on land management practices by industry personnel.
Deer Management Unit: Based on underlying physical and biological characteristics of
the state and discussions with AGFC biologists, we classified Arkansas into 4 Deer Management
Units (DMUs): 1) Ozarks, 2) Ouachitas, 3) Mississippi Alluvial Plain (MAV), and 4) Gulf
Coastal Plain (GCP) (Fig. 2).
Quality Deer Management: Typically, hunt camps under QDM strategies are actively
involved in white-tailed deer management (Woods et al. 1996). We classified hunt camps as
either under QDM (1) or not under QDM (0). We expected that hunt camps under QDM would
be actively involved in the management of white-tailed deer on their property through harvest
management of antlerless deer (does), and be more likely to use habitat management practices
such as food plots and natural vegetation management. We also expected that hunt camps under
QDM would be using harvest management practices that restricted harvest of younger bucks.
Hunt Camp Size: Given the mobility of white-tailed deer through daily, seasonal, and
annual ranges, we classified hunt camps into 3 classes according to size (acres): 1) <1000 acres,
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2) 1000-3000 acres, and 3) >3000 acres. We expected that larger hunt camps would be more
likely to use habitat management strategies that concentrate deer into specific areas during
hunting season (e.g. winter food plots, supplemental feeding).
Contact Type: For the question regarding interest in AGFC management assistance we
classified hunt camp contacts based on whether they were: 1) landowner (person who owns the
land that the hunt camp in located on), 2) land manager (person who owns the land and is
responsible for the management of the camp and wildlife), or 3) camp manager (person who does
not own the land but is responsible for the management of wildlife on the camp). We used the
contact type predictor to test for differences in responses regarding benefits from different
management assistance programs.
Biologist Contact: Typically, hunt camps that are actively involved in managing white-
tailed deer seek professional biologists for management assistance. We classified hunt camps as
either working with an AGFC biologist (1) or not working with an AGFC biologist (0). We
expected hunt camps working with AGFC biologist would have active habitat management
programs, and different interests and opinions regarding management assistance programs than
those camps not working with an AGFC biologist.
Binary Logit Modeling
Because our model selection program (W. L. Thompson, USGS Arkansas Cooperative
Fish and Wildlife Research Unit, personal communication) only identified and output model
selection results, we used the results from model selection procedures to identify those models
with substantial support ( < 2). We then evaluated each model with substantial support using
PROC GENMOD (SAS Institute Inc. 2000) to estimate parameters (odds ratios) and associated
measures of precision. Our objectives were to quantify which predictor variables contributed to
i∆
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differences in rank levels given by responding hunt camps. We estimated the odds of the ith
response category being ranked less than the jth response category (see: Data manipulation for
modeling) using the most parsimonious models from model selection results. We reported only
those estimated odds for comparisons where the estimated 95% confidence interval (CI) did not
include 1 (indicating a difference in the odds of response). An odds estimate farther from 1 in a
given direction represents a stronger level of association (Agresti 1996). Note that when
estimating odds ratios, that sample size influences precision of the estimates, but not the
direction of the estimate (G. Petris, University of Arkansas, personal communication.).
Therefore, although confidence interval coverage may be imprecise (e.g. lower confidence limit
near 1) for some estimates with small sample sizes (e.g. small cell counts), we are confident that
the direction the estimated odds represent (variation from independence) were accurate. To
quantify the importance of specific predictor variables in our candidate model set, we summed
the Akaike weights (wi) for models containing that variable in our candidate set (Burnham and
Anderson 2002). When evaluating the relative importance of predictor variables using summed
wi, the candidate model set must be balanced (e.g. equivalent numbers of candidate models
containing each predictor variable) (Burnham and Anderson 2002).
RESULTS
Survey Response
From the deer camp survey, we received 1,184 questionnaires from the 3,189 sent (37%).
Sixty-four surveys were classified as undeliverable, while deer camps that had not registered
during 2000 returned 13. Our adjusted response rate was 38%. Throughout this report,
discrepancies in percentages and/or number of respondents existed due to rounding error,
respondents provided equivalent ranks to multiple levels of ranking questions, respondents not
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answering all questions, or responses deemed impossible (e.g. 0 acres for hunt camp size).
Results (percentages, medians, means) provided will be based on the number of respondents to
each question (or category of a question), not to the entire sample.
General Hunt Camp Information
We received responses from ≥ 1 hunt camps from all but 5 counties (Table 4). All results
are interpreted without including those 5 counties. A majority of responding camps were located
in the Gulf Coastal Plain (GCP) (Table 5). Responding camps encompassed ~1.75 million acres
of land in Arkansas (~6% of the state land base). Responding camps had about 18,000 total
members with average camp member size varying from a low of 13 (SE = 0.88) in the Ozarks to
a high of 23 (SE = 3.15) in the Ouachitas (Table 6).
We asked respondents to classify property types that their deer camps were located on
(Table 7). Property types on which hunt camps were located were associated with predominant
land use practices. In the GCP, an area of predominately timber management, the majority of
hunt camps were located on industry lands, while in the Ozarks and Mississippi Alluvial Plain
(MAV), areas that are more agriculturally based, the majority of camps were located on land
privately owned by the hunt camp members (Table 7).
Across Arkansas, 40% of responding camps were under a QDM program (Table 8).
Regionally, the MAV had the highest percentage of responding camps under QDM programs
(Table 9). Of those camps under a QDM program, the primary management objective (61%)
was to improve antler development / physical condition of the deer herd (deer harvest restricted
to allow more bucks to reach older age classes of ≥ 2.5 years old) (Table 10). Across property
types, the management objective most frequently stated by respondents was to improve antler
development/physical condition of the deer herd (deer harvest restricted to allow more bucks to
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reach older age classes of ≥ 2.5 years old)(Table 11). Hunt camps stated that they usually (25%)
or always (53%) attempted to control hunter pressure on their properties (Table 12). Responding
hunt camps under a QDM program always (63%) or usually (23%) controlled hunter pressure
(Table 13). Across Arkansas, hunt camps on average had 1.5 (SE=0.04) hunters/100 acres. Hunt
camps averaged 1.8 (SE = 0.09), 1.5 (SE = 0.14), 1.5 (SE = 0.64), and 1.5 (SE = 0.05)
hunters/100 acres in the Ozarks, Ouachitas, MAV, and GCP, respectively.
Odds Ratio Estimation
Responding hunt camps across Arkansas that work with an AGFC biologist were 5.8
(95% CI = 4.28 – 7.97) times more likely to collect biological data from deer harvested by camp
members than hunt camps not working with an AGFC biologist. In the Ozarks, MAV, and GCP,
hunt camps working with AGFC biologists were 7.7 (95% CI = 3.78 – 15.53), 3.2 (95% CI =
1.52 – 6.75), and 7.9 (95% CI = 5.16 – 12.36) times, respectively, more likely to collect
biological data from deer harvested by camp members than those not working with an AGFC
biologist. Hunt camps on property owned by camp members were 6.0 (95% CI = 3.54 – 10.25)
times more likely to collect biological data when working with AGFC biologists. Camps on
non-member owned leased property were 4.4 (95% CI = 2.10 – 9.16) times more likely to collect
biological data when working with AGFC biologists, while camps on industry (e.g. timber
company lands) were 8.7 (95% CI = 5.08 – 14.95) times more likely to collect biological data
when working with AGFC biologists.
Hunt camps across Arkansas were 5.3 (95% CI = 3.82 – 7.26) times more likely to be
under a QDM strategy if they worked with an AGFC biologist. In the Ozarks, MAV, and GCP
hunt camps were 5.8 (95% CI = 2.99 – 11.36), 8.2 (95% CI = 1.55 – 42.01), and 8.2 (95% CI =
5.08 – 13.35) times, respectively, more likely to be under a QDM strategy if they worked with an
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AGFC biologist. Hunt camps on property owned by camp members were 3.1 (95% CI = 1.88 –
5.08) times more likely to be under a QDM strategy if they worked with an AGFC biologist,
while camps on non-member owned leased property and industry property were 5.5 (95% CI =
2.75 – 11.11) and 10.5 (95% CI = 5.74 – 19.20) times, respectively, more likely to be under a
QDM strategy if they worked with an AGFC biologist.
Hunt camps across Arkansas working with an AGFC biologist were 7.7 (95% CI = 2.61 –
5.34) times more likely to want increased AGFC management assistance than those not working
with an AGFC biologist. In the Ozarks and GCP, hunt camps working with AGFC biologists
were 4.1 (95% CI = 1.88 – 8.89) and 3.8 (95% CI = 2.30 – 6.26) times more likely to want
increased AGFC management assistance, while in the MAV those hunt camps working with
AGFC biologists were 5.0 (95% CI = 2.12 – 14.28) times less likely to want increased AGFC
management assistance than those not working with an AGFC biologist. Responding hunt
camps on property owned by camp members that work with AGFC biologists were 3.9 (95% CI
= 2.09 – 7.17) times more likely to want increased AGFC management assistance, while hunt
camps on non-member owned leased property working with AGFC biologists were 3.3 (95% CI
= 1.49 – 7.21) times more likely to want increased AGFC management assistance than those not
working with an AGFC biologist.
Harvest Management Summary
Across Arkansas, the primary harvest management practice being used by hunt camps in
excess of state regulations was restricted antlerless harvest (60%) (Table 14). The median rank
for the minimum 4-point rule was tied for first with restricted antlerless harvest. In each DMU,
restricted antlerless harvest (no button bucks) had a high median rank (M=1) (Tables 15-18). In
the Ozarks, MAV, and GCP, minimum 4-point rule was also ranked high (M=1), as was
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mandatory doe harvest in the MAV. In the Ozarks, MAV, and GCP, restricted buck harvest was
used frequently (M=2) (Tables 15, 17-18, respectively), while mandatory doe harvest was used
frequently in the Ouachitas (M=2) (Table 16). Harvest management practices such as mandatory
doe harvest before buck harvest and minimum spread restrictions were typically used less across
DMUs (M ≥ 4) except in the MAV, where minimum spread restrictions had median rank of 2.
Harvest Management Model Selection Results
Mandatory Doe Harvest
Model selection results for mandatory doe harvest being used instead of minimum 4-
point rule indicated 1 candidate model was supported [( QDM DMU,Π ): AICc wt = 0.65)]. Hunt
camps in the GCP were 2.3 (95% CI = 1.10 – 4.74) and 2.7 (95% CI = 1.30 – 5.61) times more
likely than hunt camps in the Ozarks and the MAV, respectively, to use mandatory doe harvest
rather than minimum 4-point rule. Hunt camps not under QDM were 2.8 (95% CI = 1.49 – 5.10)
times more likely than hunt camps under QDM to use mandatory doe harvest rather than
minimum 4-point rule. The best model indicated that respondent rankings were dependent upon
DMU and QDM, but that less evidence existed for an effect of property type. For instance,
model was 3 times more plausible than the highest ranked model containing
PROPTYPE ( ) and 9 times more plausible than the next highest ranked model
without DMU ( ). The sum of the normalized AIC
QDM DMU,Π
Π
Π
QDM DMU, Proptype,
QDM Proptype, c weights for models containing
QDM and DMU were 0.99 and 0.88, respectively, providing evidence that these predictors were
important in this model set. The summed AICC weight for models containing PROPTYPE was
only 0.29, indicating that PROPTYPE was a less important predictor relative to QDM and DMU.
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Model selection results for mandatory doe harvest being used rather than minimum antler
spread indicated that 2 models were plausible. The best model [( QDM DMU,Π ): AICc wt = 0.45)]
indicated that hunt camps in the Ozarks were 5.2 (95% CI = 1.32 – 20.5) times more likely than
hunt camps in the MAV to use mandatory doe harvest rather than minimum antler spread. Hunt
camps not under QDM were 3.0 (95% CI = 1.32 – 6.91) times more likely than hunt camps
under QDM to use mandatory doe harvest instead of minimum antler spread. The next best
model [( ): AICQDM Π c wt = 0.34)] suggested that hunt camps not under QDM were 3.1 (95% CI =
1.36 – 6.93) times more likely to use mandatory doe harvest instead of minimum antler spread.
The sum of the normalized AICc weights for this model set were 0.97 for QDM, 0.56 for DMU,
and 0.18 for PROPTYPE. All of the models that contained QDM were reasonably plausible
( <4), while models that did not contain QDM were not supported (i∆ i∆ >19).
Model selection results for mandatory doe harvest being used instead of restricted buck
harvest indicated 4 models were plausible. The top 3 models ( QDM Π : AICc wt = 0.31, Π :
AIC
DMU
c wt = 0.29, : AICProptypeΠ c wt = 0.17, respectively) did not suggest that hunt camps used
mandatory doe harvest more frequently than restricted buck harvest. The fourth model
( QDM DMU,Π : AICc wt = 0.11) indicated that hunt camps in the Ozarks were 3.9 (95% CI = 1.02 –
14.91) more likely to use mandatory doe harvest rather than restricted buck harvest. The sum of
the normalized AICc weights for this model set were 0.49 for QDM, 0.46 for DMU, and 0.29 for
PROPTYPE.
Model selection results for mandatory doe harvest being used rather than restricted
antlerless harvest (no button bucks) indicated 2 plausible models. In the best model ( Π :
AIC
DMU
c wt = 0.42) hunt camps in the MAV were 2.1 (95% CI = 1.04 – 4.35) times more likely than
19
hunt camps in the GCP to use mandatory doe harvest rather than restricted antlerless harvest.
The next best model ( : AICQDM DMU,Π c wt = 0.18) suggested that hunt camps in the Ouachitas and
MAV were 4.0 (95% CI = 1.04 – 15.51) and 2.1 (95% CI = 1.04 – 4.33) times, respectively,
more likely that hunt camps in the GCP to use mandatory doe harvest instead of restricted
antlerless harvest. The sum of the normalized AICc weights for this model set were 0.77 for
DMU, 0.35 for PROPTYPE, and 0.34 for QDM.
Doe Harvest Prior to Buck Harvest
Model selection results for doe harvest before buck harvest being used instead of
minimum 4-point rule indicated 3 plausible models. In the best model ( QDM Proptype,Π : AICc wt =
0.31) hunt camps on property owned by camp members were 4.0 (95% CI = 1.10 – 14.4) times
more likely that hunt camps on industry property to use doe harvest before buck harvest rather
than minimum 4-point rule. The next best model ( ProptypeΠ : AICc wt = 0.26) indicated that hunt
camps on property owned by camp members were more likely to use doe harvest before buck
harvest instead of minimum 4-point rule (4.8 (95% CI = 1.36 – 16.87)). The next model
( : AICQDM Π c wt = 0.19) suggested that hunt camps use of doe harvest before buck harvest
instead of minimum 4-point rule did not differ due to QDM.
Minimum 4-Point Rule
Model selection results for use of minimum 4-point rule instead of mandatory doe harvest
indicated that 4 candidate models were supported. In the best model ( ProptypeΠ : AICc wt = 0.35)
hunt camps on property owned by camp members were 1.8 (95% CI = 1.01 – 3.35) times more
likely than hunt camps on industry property to use minimum 4-point rule rather than mandatory
doe harvest. For the 2 next models ( DMUΠ : AICc wt = 0.20) and third ( QDMΠ : AICc wt = 0.15)
20
models, there was no evidence of differences in the estimated odds of minimum 4-point rule
being used rather than mandatory doe harvest across DMUs or QDM. The fourth model
( : AICQDM Proptype,Π c wt = 0.15) indicated that that hunt camps on property owned by camp
members were 1.9 (95% CI = 1.02 – 3.42) times more likely than hunt camps on industry
property to use minimum 4-point rule rather than mandatory doe harvest. The sum of the
normalized AICc weights for this model set were 0.58 for PROPTYPE, 0.39 for QDM, and 0.35
for DMU.
QDM DMU,Π
Model selection results for use of minimum 4-point rule rather than doe harvest before
buck harvest indicated 3 plausible models. In the best model ( ProptypeΠ : AICc wt = 0.34) hunt
camps on camp member owned property were 3.4 (95% CI = 1.07 – 10.81) times more likely
than hunt camps on privately owned leased property to use minimum 4-point rule instead of doe
harvest before buck harvest. The next best model ( QDM Proptype,Π : AICc wt = 0.28) indicated that
hunt camps on camp member owned property were more likely to use minimum 4-point rule
than hunt camps on leased property (3.6 [95% CI = 1.12 – 11.46]). In the third model ( QDM Π :
AICc wt = 0.21), use of minimum 4-point rule rather than doe harvest before buck harvest did not
differ due to QDM. The sum of the normalized AICc weights for this model set were 0.68 for
PROPTYPE, 0.57 for QDM, and 0.17 for DMU.
Model selection results for minimum 4-point rule being used instead of minimum spread
restriction indicated 2 plausible models. In the best model ( DMUΠ : AICc wt = 0.43) hunt camps in
the Ozarks were 3.6 (95% CI = 1.30 – 9.79) times more likely than hunt camps in the MAV to
use minimum 4-point rule rather than minimum spread restrictions. The next best model
( : AICc wt = 0.17) indicated that hunt camps in the Ozarks were more likely than hunt
21
camps in the MAV to use minimum 4-point rule rather than minimum spread restrictions (3.5
[95% CI = 1.27 – 9.66]). The sum of the normalized AICc weights for this model set were 0.78
for DMU, 0.35 for QDM, and 0.31 for PROPTYPE.
Model selection results for minimum 4-point rule being used rather than restricted buck
harvest indicated 1 plausible model. In the best model ( QDMΠ : AICc wt = 0.59) the estimated
odds of using minimum 4-point rule instead of restricted buck harvest did not differ whether a
hunt camp practices QDM or not. The sum of the normalized AICC weights for this model set
were 0.69 for QDM, 0.29 for PROPTYPE, and 0.13 for DMU.
Model selection results for minimum 4-point rule being used instead of restricted
antlerless harvest (no button bucks) indicated that 2 models were plausible. In the best model
( : AICQDM Proptype,Π c wt = 0.55) hunt camps on leased property were 2.5 (95% CI = 1.10 – 5.53)
times more likely than hunt camps on industry property to use minimum 4-point rule instead of
restricted antlerless harvest. In the best model, hunt camps under QDM were 2.5 (95% CI = 1.38
– 4.57) times more likely than hunt camps not under QDM to use minimum 4-point rule rather
than restricted antlerless harvest. In the next best model ( QDMΠ : AICc wt = 0.34) hunt camps
under QDM were more likely to use minimum 4-point rule than restricted antlerless harvest (2.3
(95% CI = 1.27 – 4.06)). The sum of the normalized AICc weights for this model set were 0.98
for QDM, 0.62 for PROPTYPE, and 0.09 for DMU.
Minimum Spread Restriction
Model selection results for use of minimum antler spread rather than mandatory doe
harvest indicated 1 model was plausible. In the best model ( ProptypeΠ : AICc wt = 0.53) hunt camps
on property owned by camp members were 2.9 (95% CI = 1.24 – 6.88) times more likely than
camps on industry property to use minimum spread restrictions instead of mandatory doe
22
harvest. The sum of the normalized AICc weights for this model set were 0.82 for PROPTYPE,
0.31 for QDM, and 0.21 for DMU.
Model selection results for use of minimum spread restrictions instead of minimum 4-
point rule indicated 2 plausible models. In the best model ( DMUΠ : AICc wt = 0.48), hunt camps in
the Ouachitas were 7.5 (95% CI = 1.03 – 54.95) and 6.9 (95% CI = 1.11 – 42.79) times more
likely than hunt camps in the Ozarks and the MAV, respectively, to use minimum spread
restrictions than minimum 4-point rule. In the best model, hunt camps in the GCP were 2.7
(95% CI = 1.04 – 6.87) times more likely than hunt camps in the MAV to use minimum spread
restrictions instead of a minimum 4-point rule. In the next best model ( QDM DMU,Π : AICc wt =
0.21) hunt camps in the Ouachitas and GCP were 6.7 (95% CI = 1.08 – 42.13) and 2.6 (95% CI =
1.02 – 6.79) times more likely than hunt camps in the MAV to use minimum spread restrictions
instead of minimum 4-point rule. Models containing PROPTYPE were at least 9 times less
likely to be the best fitting model in this set, indicating that little evidence existed for an effect of
property type on use of spread restrictions rather than minimum 4-point rule. The sum of the
normalized AICc weights for this model set were 0.89 for DMU, 0.36 for QDM, and 0.23 for
PROPTYPE.
Model selection results for use of minimum spread restrictions rather than restricted buck
harvest indicated 2 plausible models. For these 2 candidate models ( QDM Proptype,Π : AICc wt =
0.47, : AICProptypeΠ c wt = 0.26), hunt camps on non-members owned property were 4.8 (95% CI =
1.38 – 16.78) and 3.6 (95% CI = 1.11 – 11.41), times, respectively, more likely than hunt camps
on property owned by camp members and industry property, respectively, to use minimum
spread restrictions rather than restricted buck harvest. The sum of the normalized AICc weights
for this model set were 0.85 for PROPTYPE, 0.69 for QDM, and 0.15 for DMU.
23
Restricted Buck Harvest
Model selection results for use of restricted buck harvest instead of mandatory doe
harvest indicated that 3 models were plausible. In the best model ( ProptypeΠ : AICc wt = 0.32) hunt
camps on property owned by camp members were 1.9 (95% CI = 1.04 – 3.45) times more likely
to use restricted buck harvest rather than mandatory doe harvest. The next best model
( : AICQDM Proptype,Π c wt = 0.30) hunt camps on property owned by camp members were 1.9 (95%
CI = 1.07 – 3.59) times more likely to use restricted buck harvest instead of mandatory doe
harvest. In the next model ( Π : AICQDM c wt = 0.21) the estimated odds of a hunt camps using
restricted buck harvest rather than mandatory doe harvest did not differ whether a hunt camp was
QDM or not. The sum of the normalized AICc weights for this model set were 0.73 for
PROPTYPE, 0.59 for QDM, and 0.15 for DMU.
Model selection results for restricted buck harvest being used instead of minimum 4-point
rule indicated that 2 models were plausible. In the best model ( QDM DMU,Π : AICc wt = 0.40) hunt
camps in the GCP were 2.5 (95% CI = 1.25 – 5.06) times more likely that hunt camps in the
MAV to use restricted buck harvest rather than minimum 4-point rule. In the best model, hunt
camps not under QDM were 2.1 (95% CI = 1.07 – 3.90) times more likely that hunt camps under
QDM to use restricted buck harvest instead of minimum 4-point rule. In the next best model
( : AICQDM Π c wt = 0.26) hunt camps not under QDM were more likely to use restricted buck
harvest rather than minimum 4-point rule (2.2 (95% CI = 1.12 – 4.04)). The sum of the
normalized AICc weights for this model set were 0.86 for QDM, 0.61 for DMU, and 0.24 for
PROPTYPE.
24
Model selection results for restricted buck harvest being used instead of minimum spread
restrictions indicated 4 plausible models. Across these 4 candidate models ( : AICDMUΠ c wt =
0.37, : AICDMU Proptype,Π c wt = 0.28, Π : AICQDM DMU, c wt = 0.20, QDM DMU, Proptype, Π : AICc wt = 0.14)
hunt camps in the Ozarks, Ouachitas, and GCP were 6.0, 9.5, and 2.7 times, respectively, more
likely than hunt camps in the MAV to use restricted buck harvest instead of minimum antler
restrictions. The sum of the normalized AICc weights for this model set were 0.99 for QDM,
0.60 for DMU, and 0.16 for PROPTYPE.
Model selection results for restricted buck harvest being used rather than restricted
antlerless harvest indicated that 3 models were plausible. In the best model ( : AICQDMΠ c wt =
0.36) hunt camps under QDM were 2.1 (95% CI = 1.19 – 3.79) times more likely to use
restricted buck harvest than restricted antlerless harvest than hunt camps not under QDM. In the
next best model ( Π : AICQDM Proptype,
QDM DMU,
c wt = 0.35) hunt camps on member owned private property
were 1.84 (95% CI = 1.01 – 3.36) times more likely than hunt camps on industry property to use
restricted buck harvest instead of restricted antlerless harvest. Both the second and third model
( , Π AICQDM Proptype,Π c wt = 0.20) indicated that hunt camps under QDM were more likely
(2.23 (95% CI = 1.24 – 4.03) and 2.31 (95% CI = 1.27 – 4.22)) to use restricted buck harvest
instead of restricted antlerless harvest. The sum of the normalized AICc weights for this model
set were 0.96 for QDM, 0.43 for PROPTYPE, and 0.28 for DMU.
Restricted Antlerless Harvest (no Button Bucks)
Model selection results for restricted antlerless harvest being used rather than mandatory
doe harvest indicated 1 plausible model. In the best model ( QDM Π : AICc wt = 0.57) we found no
evidence that hunt camps used restricted antlerless harvest instead of mandatory doe harvest
25
based on QDM. The sum of the normalized AICc weights for this model was 0.79 for QDM,
0.24 for PROPTYPE, and 0.22 for DMU.
Model selection results for restricted antlerless harvest being used instead of minimum 4-
point rule indicated that 3 models were plausible. Each of these 3 models ( Π : AICQDM c wt =
0.38, : AICQDM DMU,Π c wt = 0.30, Π : AICQDM Proptype, c wt = 0.20) indicated that hunt camps not under
QDM were more likely than camps under QDM to use restricted antlerless harvest rather than
minimum 4-point rule (2.1 (95% CI = 1.29 – 3.37); 2.1 (95% CI = 1.31 – 3.46); and 2.1 (95% CI
= 1.27 – 3.34)), respectively. The sum of the normalized AICc weights for this model was 0.99
for QDM, 0.41 for DMU, and 0.31 for PROPTYPE.
Model selection results for restricted antlerless harvest being used rather than restricted
buck harvest indicated that 2 models were plausible. In the best model ( QDM DMU,Π : AICc wt =
0.52) hunt camps in the GCP were 2.0 (95% CI = 1.06 – 2.95) times more likely than hunt camps
in the MAV to use restricted antlerless harvest instead of restricted buck harvest. The best model
also indicated that hunt camps not under QDM were 2.2 (95% CI = 1.36 – 3.51) times more
likely than those under QDM to use restricted antlerless harvest instead of restricted buck
harvest. In the next best fitting model ( QDM Π : AICc wt = 0.31) hunt camps not under QDM were
2.2 (95% CI = 1.36 – 3.51) times more likely than hunt camps under QDM to use restricted
antlerless harvest instead of restricted buck harvest. The sum of the normalized AICc weights for
this model were 0.99 for QDM, 0.60 for DMU, and 0.16 for PROPTYPE.
Hunt Camp Habitat Management Summary
Across Arkansas, 70% of hunt camps used winter food plots as their primary habitat
management practice, while 60% and 50% of hunt camps also used supplemental feeding and
supplemental minerals, respectively (Table 19). Nearly 2.5 times more hunt camps used winter
26
food plots rather than summer food plots (673 versus 284) as their primary habitat management
practice, and approximately 2 times as many hunt camps used supplemental feeding rather than
summer food plots (605 versus 284). Few hunt camps used timber management (30%),
fertilization of natural vegetation (28%), set-aside programs (19%), and prescribed burning
(11%) as their primary habitat management practice. In each DMU, winter food plots had the
highest median rank (M=1) (Tables 20-23). In the Ozarks, summer food plots and supplemental
feeding were also ranked high (M=1) (Table 20), while supplemental feeding and supplemental
minerals were highly utilized in the MAV and GCP (Tables 22 – 23). In the Ouachitas,
supplemental feeding and supplemental minerals were used commonly (M=2) (Table 21).
Habitat management practices such as prescribed burning, timber management, and set-aside
programs were typically used less across DMUs (M ≥ 5) except in the MAV, where timber
management had a median rank of 2. Across Arkansas, hunt camps had used timber
management the longest (12 years) (Table 24). In each DMU, timber harvest had been used the
longest, and there were few differences between other practices in the amount of time they had
been in use (Table 24).
Habitat Management Model Selection Results
Summer Food Plots
Model selection results for use of summer food plots instead of winter food plots as a
habitat management practice on camp property indicated 1 plausible model. In the best model
( : AICProptypeΠ c wt = 0.87) hunt camps on non-member owned leased property were 2.6 (95% CI
= 1.41 – 3.86) and 2.1 (95% CI = 1.09 – 3.39) times more likely than hunt camps on property
owned by members and industry property, respectively, to use summer food plots than winter
27
food plots. The best model ( Π ) was nearly 16 times more plausible than any other model
in the candidate set.
Proptype
Model selection results for summer food plots being used rather than supplemental
feeding indicated that 1 model was plausible. In the best model ( DMUΠ : AICc wt = 0.62) hunt
camps in the Ozarks and the MAV were 1.8 (95% CI = 1.14 – 2.93) and 3.0 (95% CI = 1.71 –
5.36) times more likely, respectively, than hunt camps in the GCP to use summer food plots
rather than supplemental feeding.
Model selection results for summer food plots being used instead of supplemental
minerals indicated that 1 model was plausible. For this model ( DMUΠ : AICc wt = 0.59), we found
no differences in the use of summer food plots instead of supplemental minerals across DMUs.
Winter Food Plots
Model selection results for use of winter food plots rather than summer food plots
indicated 4 plausible models. In the best model ( ProptypeΠ : AICc wt = 0.30) hunt camps on
industry property were 1.9 (95% CI = 1.34 – 2.60) and 1.7 (95% CI = 1.16 – 2.61) times more
likely than hunt camps on hunt camp member owned property and non-member owned leased
property, respectively, to use winter food plots rather than summer food plots. In the next best
model ( : AICDMU Proptype,Π c wt = 0.27) hunt camps on industry property were 1.5 (95% CI = 1.02 –
2.22) times more likely than hunt camps on member owned property to use winter food plots
instead of summer food plots. The second model ( DMU Proptype,Π ) also indicated that hunt camps in
the GCP were 1.7 (95% CI = 1.09 – 2.52) times more likely than hunt camps in the Ozarks to use
winter food plots rather than summer food plots. In the third model ( DMUΠ : AICc wt = 0.16) hunt
camps in the Ouachitas and GCP were 2.0 (95% CI = 1.04 – 3.93) and 2.1 (95% CI = 1.45 –
28
2.99) times, respectively, more likely than hunt camps in the Ozarks to use winter food plots
instead of summer food plots. In the fourth model ( QDM DMU, Proptype,Π : AICc wt = 0.14) hunt camps
in the GCP were more likely than hunt camps in the Ozarks to use winter food plots instead of
summer food plots (1.7 (95% CI = 1.09 – 2.53), and that hunt camps on industry lands were 1.5
(95% CI = 1.02 – 2.23) and 1.5 (95% CI = 1.02 – 2.35) times, respectively, more likely, than
hunt camps on camp member owned property and non-member owned least property to use
winter food plots instead of summer food plots.
QDM DMU, Proptype,
DMU, Proptype,
Model selection results for winter food plots being used rather than supplemental feeding
indicated 1 plausible model. In the best model ( Π : AICc wt = 0.86) hunt camps in
the Ouachitas and the MAV were 2.1 (95 %CI = 1.20 – 3.75) and 2.3 (95% CI = 1.47 – 3.47)
times more likely than hunt camps in the GCP to use winter food plots instead of supplemental
feeding. The best model also indicated that hunt camps under QDM were 1.6 (95% CI = 1.24 –
2.16) times more likely than those not under QDM to use winter food plots rather than
supplemental feeding.
Model selection results for use of winter food plots rather than supplemental minerals
indicated that 1 model was plausible. In the best model ( QDM Π : AICc wt = 0.55) hunt
camps under QDM were 1.5 (95% CI = 1.14 – 1.98) times more likely than hunt camps not
under QDM to use winter food plots instead of supplemental minerals. The best model also
indicated that hunt camps in the Ouachitas were 1.9 (95% CI = 1.07 – 3.43) times more likely
than hunt camps in the GCP to use winter food plots rather than supplemental minerals.
Supplemental Feeding
Model selection results for use of supplemental feeding instead of summer food plots
indicated that 4 models were plausible. In the best model ( Acre DMU, Proptype,Π : AICc wt = 0.31) hunt
29
camps on industry property were 2.3 (95% CI = 1.51 – 3.61) times more likely than hunt camps
on member owned private property to use supplemental feedings rather than summer food plots.
The best model also indicated that hunt camps in the GCP were more likely to use supplemental
feeding than hunt camps in the Ozarks (1.8 (95% CI = 1.14 – 2.77)). The second model
( : AICAcre Proptype,Π c wt = 0.22) suggested that hunt camps on industry property were 3.2 (95% CI =
2.19 – 4.54) and 1.8 (95% CI = 1.19 – 2.78) times, respectively, more likely than hunt camps on
member owned private property or non-member owned leased property to use supplemental
feeding rather than summer food plots. The third and fourth models ( Acre QDM, DMU, Proptype,Π : AICc
wt = 0.22, : AICQDM DMU, Proptype,Π c wt = 0.15) both indicated that hunt camps on industry property
were more likely than hunt camps on member owned property to use supplemental feeding
instead of summer food plots (2.3(95% CI = 1.49 – 3.57)) and (2.0 (95% CI = 1.33 – 3.09)),
respectively, and that hunt camps in the GCP were more likely to use supplemental feeding
instead of summer food plots than hunt camps in the Ozarks (1.8 (95% CI = 1.14 – 2.77)) and
MAV (1.73 (95% CI = 1.11 – 2.68)), respectively. The fourth model also indicated that hunt
camps not under QDM were 1.4 (95% CI = 1.02 – 1.87) times more likely than hunt camps
under QDM to use supplemental feeding rather than summer food plots.
Acre DMU,
Model selection results for supplemental feeding being used instead of winter food plots
indicated that 2 models were plausible. In the best model ( Proptype,Π : AICc wt = 0.48) hunt
camps on industry property were 2.0 (95% CI = 1.29 – 3.01) times more likely than hunt camps
on camp member owned private property to use supplemental feeding instead of winter food
plots. The best mode also indicated that hunt camps in the Ozarks, Ouachitas and the GCP were
3.2 (95% CI = 1.55 – 6.56), 2.7 (95% CI = 1.06 – 6.61), and 3.4 (95% CI = 1.67 – 6.76) times,
respectively, more likely than camps in the MAV to use supplemental feeding instead of winter
30
food plots. In the next best model ( Π : AICAcre QDM, DMU, Proptype,
DMU
c wt = 0.22) hunt camps in the
Ozarks, Ouachitas, and GCP were 3.2 (95% CI = 1.28 – 6.57), 2.7 (95% CI = 1.06 – 6.62), and
3.4 (95% CI = 1.67 – 6.78) times, respectively, more likely than camps in the MAV to use
supplemental feeding instead of winter food plots. The next best model also indicated that hunt
camps on industry property were 2.0 (95% CI = 1.28 – 2.99) times more likely than hunt camps
on member owned private property to use supplemental feeding rather than winter food plots.
Model selection results for use of supplemental feeding instead of supplemental minerals
indicated 4 plausible models. In the best model ( Π : AICc wt = 0.31) hunt camps in the
Ouachitas were 2.1 (95% CI = 1.05 – 4.08), 2.6 (95% CI = 1.23 – 5.32), and 1.9 (95% CI = 1.02
– 3.51) times, respectively, more likely than responding hunt camps in the Ozarks, MAV, and
GCP to use supplemental feeding rather than supplemental minerals. The second model
( : AICQDM DMU, Proptype,Π
ProptypeΠ
c wt = 0.19) indicated that hunt camps in the Ouachitas were 2.4 (95% CI =
1.13 – 5.14) and 1.9 (95% CI = 1.04 – 3.63) times, respectively, more likely to use supplemental
feeding instead of supplemental minerals than hunt camps in the MAV or GCP. In the third
model ( : AICc wt = 0.19) we found no differences between property types in the odds of
using supplemental feeding instead of supplemental minerals. In the fourth model ( :
AIC
DMU Proptype,Π
c wt = 0.16) hunt camps in the Ouachitas were 1.9 (95% CI = 1.04 – 3.63) times more likely
than hunt camps in the GCP to use supplemental feeding rather than supplemental minerals.
Supplemental Minerals
Model selection results for supplemental minerals being used rather than summer food
plots indicated 5 plausible models. The first model ( QDM DMU, Proptype,Π : AICc wt = 0.25) indicated
that hunt camps on industry property were 2.4 (95% CI = 1.59 – 3.71) and 1.6 (95% CI = 1.03 –
31
2.59) times more likely to use supplemental minerals instead of summer food plots than hunt
camps on member owned private property and non-camp member owned leased property,
respectively. The first model also indicated that hunt camps in the Ouachitas were 3.0 (95% CI
= 1.29 – 7.08) times more likely than hunt camps in the Ozarks to use supplemental minerals
instead of summer food plots. The second model ( Acre DMU, Proptype,Π : AICc wt = 0.24) indicated that
hunt camps on non-member owned leased property were 1.6 (95% CI = 1.01 – 2.47) times more
likely than hunt camps on member owned property to use supplemental mineral instead of
summer food plots and that hunt camps on industry property were 2.7 (95% CI = 1.76 – 4.22)
and 1.7 (95% CI = 1.08 – 2.74) more times more likely to use supplemental minerals rather than
hunt camps on member owned private property and non-member owned leased property,
respectively. The second model also indicated that hunt camps in the Ouachitas were 3.0 (95%
CI = 1.30 – 7.17) times more likely than hunt camps in the Ozarks to use supplemental minerals
instead of summer food plots. The third model ( DMU Proptype,Π : AICc wt = 0.16) indicated that hunt
camps on industry property were 2.4 (95% CI = 1.56 – 3.60) times more likely than hunt camps
on non-member owned leased property to use supplemental mineral instead of summer food
plots. The third model also indicated that hunt camps in the Ouachitas were 3.0 (95% CI = 1.27
– 6.97) times more likely than hunt camps in the Ozarks to use supplemental minerals rather than
summer food plots. The fourth model ( Acre QDM, DMU, Proptype,Π : AICc wt = 0.16) indicated that hunt
camps on industry property were 2.7 (95% CI = 1.76 – 4.22) and 1.8 (95% CI = 1.09 – 2.78)
times more likely to use supplemental minerals instead of summer food plots than hunt camps on
member owned private property and non-member owned leased property, respectively. The
fourth model also suggested that hunt camps in the Ouachitas were 3.1 (95% CI = 1.31 – 7.26)
times more likely than hunt camps in the Ozarks to use supplemental minerals instead of summer
32
food plots. The fifth model ( : AICAcre Proptype,Π c wt = 0.11) indicated that hunt camps on industry
property were 3.2 (95% CI = 2.18 – 4.57) and 1.9 (95% CI = 1.24 – 2.98) times more likely than
hunt camps on camp member owned property and non member owned leased property to use
supplemental minerals instead of summer food plots. The fifth model also indicated that hunt
camps on non-member owned leased property were 1.7 (95% CI = 1.07 – 2.54) times more likely
than hunt camps on camp member owned property to use supplemental minerals higher than
summer food plots.
Model selection results for use of supplemental minerals rather than winter food plots
indicated 1 plausible model. In the best model ( DMUΠ : AICc wt = 0.62) hunt camps in the GCP
were 1.6 (95% CI = 1.03 – 2.45) and 2.9 (95% CI = 1.63 – 5.21) times, respectively, more likely
that hunt camps in the Ozarks and MAV to use supplemental minerals instead of winter food
plots. The best model also suggested that hunt camps in the Ouachitas were 2.4 (95% CI = 1.03
– 5.55) times more likely than hunt camps in the MAV to use supplemental minerals rather than
winter food plots.
Model selection for use of supplemental minerals instead of supplemental feeding
indicated 2 plausible models. For these 2 models, [( ProptypeΠ : AICc wt = 0.55); ( : AICAcre Proptype,Π c
wt = 0.23) we found no differences in the odds of using supplemental minerals rather than
supplemental feeding across property types and camp size.
Hunt Camp Management for Other Wildlife
Species Management
Across Arkansas, 80% of hunt camps stated that they managed turkeys most frequently
(Table 25). Other than managing for turkeys, there was not a tendency to manage for any
particular species or species group across Arkansas (Table 25). In each DMU, turkeys were
33
managed for most frequently (M=1) (Tables 26-29). In the MAV, deer camp properties managed
for waterfowl (M=1) in addition to turkeys (Table 28). Across DMUs, few hunt camps managed
for elk, feral hogs, furbearers or non-game species (M ≥ 7).
About 50% of hunt camps responded that they actively conducted habitat management
for wildlife other than white-tailed deer. Across Arkansas, hunt camps used mowing/grassland
management (66%) and timber management (51%) most often as habitat management practices
for wildlife (Table 30). As was found across Arkansas, hunt camps primarily used mowing or
grassland management when managing for other wildlife in all DMUs (Tables 31-34). In the
MAV hunt camps frequently conducted timber management (M=1), and flooding fields for
waterfowl (M=1) (Table 33). In the GCP, hunt camps used timber management most often
(M=1) (Table 34). Hunt camps in the Ozarks, Ouachitas, and GCP typically did not conduct any
management for waterfowl (either flooding fields or nest platforms/boxes) (Tables 31, 32, and
34), while hunt camps in the MAV and GCP typically did not manage for songbirds (Tables 33
and 34).
Results from Hunt Camp Management
A majority of respondents (57%) stated that they had seen an increase in the number of
bucks > 2.5 years old on their deer camps since they began using harvest and habitat
management practices on their property (Table 35). Seventy-seven percent of respondents stated
that they had not seen an increase in the number of > 4.5 years old, while 65% felt that they did
not have a more equal ratio of bucks to does on their deer camps property (Table 35). Seventy-
two percent of responding hunt camps did not collect biological data off of deer harvest by camp
members (Table 36). A majority (60%) of those camps that collect biological data from deer
harvested on deer camp properties were located in the GCP (Table 37). However, proportionally
34
fewer hunt camps in the Ozarks (20%) and GCP (28%) collected biological data from harvested
deer than in the Ouachitas (31%) and MAV (35%). A majority of the hunt camps collecting
biological data were located on industry lands (60%) and proportionally more hunt camps
collected biological data from harvested deer on industry property (36%) than other property
types (Table 38).
Only 19% of hunt camps worked with an AGFC biologist in establishing deer harvest and
habitat management guidelines (Table 39). Of the 19% of hunt camps that work with an AGFC
biologist, 38% were on privately owned lands, and 40% were on industry lands while only 19%
were on private leased lands (Table 40). Regionally, a majority (53%) of hunt camps working
with an AGFC biologist were in the GCP (Table 41). Sixty percent of responding deer camps
that worked with an AGFC biologist kept biological data from deer harvested by camp members,
while only 20% of those not working with a biologist keep biological data (Table 42). In
Arkansas, only 30% of the hunt camps have sought outside management assistance or advice on
harvest and habitat management from biologists (Table 43).
Hunt Camp Management Assistance Programs Summary
Across Arkansas, a majority of hunt camps (56%) felt that the management assistance
program that would most benefit/interest their hunt camp was recommendations from a wildlife
biologist (Table 44). Hunt camps also stated that wildlife management assistance programs
(49%), population estimation (47%), and habitat development (43%) would most benefit/interest
their camps. Management assistance programs such as public information (29%), hunter
education (22%), and non-game management (7%) were less important to hunt camps. In each
DMU, wildlife biologist recommendations had a high median rank (M=1) (Table 45-48). In the
Ozarks and GCP, wildlife management assistance programs were also ranked high (Tables 45
35
and 48), as was population estimation in the GCP. In each DMU, hunt camps were frequently
interested in habitat development programs, while wildlife management assistance programs and
population estimation commonly interested hunt camps in the Ouachitas and MAV (M=2) (Table
46-47). Hunt camps were typically less interested in management assistance programs such as
public information, hunter education, and non-game management assistance across DMUs (M
≥4), except in the Ouachitas, where hunter education had a median rank of 3.
Management Assistance Programs Model Selection Results
Public Information Programs
Model selection results for public information programs being more beneficial than
hunter educational programs indicated that 7 models were plausible. In the best model
( : AICQDM DMU,Π c wt = 0.19) hunt camps in the MAV and the GCP were 10.2 (95% CI = 2.11 –
49.26) and 3.7 (95% CI = 1.05 – 13.32) times more likely, respectively, than hunt camps in the
Ouachitas to feel that they would benefit more from public information programs than hunter
educational programs. The second model ( Biologist Contact, QDM, DMU, Proptype,Π : AICc wt = 0.17) indicated
that hunt camps in the MAV were 3.6 (95% CI = 1.02 – 12.55) and 11.3 (95% CI = 1.26 – 60.98)
times, respectively, more likely, to feel that they would benefit from public information
programs than respondents in the Ozarks and Ouachitas. The second model also indicated that
hunt camps in the GCP were 5.4 (95% CI = 1.38 – 21.05) times more likely than hunt camps in
the Ouachitas to feel that they would benefit from public information programs. In the second
model hunt camps that do not work with an AGFC biologist were 2.3 (95% CI = 1.03 – 5.29)
times more likely than hunt camps working with an AGFC biologist to feel that they would
benefit from public information programs. The third model ( QDM Proptype,Π : AICc wt = 0.11)
indicated that hunt camps on member owned property were 2.3 (95% CI = 1.15 – 4.70) times
36
more likely than hunt camps on industry property to feel that they would benefit from public
information programs more than hunter educational programs. The fourth model ( :
AIC
DMU Proptype,Π
c wt = 0.11), and fifth model ( : AICContact DMU,Π c wt = 0.11) both suggested that hunt camps in
the MAV and GCP were more likely than hunt camps in the Ouachitas to feel that they would
benefit from public information programs than hunter educational programs. The sixth model
( : AICProptypeΠ c wt = 0.09) indicated the same results as those found in the third model, and the
seventh model ( : AICDMUΠ C wt = 0.08) had the same results as those in the first and fourth
models.
BiologistΠ
BiologistΠ
Hunter Educational Programs
Model selection results for hunter educational programs being more beneficial than
public information programs indicated that 3 models were plausible. For these three models
( : AICc wt = 0.37, Π : AICQDM c wt = 0.22, DMUΠ : AICc wt = 0.14) we found no differences
in the odds of a hunt camp benefiting more from hunter educational programs rather than public
informational programs.
Wildlife Management Assistance Programs
Model selection results for wildlife management assistance programs (WMAP) being
more beneficial than management recommendations from a biologist indicated that 3 models
were plausible. The first two models ( : AICc wt = 0.40, QDMΠ : AICc wt = 0.17) indicated
no differences in the odds of hunt camps thinking that WMAP is more beneficial than
management recommendations from a biologist. The third model ( ProptypeΠ : AICc wt = 0.15)
suggested that hunt camps on property owned by camp members were 1.8 (95% CI = 1.06 –
37
2.99) times more likely than hunt camps on industry property to feel that they would benefit
from WMAP rather than biologist recommendations.
Model selection results for WMAP being more beneficial than population estimation
indicated that 1 model was plausible. In the best model ( Contact DMU,Π : AICc wt = 0.45) hunt camps
in the Ozarks were 2.2 (95% CI = 1.27 – 3.67) times more likely than respondents in the GCP to
feel that they would benefit from WMAP rather than population estimation. The best model also
indicated that landowners were 2.2 (95% CI = 1.19 – 4.13) times more likely than camp
managers to feel that their camp would benefit from WMAP rather than population estimation.
Model selection results for WMAP being more beneficial than habitat development
indicated that 2 models were plausible. In the best model ( Contact Proptype,Π : AICc wt = 0.40) camp
mangers were 2.8 (95% CI = 1.43 – 5.36) times more likely than landowners to feel that WMAP
is more beneficial than habitat development assistance. The next best model ( Π : AICBiologist c wt =
0.31) suggested that hunt camps not working with an AGFC biologist were 1.6 (95% CI = 1.05 -
2.35) times more likely than camps working with an AGFC biologist to feel that WMAP
programs would be more beneficial than habitat development assistance.
Management Recommendations from a Biologist
Model selection results for management recommendations from a biologist being more
beneficial than WMAP indicated that 2 models were plausible. In the best model ( :
AIC
BiologistΠ
c wt = 0.59) hunt camps not working with an AGFC biologist were 1.7 (95% CI = 1.15 –
2.37) times more likely than hunt camps working with a AGFC biologist to feel that management
recommendations from a biologist are more beneficial than WMAP. The next best model
( : AICBiologist Contact, QDM, DMU, Proptype,Π c wt = 0.25) suggested that hunt camps on member owned
private property were 1.9 (95% CI = 1.05 -3.54) times more likely than hunt camps on non-
38
member owned leased property to feel that management recommendations are more beneficial
than WMAP. The next best model also indicated that hunt camps under QDM were 1.5 (95% CI
= 1.05 – 2.13) times more likely than camps not under QDM to feel that management
recommendations are more beneficial than WMAP. The second model also indicated that camp
managers were 1.9 (95%CI = 1.06 – 3.52) times more likely than landowners to benefit from
management recommendations rather than WMAP. The second model also indicated that hunt
camps that not working with an AGFC biologist were more likely than those working with an
AGFC biologist to benefit from management recommendations rather than WMAP (1.9 (95% CI
= 1.33 – 2.96)).
Model selection results for management recommendations from a wildlife biologist being
more beneficial than population estimation indicated that 6 models were plausible. In the best
model ( : AICDMU Proptype,Π c wt = 0.22) hunt camps on member owned private property were 1.7
(95% CI = 1.04 – 2.66) times more likely to think that management recommendations were more
beneficial than population estimation than hunt camps on non-member owned leased property.
The best model also suggested that hunt camps in the Ozarks were 1.9 (95% CI = 1.13 – 3.09)
times more likely than hunt camps in the GCP to feel that management recommendations were
more beneficial than population estimation. The second model ( ProptypeΠ : AICc wt = 0.21)
indicated that hunt camps on privately owned camp member property were 1.8 (95% CI = 1.18 –
2.94) and 1.9 (95% CI = 1.37 – 2.84) times more likely than hunt camps on leased property or
hunt camps on industry property, respectively, to think management recommendations were
more beneficial that population estimation. The third model ( DMUΠ : AICc wt = 0.15) indicated
that hunt camps in the Ozarks and the MAV were 2.2 (95% CI = 1.46 – 3.42) and 1.7 (95% CI =
1.05 – 2.79) times more likely, respectively, than hunt camps in the GCP to feel that their hunt
39
camps would benefit more from management recommendations than population estimation. The
fourth model ( Π : AICQDM Proptype,
Contact DMU,
c wt = 0.13) indicated that hunt camps on member owned private
property were 1.9 (95% CI = 1.19 – 2.99) and 2.0 (95% CI = 1.37 – 2.84) times more likely,
respectively, than hunt camps on non-member owned leased property and industry property to
feel that management recommendations were more beneficial than population estimation. The
fifth model ( : AICΠ c wt = 0.09) and sixth model ( QDM DMU,Π : AICc wt = 0.09) both
suggested that hunt camps in the Ozarks were 1.9 (95% CI = 1.19 – 3.06) and 2.2 (95% CI =
1.46 – 3.41) times more likely than hunt camps in the GCP to feel that management
recommendations were more beneficial than population estimation, while the sixth model also
indicated that hunt camps in the MAV were 1.7 (95% CI = 1.06 – 2.85) times more likely than
hunt camps in the GCP to feel that management recommendations were more beneficial than
population estimation.
Biologist
Model selection results for management recommendations for a biologist being more
beneficial than habitat development assistance indicated that 2 models were plausible. In the
best model ( Π : AICc wt = 0.52) hunt camps not working with an AGFC biologist were 1.5
(95% CI = 1.02 – 2.12) times more likely than hunt camps working with an AGFC biologist to
feel that management recommendations would be more beneficial than habitat development
assistance. In the second model ( Π : AICContact Proptype, c wt = 0.27) hunt camps on member owned
private property were 2.1 (95% CI = 1.16 – 3.84) and 1.8 (95% CI = 1.03 – 3.21) times more
likely, respectively, than hunt camps on non-member owned leased property and industry
property, to feel that management recommendations were more beneficial than habitat
development. The second model also suggested that camp managers were 2.4 (95% CI = 1.26 –
40
4.43) times more likely than land managers to benefit more from management recommendations
than habitat development.
Population/Density Estimation
Model selection results for population estimation being more beneficial than WMAP
indicated that 4 models were plausible. In the first 3 models ( BiologistΠ : AICc wt =
0.29, Π : AICQDM Proptype,
Proptype
c wt = 0.21, Π : AICQDM c wt = 0.20) we found no differences in hunt camps
regarding population estimation being more beneficial than WMAP. The fourth model
( : AICΠ c wt = 0.17) suggested that hunt camps on industry property were 1.7 (95% CI =
1.03 – 2.64) times more likely than hunt camps on member owned property to get more benefit
from population estimation than WMAP.
Model selection results for population estimation being more beneficial than management
recommendations from a biologist indicated that 6 models were plausible. Results across this set
of models indicated no differences between hunt camps regarding population estimation and
management recommendations from a biologist.
Habitat Development Management Assistance
Model selection results for habitat development being more beneficial than WMAP
indicated that 1 model was plausible. The best model ( BiologistΠ : AICc wt = 0.40) indicated that
hunt camps not working with an AGFC biologist were 1.8 (95% CI = 1.17 – 2.65) times more
likely than hunt camps working with a AGFC biologist to get more benefit from habitat
development than WMAP.
Model selection results for habitat development being more beneficial than management
recommendations from a biologist indicated that 5 models were plausible. Results across this set
41
of models indicated no differences between hunt camps regarding habitat development and
management recommendations from a biologist.
Hunt Camp Information Interests
Across Arkansas, other than information on prescribed burning, clubs were interested in
all other information types (Table 49). Across DMUs, hunt camps were typically not as
interested in information on hunting techniques, forest management, or prescribed burning, (M ≤
3), except in the Ozarks, where forest management had a median rank of 4 (Table 50).
Proportional Odds Modeling
Camp managers were 1.6 (95% CI = 1.08 – 2.33) times more likely to be more interested
in information on white-tailed deer behavior than landowners. Camps on member owned private
property were 1.9 (95% CI = 1.25 – 2.89) times more likely to be interested forest management
information than camps on non-member owned leased property and 1.8 (95% CI = 1.21 – 2.72)
times more likely than camps on industry land to be interested forest management information.
Hunt camps in the Ozarks were 1.6 (95% CI = 1.08 – 2.47) times more likely to be interested
forest management information than camps in the MAV and 1.7 (95% CI = 1.17 – 2.41) times
more likely than camps in the GCP. Camp managers were 1.9 (95% CI = 1.09 – 9.37) times
more likely to be interested forest management information than landowners, while land
managers were 1.6 (95% CI = 1.05 – 2.53) times more likely to be interested forest management
information than camp managers. Camps on member owned private property were 1.6 (95% CI
= 1.05 – 2.49) times more likely to be interested in information interest on prescribed burning
than camps non-member owned leased property. Camps in the Ozarks were 2.0 (95% CI = 1.11
– 3.40); 2.7 (95% CI = 1.75 – 4.09); and 2.0 (95% CI = 1.38 – 2.87) times more likely to be
interested in information interest on prescribed burning than camps in the Ouachitas, MAV, and
42
GCP, respectively. Landowners and land managers were 1.7 (95% CI = 1.12 – 2.59) and 2.0
(95% CI = 1.29 – 3.19) times, respectively, more likely to be interested in information on
prescribed burning than camp managers. Camps in the Ozarks and GCP were 2.1 (95% CI =
1.22 – 3.70) and 1.8 (95% CI = 1.11 – 2.99) times more likely to be interested in information on
white-tailed deer genetics than camps in the Ouachitas. Camp managers were 1.5 (95% CI =
1.03 – 2.19) times more likely than landowners to rank interest in supplemental feeding
information higher. We found no differences in information interests in aging techniques, food
plots, wildlife plants, Quality Deer Management techniques across property types, deer
management units, or contact category.
Hunt Camp Delivery Method Interests
Across Arkansas, except for AGFC seminars, all forms of delivery method of deer
management information were rated about the same (high) based on median scores (Table 54).
In each DMU, respondents were usually less interested in AGFC seminars (M=3) than other
categories, but there was little difference among other categories (Tables 55 - 58).
Goals and Future Management Options
The current goal of the AGFC deer program is to “maintain a healthy deer herd with a
balanced sex and age structure at a level that is consistent with long-term habitat capability and
to maintain deer populations and parameters at levels that are consistent with public satisfaction
and acceptance.” We asked respondents whether they felt that the AGFC was doing a good job
of managing the white-tailed deer herd to meet this objective. Eighty percent of respondents felt
that the AGFC was doing a good job of managing the statewide deer herd to meet these goals
(Table 59).
Hunt Camp State Management Options Summary
43
Across Arkansas, 35% of hunt camps felt that expanding educational efforts for hunters
and hunt camps on deer management assistance for private lands was the most important
management option for the AGFC, while 30% felt that increased antlerless hunting opportunities
was the most important management option (Table 60). Few hunt camps ranked reduction in
buck season length (15%), buck bag limit (12%), or hunting permit quotas for bucks (7%) as the
most important future management option. Expanding educational efforts on deer management
assistance for private lands had the highest median rank (M=2) across Arkansas (Table 60). In
each DMU, expanding educational efforts for hunters and hunt camps on deer management
assistance for private lands had the highest median rank (M=2) followed by increased deer
research and increased public information on proper deer management techniques (M=3) (Tables
61-64). Respondents typically gave lower ranks for future management option that regulated or
restricted harvest of antlered white-tailed deer (M≥6 in each DMU, Tables 61-64).
Hunt Camp Wildlife Related Recreation and Public Hunting
Forty percent of hunt camps offered wildlife observation and had on average 10
individuals involved, while 34% of respondents had fishing on their camps with an average of 9
individuals involved (Table 65). Most hunt camps (82%) allowed guests of hunt camp members
to harvest antlerless deer on camp properties (Table 66).
Hunt Camp Problems and Concerns Summary
Thirty-two percent of hunt camps felt that illegal hunting (poaching) and trespassing were
the greatest problems on their hunt camp property (Table 67). Hunt camps commonly stated that
unauthorized hunting of deer (30%) and non-members hunting near camp boundaries (30%)
were the greatest problems on their hunt camp. Few hunt camps ranked hunter safety (7%)
among the greatest problems on hunt camp properties. In each DMU, hunt camp problems were
44
illegal hunting (M=3), followed by trespassing (M=2 or 3), and unauthorized hunting (M=3)
(Tables 68-71, respectively). In each DMU, there was little concern of respondents for hunter
safety (M=7), and unauthorized hunting of other wildlife (M=5) (Tables 68-71).
ACKNOWLEDGEMENTS
This research was supported by the Arkansas Game and Fish Commission and the
Arkansas Cooperative Fish and Wildlife Research Unit, under University of Arkansas
Institutional Review Board Protocol # 02174. We thank A. Marston for her administrative
assistance. We thank G. R. Woods and D. C. Guynn for providing example survey instruments.
We thank R. A. James, F. L. Loncarich, M. Cartwright, and D. Urbston for providing valuable
assistance and comments on survey design. We thank N. Myatt for assistance in figure creation.
We thank J. E. Dunn and G. Petris for assistance with statistical analysis and interpretation.
Model selection and interpretation was greatly facilitated by a SAS macro written by W. L.
Thompson. None of this could have been possible without the hunt camps involvement in this
study and assistance from the Arkansas Game and Fish Commission staff.
.
45
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47
Statewide Regulations Buck Bag Limit, Antler Restrictions
Regional (DMU) Regulations Doe Bag Limit, Season Length
Zone (DMZ) Regulations Season Length
Permit/Quota on WMAs, NWRs Private Land Regulations
Mandatory Doe / Restricted Buck Inter Zone Regulations
Figure 1. Hierarchical structure of deer harvest regulation in Arkansas. Regulations at large
scales are typically broad (e.g. bag limits and season lengths) and more restrictive at smaller
scales (e.g. permit hunts on wildlife management areas).
48
Figure 2. Delineation of Arkansas Deer Management Units (DMUs) used in this study.
49
Table 1. Form, notation, and description of candidate models used to estimate log-odds between response categories for hunt camp
contact survey question on white-tailed deer harvest management strategies in excess of state regulations in Arkansas.
Model Form Model Notation Model Description
)QDM(ˆ)DMU(ˆ)Proptype(ˆˆp1
pln 3210i
i β+β+β+β=
−
QDM DMU, Proptype,Π Log-odds differ by property ownership status1,
deer management unit2, and QDM3 strategy
)DMU(ˆ)Proptype(ˆˆp1
pln 210i
i β+β+β=
−
DMU Proptype,Π Log-odds differ by property ownership status and
deer management unit
)QDM(ˆ)Proptype(ˆˆp1
pln 210i
i β+β+β=
−
QDM Proptype,Π Log-odds differ by property ownership status and
QDM strategy
)QDM(ˆ)DMU(ˆˆp1
pln 210i
i β+β+β=
−
QDM Region,Π Log-odds differ by deer management unit and
QDM strategy
)Proptype(ˆˆp1
pln 10i
i β+β=
−
ProptypeΠ Log-odds differ by property ownership status
)DMU(ˆˆp1
pln 10i
i β+β=
−
DMUΠ Log-odds differ by deer management unit
)QDM(ˆˆp1
pln 10i
i β+β=
−
QDM Π Log-odds differ by QDM strategy
1 Property Ownership Categories: Private Owned by Camp Members, Privately Owned Leased Land, and Industry Land. 2 Deer Management Unit Categories: Ozarks, Ouachitas, Mississippi Alluvial Plain (MAV), and Gulf Coastal Plain (GCP). 3 QDM Strategy Categories: Under QDM or Not Under QDM.
50
Table 2. Form, notation, and description of candidate models used to estimate log-odds between response categories for hunt camp
contact question on white-tailed deer habitat management practices used by hunt camps in Arkansas.
Model Form Model Notation Model Description
Acre)(ˆ)QDM(ˆ)DMU(ˆ)Proptype(ˆˆp1
pln 43210
i
i β+β+β+β+β=
−
Acre QDM, DMU, Proptype,Π Log-odds differ by property ownership
status1, deer management unit2, QDM3
strategy and hunt camp size4
Acre)(ˆ)DMU(ˆ)Proptype(ˆˆp1
pln 3210i
i β+β+β+β=
−
Acre DMU, Proptype,Π Log-odds differ by property ownership
status, deer management unit, and hunt
camp size
QDM)(ˆ)DMU(ˆ)Proptype(ˆˆp1
pln 3210
i
i β+β+β+β=
−
QDM DMU, Proptype,Π Log-odds differ by property ownership
status, deer management unit, and
QDM strategy
)Acre(ˆ)DMU(ˆˆp1
pln 210
i
i β+β+β=
−
Acre DMU,Π Log-odds differ by deer management
unit and hunt camp size
)Acre(ˆ)Proptype(ˆˆp1
pln 210
i
i β+β+β=
−
Acre Proptype,Π Log-odds differ by property ownership
status and hunt camp size
DMU)(ˆ)Proptype(ˆˆp1
pln 210
i
i β+β+β=
−
DMU Proptype,Π Log-odds differ by property ownership
status and Deer Management Unit
)DMU(ˆˆp1
pln 10
i
i β+β=
−
DMUΠ Log-odds differ by deer management
unit
51
)Proptype(ˆˆp1
pln 10
i
i β+β=
−
Proptype Π Log-odds differ by property ownership
status
1 Property Ownership Categories: Private Owned by Camp Members, Privately Owned Leased Land, and Industry Land. 2 Deer Management Unit Categories: Ozarks, Ouachitas, Mississippi Alluvial Plain (MAV), and Gulf Coastal Plain (GCP). 3 QDM Strategy Categories: Under QDM or Not Under QDM. 4 Hunt Camp Size Categories: < 1000ac, 1000 – 3000ac, > 3000ac.
52
Table 3. Form, notation, and description of candidate models used to estimate log-odds between response categories for hunt camp
contact survey question on Arkansas Game and Fish Commission management assistance program interest in Arkansas.
Model Form Model Notation Model Description
)Biologist(ˆ)Contact(ˆ
)QDM(ˆ)DMU(ˆ)Proptype(ˆˆp1
pln
54
3210i
i
β+β
+β+β+β+β=
−
Biologist Contact, QDM, DMU, Proptype,Π Log-odds differ by property ownership
status1, deer management unit2, QDM3
strategy, contact type4, and biologist
contact5
)Contact(ˆ)DMU(ˆ)Proptype(ˆˆp1
pln 3210
i
i β+β+β+β=
−
Contact DMU, Proptype,Π Log-odds differ by property ownership
status, deer management unit, and
contact type
)DMU(ˆ)Proptype(ˆˆp1
pln 210
i
i β+β+β=
−
DMU Proptype,Π Log-odds differ by property ownership
status and deer management unit
)Contact(ˆ)Proptype(ˆˆp1
pln 210i
i β+β+β=
−
Contact Proptype,Π Log-odds differ by property ownership
status and contact type
)Contact(ˆ)DMU(ˆˆp1
pln 210
i
i β+β+β=
−
Contact DMU,Π Log-odds differ by deer management
unit and contact type
53
)QDM(ˆ)DMU(ˆˆp1
pln 210
i
i β+β+β=
−
QDM DMU,Π Log-odds differ by deer management
unit and QDM strategy
)QDM(ˆ)Proptype(ˆˆp1
pln 210
i
i β+β+β=
−
QDM Proptype,Π Log-odds differ by property ownership
status and QDM strategy
)Proptype(ˆˆp1
pln 10i
i β+β=
−
ProptypeΠ Log-odds differ by property ownership
status
)DMU(ˆˆp1
pln 10
i
i β+β=
−
DMUΠ Log-odds differ by deer management
unit
)Biologist(ˆˆp1
pln 10i
i β+β=
−
BiologistΠ Log-odds differ by biologist contact
)QDM(ˆˆp1
pln 10i
i β+β=
−
QDMΠ Log-odds differ by QDM strategy
1 Property Ownership Categories: Private Owned by Camp Members, Privately Owned Leased Land, and Industry Land. 2 Deer Management Unit Categories: Ozarks, Ouachitas, Mississippi Alluvial Plain (MAV), and Gulf Coastal Plain (GCP). 3 QDM Strategy Categories: Under QDM or Not Under QDM. 4 Contact Type Categories: Landowner, Land manager, Camp manager. 5 Biologist Contact Categories: Work with Biologist or Do Not Work with Biologist
54
Table 4. County level frequency, total acreage, and mean acreage (SE) of responding hunt
camps in Arkansas.
County No. Responding Camps Total Acres Mean Acreage (SE)
Arkansas 21 28,143 1,340 (242)
Ashley 63 91,477 1,452 (115)
Baxter 6 5,994 999 (146)
Benton 1 1,400 1,400 (---)
Boone 4 7,800 1,950 (523)
Bradley 48 97,960 2,040 (237)
Calhoun 41 70,884 1,728 (200)
Carroll 3 2,673 891 (207)
Chicot 13 35,355 2,719 (541)
Clark 62 88,372 1,425 (145)
Clay 0 0 0
Cleburne 11 13,222 1,202 (288)
Cleveland 44 62,532 1,421 (177)
Columbia 32 42,139 1,316 (161)
Conway 14 13,880 991 (235)
Craighead 0 0 0
Crawford 1 563 563 (---)
Crittenden 2 12,200 6,100 (5,900)
Cross 1 700 700 (---)
Dallas 52 89,746 1,725 (204)
Desha 23 45,786 1,990 (346)
Drew 47 65,884 1,401 (161)
Faulkner 6 6,336 1,056 (232)
Franklin 1 410 410 (---)
Fulton 29 30,325 1,045 (135)
Garland 6 12,635 2,105 (818)
Grant 26 60,142 2,313 (425)
Greene 0 0 0
55
Hempstead 27 29,093 1,077 (154)
Hot Springs 10 21,711 2,171 (386)
Howard 12 61,781 5,148 (2,870)
Independence 15 19,861 1,324 (293)
Izard 35 40,211 1,148 (173)
Jackson 2 6,400 3,200 (2,800)
Jefferson 8 11,869 1,483 (273)
Johnson 5 4,589 917 (231)
Lafayette 15 19,623 1,308 (289)
Lawrence 11 12,163 1105 (256)
Lee 1 10,000 10,000 (---)
Lincoln 26 22,425 862 (154)
Little River 9 13,972 1,552 (490)
Logan 6 4,770 795 (164)
Lonoke 4 2,425 606 (165)
Madison 9 7,456 828 (200)
Marion 6 6,044 1007 (222)
Miller 4 3,617 904 (338)
Mississippi 1 1,200 1,200 (---)
Monroe 7 8,586 1,226 (230)
Montgomery 2 1,000 500 (200)
Nevada 34 51,084 1,502 (199)
Newton 1 1,540 1,540 (---)
Ouachita 44 67,572 1,535 (164)
Perry 4 16,876 4,219 (1,434)
Phillips 5 16,212 3,242 (1,377)
Pike 9 14,182 1,575 (352)
Poinsett 1 1,386 1,386 (---)
Polk 5 16,747 3,349 (1,707)
Pope 4 1,179 294 (24)
Prairie 16 20,375 1,273 (460)
56
Pulaski 2 9,500 4,750 (1,250)
Randolph 15 12,713 847 (161)
St. Francis 3 6,610 2,203 (1,412)
Saline 19 46,705 2,458 (484)
Scott 0 0 0
Searcy 6 7,832 1,305 (304)
Sebastian 0 0 0
Sevier 2 1,848 924 (474)
Sharp 34 28,589 840 (273)
Stone 11 10,080 916 (173)
Union 61 128,814 2,111 (245)
Van Buren 16 27,129 1,695 (541)
Washington 13 11,966 920 (245)
White 28 28,887 1,031 (101)
Woodruff 16 24,211 1,513 (380)
Yell 8 22,396 2,799 (1,901)
Total 1,129 1,769,787
57
Table 5. Number respondents, total acreage, and mean acreage (SE) of responding hunt camps by
Deer Management Unit in Arkansas.
DMU
No. Responding
Camps
Total Camp
Acreage
Mean Camp Acreage
(SE)
Ozarks 226 241,576 1,069 (74)
Ouachitas 72 150,845 2,095 (308)
Mississippi Alluvial Plain 152 254,029 1,671 (151)
Gulf Coastal Plain 666 1,095,016 1,644 (74)
Table 6. Number respondents, total number of members, and mean number of hunt camps
members by Deer Management Unit (DMU) in Arkansas.
DMU No. Responding
Camps
Total No.
Members
Mean No. Members
(SE)
Ozarks 223 2,886 13 (0.88)
Ouachitas 72 1,642 23 (3.15)
Mississippi Alluvial Plain 144 2,222 15 (1.20)
Gulf Coastal Plain 659 11,399 17 (0.40)
58
Table 7. Property ownership status for responding hunt camps by Deer Management Unit
(DMU) and statewide in Arkansas.
Deer Management Unit
Property Type
Ozarks
Ouachitas
Mississippi
Plain
Gulf Coastal
Plain
Statewide
Privately Owned
(Member)
157
(67%)
26
(35%)
99
(63%)
114
(16%)
400
(34%)
Privately Owned
(Leased)
57
(24%)
8
(11%)
34
(22%)
120
(17%)
226
(19%)
Industry Land
(Leased)
13
(5%)
36
(49%)
23
(15%)
448
(66%)
530
(45%)
Public Land 8
(3%)
3
(4%)
0
(0%)
2
(1%)
13
(1%)
Table 8. Property ownership status of responding deer camps under a Quality Deer Management
(QDM) program in Arkansas.
Under QDM
Privately
Owned
(Member)
Privately
Owned
(Leased)
Industry Land
(Leased)
Public Land
Statewide
Yes
161
(40%)
80
(35%)
224
(42%)
0
(0%)
465
(40%)
No 239
(60%)
146
(65%)
306
(58%)
13
(100%)
704
(60%)
59
Table 9. Responding deer camps under a Quality Deer Management (QDM) program by Deer
Management Unit (DMU) in Arkansas.
Under QDM
Ozarks
Ouachitas
Mississippi
Alluvial Plain
Gulf Coastal
Plain
Statewide
Yes
77
(33%)
27
(39%)
79
(51%)
273
(40%)
456
(40%)
No 158
(67%)
45
(61%)
77
(49%)
413
(60%)
639
(60%)
Table 10. Management objectives of responding hunt camps under a Quality Deer Management
(QDM) program in Arkansas.
Maintain
Present
Density
Increase
Deer
Density
Improve Antler
Development/Physical
Condition
Trophy Deer
Management
No
Response
Under
QDM
34
(7%)
33
(7%)
286
(61%)
88
(19%)
24
(5%)
60
Table 11. Management objective of responding hunt camps under a Quality Deer Management
(QDM) program by property ownership status in Arkansas.
Property Type
Maintain
Present
Density
Increase
Deer
Density
Improve Antler
Development/Physical
Condition
Trophy Deer
Management
Total
Under
QDM
Privately Owned
(Member)
8
(5%)
16
(11%)
78
(52%)
48
(32%)
150
(34%)
Privately Owned
(Leased)
9
(12%)
3
(4%)
51
(68%)
12
(16%)
75
(17%)
Industry Land
(Leased)
17
(8%)
14
(6%)
156
(73%)
27
(13%)
214
(49%)
Table 12. Frequency and level of hunter pressure controlled by
responding hunt camps in Arkansas.
Control Pressure
Always
Usually
Sometimes
Never
No
Response
Control
Pressure
627
(53%)
298
(25%)
80
(7%)
151
(13%)
28
(2%)
61
Table 13. Frequency of hunt camps controlling hunter pressure that are
under a Quality Deer Management (QDM) program in Arkansas.
Control Pressure
Always Usually Sometimes Never
Under QDM
290
(63%)
107
(23%)
20
(4%)
44
(10%)
62
Table 14. Response frequencies of harvest management strategies in excess of minimum state regulations in use by hunt camps in Arkansas. Rank levels are
from 1 (practice most used) to 7 (practice least used).
Rank Levels Summary Statistics
Restrictive Management Practices
Most Used
1
2
3
4
5
6
Least Used
7
Mean Rank (SE)
M
Mandatory Doe Harvest
191
(47%)
53
(13%)
46
(11%)
32
(8%)
28
(7%)
14
(4%)
42
(10%)
2.66 (0.10)
2
Doe Harvest before Buck Harvest 49
(18%)
22
(8%)
25
(9%)
27
(10%)
44
(16%)
44
(16%)
65
(23%)
4.40 (0.13) 5
Four-Point Rule or Greater 205
(51%)
34
(8%)
33
(8%)
24
(6%)
22
(5%)
30
(8%)
57
(1%)
2.86 (0.11) 1
Minimum Inside Spread 88
(28%)
31
(10%)
20
(6%)
36
(12%)
37
(12%)
32
(10%)
70
(22%)
3.89 (0.13) 4
Restricted Buck Harvest 156
(43%)
47
(13%)
49
(13%)
32
(9%)
22
(6%)
14
(4%)
46
(12%)
2.84 (0.11) 2
Restricted Antlerless Harvest 317
(60%)
64
(12%)
52
(10%)
35
(7%)
16
(3%)
14
(3%)
28
(5%)
2.09 (0.08) 1
63
Table 15. Response frequencies of harvest management strategies in excess of minimum state regulations in use by hunt camps in the Ozarks DMU. Rank levels
are from 1 (practice most used) to 7 (practice least used).
Rank Levels Summary Statistics
Restrictive Management Practices
Most Used
1
2
3
4
5
6
Least Used
7
Mean Rank (SE)
M
Mandatory Doe Harvest
32
(43%)
10
(13%)
7
(9%)
8
(11%)
4
(5%)
5
(7%)
9
(12%)
2.91 (0.25)
2
Doe Harvest before Buck Harvest 7
(13%)
5
(9%)
4
(7%)
4
(7%)
14
(26%)
8
(15%)
12
(22%)
4.57 (0.28) 5
Four-point Rule or Greater 43
(52%)
8
(10%)
7
(9%)
6
(6%)
4
(5%)
5
(6%)
9
(11%)
2.64 (0.24) 1
Minimum Inside Spread 11
(20%)
5
(9%)
5
(9%)
7
(13%)
9
(17%)
8
(15%)
9
(17%)
4.07 (0.29) 4
Restricted Buck Harvest 32
(44%)
10
(14%)
11
(15%)
9
(12%)
2
(3%)
4
(5%)
5
(7%)
2.60 (0.22) 2
Restricted Antlerless Harvest 65
(61%)
12
(11%)
10
(9%)
10
(9%)
5
(5%)
3
(3%)
2
(2%)
2.02 (0.15) 1
64
Table 16. Response frequencies of harvest management strategies in excess of minimum state regulations in use by hunt camps in the Ouachitas DMU. Rank
levels are from 1 (practice most used) to 7 (practice least used).
Rank Levels Summary Statistics
Restrictive Management Practices
Most Used
1
2
3
4
5
6
Least Used
7
Mean Rank (SE)
M
Mandatory Doe Harvest
10
(42%)
2
(8%)
3
(13%)
3
(13%)
2
(8%)
0
(0%)
4
(17%)
2.04 (0.46)
2
Doe Harvest before Buck Harvest 4
(22%)
0
(0%)
1
(6%)
2
(11%)
4
(22%)
2
(11%)
5
(28%)
4.56 (0.54) 5
Four-point Rule or Greater 6
(26%)
4
(17%)
1
(4%)
2
(9%)
1
(4%)
1
(4%)
8
(35%)
4.00 (0.54) 4
Minimum Inside Spread 3
(14%)
3
(14%)
3
(14%)
1
(5%)
2
(9%)
3
(14%)
7
(32%)
4.50 (0.49) 5
Restricted Buck Harvest 8
(35%)
3
(13%)
3
(13%)
1
(4%)
1
(4%)
1
(4%)
6
(26%)
3.48 (0.53) 3
Restricted Antlerless Harvest 15
(54%)
2
(7%)
0
(0%)
3
(11%)
2
(7%)
2
(7%)
4
(14%)
2.89 (0.45) 1
65
Table 17. Response frequencies of harvest management strategies in excess of minimum state regulations in use by hunt camps in the Mississippi Alluvial Plain
DMU. Rank levels are from 1 (practice most used) to 7 (practice least used).
Rank Levels Summary Statistics
Restrictive Management Practices
Most Used
1
2
3
4
5
6
Least Used
7
Mean Rank (SE)
M
Mandatory Doe Harvest
32
(51%)
6
(10%)
6
(10%)
5
(8%)
6
(10%)
2
(3%)
6
(10%)
2.63 (0.26)
1
Doe Harvest before Buck Harvest 8
(21%)
3
(8%)
5
(13%)
0
(0%)
2
(5%)
11
(29%)
9
(24%)
4.42 (0.39) 6
Four-point Rule or Greater 49
(59%)
8
(10%)
9
(11%)
4
(5%)
4
(5%)
4
(5%)
5
(6%)
2.25 (0.21) 1
Minimum Inside Spread 26
(47%)
6
(11%)
2
(4%)
7
(13%)
5
(9%)
2
(4%)
7
(13%)
2.87 (0.30) 2
Restricted Buck Harvest 29
(44%)
11
(17%)
14
(21%)
3
(5%)
1
(2%)
1
(2%)
7
(11%)
2.50 (0.24) 2
Restricted Antlerless Harvest 42
(58%)
9
(13%)
6
(8%)
10
(14%)
3
(4%)
0
(0%)
2
(3%)
2.04 (0.18) 1
66
Table 18. Response frequencies of harvest management strategies in excess of minimum state regulations in use by hunt camps in the Gulf Coastal Plain DMU.
Rank levels are from 1 (practice most used) to 7 (practice least used).
Rank Levels Summary Statistics
Restrictive Management Practices
Most Used
1
2
3
4
5
6
Least Used
7
Mean Rank (SE)
M
Mandatory Doe Harvest
113
(49%)
31
(13%)
30
(13%)
15
(6%)
15
(6%)
7
(3%)
22
(9%)
2.56 (0.13)
2
Doe Harvest before Buck Harvest 28
(18%)
14
(9%)
15
(10%)
19
(12%)
22
(14%)
23
(15%)
35
(22%)
4.29 (0.17) 5
Four-point Rule or Greater 105
(51%)
13
(6%)
14
(7%)
12
(6%)
12
(6%)
18
(9%)
33
(16%)
2.99 (0.17) 1
Minimum Inside Spread 45
(26%)
17
(10%)
10
(6%)
19
(11%)
21
(12%)
16
(9%)
44
(26%)
4.03 (0.18) 4
Restricted Buck Harvest 84
(44%)
23
(12%)
19
(10%)
19
(10%)
14
(7%)
7
(4%)
27
(14%)
2.92 (0.16) 2
Restricted Antlerless Harvest 185
(61%)
40
(13%)
32
(11%)
12
(4%)
6
(2%)
8
(3%)
19
(6%)
2.05 (0.10) 1
67
Table 19. Response frequencies of habitat management practices in use by hunt camps in Arkansas. Rank levels are from 1 (practice most used) to 9 (practice
least used).
Rank Levels Summary Statistics
Habitat Management Practices
Most Used
1
2
3
4
5
6
7
8
Least Used
9
Mean Rank (SE)
M
Summer Food Plots
284
(42%)
76
(11%)
66
(10%)
83
(12%)
62
(9%)
17
(3%)
18
(3%)
15
(2%)
59
(9%)
3.17 (0.10)
2
Winter Food Plots 673
(70%)
146
(15%)
60
(6%)
30
(3%)
23
(2%)
6
(1%)
6
(1%)
2
(0.5%)
20
(2%)
1.71 (0.05) 1
Fertilization of Vegetation 153
(28%)
39
(7%)
67
(12%)
66
(12%)
73
(13%)
43
(8%)
23
(4%)
11
(2%)
68
(13%)
4.01 (0.12) 4
Supplemental Feeding 605
(60%)
154
(15%)
101
(10%)
54
(5%)
43
(4%)
10
(1%)
16
(2%)
2
(0.5%)
23
(2%)
2.03 (0.05) 1
Supplemental Minerals 504
(50%)
115
(12%)
158
(16%)
108
(11%)
63
(6%)
23
(2%)
9
(1%)
5
(1%)
15
(2%)
2.33 (0.06) 1
Prescribed Burning 36
(11%)
6
(2%)
13
(4%)
8
(2%)
18
(5%)
36
(11%)
53
(16%)
35
(11%)
125
(38%)
6.67 (0.15) 7
Timber Management 142
(30%)
23
(5%)
30
(6%)
31
(7%)
43
(9%)
47
(10%)
49
(11%)
20
(4%)
81
(17%)
4.57 (0.14) 5
Set-Aside Programs 66
(19%)
1
(0.5%)
14
(4%)
14
(4%)
20
(6%)
31
(9%)
24
(7%)
60
(17%)
126
(35%)
6.27 (0.16) 8
68
Table 20. Response frequencies of habitat management practices in use by hunt camps in the Ozarks DMU. Rank levels are from 1 (practice most used) to 9
(practice least used).
Rank Levels Summary Statistics
Habitat Management Practices
Most Used
1
2
3
4
5
6
7
8
Least Used
9
Mean Rank (SE)
M
Summer Food Plots
78
18
(12%)
15
(10%)
15
(10%)
8
(5%)
5
(3%)
2
(1%)
2
(1%)
9
(6%)
2.63 (0.19)
1
Winter Food Plots 132
(70%)
34
(18%)
9
(5%)
5
(3%)
3
(2%)
0
(0%)
2
(1%)
0
(0%)
3
(2%)
1.61 (0.10) 1
Fertilization of Vegetation 38
(31%)
10
(8%)
15
(12%)
14
(11%)
12
(10%)
11
(9%)
8
(7%)
3
(2%)
12
(10%)
3.84 (0.24) 3
Supplemental Feeding 115
(59%)
21
(11%)
22
(11%)
17
(9%)
10
(5%)
5
(3%)
2
(1%)
1
(1%)
3
(2%)
2.14 (0.13) 1
Supplemental Minerals 100
(50%)
19
(10%)
30
(15%)
20
(10%)
17
(9%)
7
(4%)
4
(2%)
1
(1%)
2
(1%)
2.44 (0.13) 1.5
Prescribed Burning 14
(17%)
2
(2%)
6
(7%)
3
(4%)
10
(12%)
10
(12%)
10
(12%)
2
(2%)
26
(31%)
5.75 (0.32) 6
Timber Management 25
(24%)
6
(6%)
3
(3%)
9
(9%)
19
(18%)
4
(4%)
14
(13%)
6
(6%)
18
(17%)
4.89 (0.29) 5
Set-Aside Programs 15
(20%)
0
(0%)
4
(5%)
3
(4%)
1
(1%)
4
(5%)
8
(11%)
15
(20%)
24
(32%)
6.21 (0.36) 8
(51%)
69
Table 21. Response frequencies of habitat management practices in use by hunt camps in the Ouachitas DMU. Rank levels are from 1 (practice most used) to 9
(practice least used).
Rank Levels Summary Statistics
Habitat Management Practices
Most Used
1
2
3
4
5
6
7
8
Least Used
9
Mean Rank (SE)
M
Summer Food Plots
14
(33%)
4
(9%)
4
(9%)
6
(14%)
7
(16%)
1
(2%)
2
(5%)
0
(0%)
5
(12%)
3.67 (0.40)
3
Winter Food Plots 45
(69%)
8
(12%)
5
(8%)
2
(3%)
3
(5%)
1
(2%)
0
(0%)
0
(0%)
1
(2%)
1.75 (0.19) 1
Fertilization of Vegetation 10
(28%)
4
(11%)
3
(8%)
5
(14%)
4
(14%)
2
(6%)
2
(6%)
2
(6%)
3
(8%)
3.92 (0.44) 4
Supplemental Feeding 27
(45%)
15
(25%)
7
(12%)
2
(3%)
4
(7%)
1
(2%)
3
(5%)
0
(0%)
1
(2%)
2.36 (0.24) 2
Supplemental Minerals 25
(38%)
9
(14%)
14
(22%)
9
(14%)
5
(8%)
2
(3%)
0
(0%)
0
(0%)
1
(2%)
2.57 (0.21) 2
Prescribed Burning 3
(13%)
2
(9%)
2
(9%)
1
(4%)
0
(0%)
1
(4%)
2
(9%)
4
(17%)
8
(35%)
6.13 (0.66) 8
Timber Management 4
(13%)
1
(3%)
4
(13%)
4
(13%)
3
(9%)
8
(25%)
4
(13%)
1
(3%)
3
(9%)
5.00 (0.42) 5
Set-Aside Programs 8
(28%)
0
(0%)
2
(7%)
1
(3%)
2
(7%)
5
(17%)
3
(10%)
2
(7%)
6
(21%)
5.14 (0.57) 6
70
Table 22. Response frequencies of habitat management practices in use by hunt camps in the Mississippi Alluvial Plain DMU. Rank levels are from 1 (practice
most used) to 9 (practice least used).
Rank Levels Summary Statistics
Habitat Management Practices
Most Used
1
2
3
4
5
6
7
8
Least Used
9
Mean Rank (SE)
M
Summer Food Plots
46
(46%)
12
(12%)
7
(7%)
11
(11%)
9
(9%)
2
(2%)
3
(3%)
2
(2%)
8
(8%)
3.01 (0.26)
2
Winter Food Plots 110
(77%)
21
(15%)
4
(3%)
4
(3%)
1
(1%)
1
(1%)
0
(0%)
0
(0%)
2
(1%)
1.46 (0.10) 1
Fertilization of Vegetation 18
(27%)
2
(3%)
5
(7%)
7
(10%)
9
(13%)
8
(12%)
3
(4%)
3
(4%)
12
(18%)
4.64 (0.36) 5
Supplemental Feeding 53
(46%)
20
(17%)
17
(15%)
9
(8%)
7
(6%)
1
(1%)
2
(2%)
0
(0%)
7
(6%)
2.57 (0.20) 2
Supplemental Minerals 69
(52%)
9
(7%)
25
(19%)
12
(9%)
11
(8%)
2
(2%)
3
(2%)
0
(0%)
1
(1%)
2.33 (0.15) 1
Prescribed Burning 2
(5%)
1
(2%)
1
(2%)
0
(0%)
2
(5%)
4
(9%)
7
(16%)
8
(18%)
19
(43%)
7.39 (0.33) 8
Timber Management 36
(43%)
7
(8%)
5
(6%)
8
(10%)
5
(6%)
8
(10%)
6
(7%)
3
(4%)
5
(6%)
3.39 (0.29) 2
Set-Aside Programs 18
(30%)
0
(0%)
4
(7%)
6
(10%)
7
(12%)
3
(5%)
3
(5%)
4
(7%)
15
(25%)
4.92 (0.41) 5
71
Table 23. Response frequencies of habitat management practices in use by deer hunt camps in the Gulf Coastal Plain DMU. Rank levels are from 1 (practice most
used) to 9 (practice least used).
Rank Levels Summary Statistics
Habitat Management Practices
Most Used
1
2
3
4
5
6
7
8
Least Used
9
Mean Rank (SE)
M
Summer Food Plots
135
(37%)
39
(11%)
39
(11%)
50
(14%)
35
(10%)
9
(2%)
11
(3%)
11
(3%)
36
(10%)
3.42 (0.14)
3
Winter Food Plots 367
(68%)
78
(14%)
41
(8%)
16
(3%)
16
(3%)
4
(1%)
4
(1%)
2
(1%)
14
(3%)
1.82 (0.07) 1
Fertilization of Vegetation 82
(28%)
21
(7%)
40
(13%)
38
(13%)
43
(14%)
21
(7%)
9
(3%)
3
(1%)
40
(13%)
3.99 (0.16) 4
Supplemental Feeding 398
(66%)
92
(15%)
49
(8%)
24
(4%)
20
(3%)
3
(1%)
7
(1%)
1
(0.5%)
12
(2%)
1.83 (0.07) 1
Supplemental Minerals 297
(52%)
74
(13%)
86
(15%)
60
(10%)
28
(5%)
11
(2%)
2
(0.5%)
4
(1%)
10
(2%)
2.25 (0.07) 1
Prescribed Burning 16
(10%)
1
(1%)
4
(2%)
4
(2%)
6
(4%)
18
(11%)
29
(17%)
20
(12%)
68
(41%)
6.98 (0.19) 8
Timber Management 73
(31%)
8
(3%)
17
(7%)
10
(4%)
15
(6%)
25
(11%)
23
(10%)
9
(4%)
54
(23%)
4.80 (0.21) 5
Set-Aside Programs 22
(12%)
0
(0%)
3
(2%)
4
(2%)
10
(6%)
17
(10%)
9
(5%)
35
(20%)
70
(44%)
7.00 (0.20) 8
72
Table 24. Number of respondents (n) and mean (SE) number of years habitat management practices have been in use on hunt camp
properties in Arkansas.
Deer Management Unit
Management Practice Ozarks Ouachitas Mississippi Alluvial Plain Gulf Coastal Plain Statewide
Summer Food Plots
7.07 (0.46)
(n=134)
5.73 (0.85)
(n=38)
10.1 (1.00)
(n=86)
6.41 (0.28)
(n=323)
7.06 (0.25)
(n=581)
Winter Food Plots 7.54 (0.38)
(n=184)
6.35 (0.59)
(n=63)
11.35 (0.76)
(n=141)
8.49 (0.27)
(n=529)
8.59 (0.22)
(n=917)
Fertilizing Natural Vegetation 9.29 (0.93)
(n=96)
6.10 (0.75)
(n=30)
6.26 (0.78)
(n=47)
6.43 (0.37)
(n=234)
7.06 (0.33)
(n=407)
Supplemental Feeding 6.95 (0.31)
(n=187)
5.58 (0.46)
(n=58)
8.03 (0.51)
(n=108)
8.71 (0.24)
(n=598)
8.10 (0.18)
(n=951)
Supplemental Minerals 8.52 (0.47)
(n=194)
6.92 (0.58)
(n=62)
11.52 (0.84)
(n=121)
9.95 (0.26)
(n=547)
9.65 (0.22)
(n=924)
Prescribed Burning 7.06 (1.26)
(n=45)
7.33 (1.85)
(n=9)
7.63 (2.48)
(n=11)
9.60 (1.05)
(n=40)
8.08 (0.74)
(n=105)
Timber Management 7.38 (0.69)
(n=71)
10.1 (2.35)
(n=20)
15.11 (2.09)
(n=65)
15.11 (1.03)
(n=122)
12.77 (0.73)
(n=278)
Set-Aside Programs 6.93 (0.85)
(n=27)
6.69 (1.16)
(n=13)
8.74 (1.02)
(n=38)
7.29 (0.97)
(n=45)
7.59 (0.53)
(n=123)
73
Table 25. Response frequencies of management for other wildlife performed by hunt camps in Arkansas. Rank levels are from 1 (managed for the most) to 12
(managed for the least).
Rank Levels Summary Statistics Other wildlife
Managed Most
1
2
3
4
5
6
7
8
9
10
11
Managed Least
12
Mean Rank
(SE)
M Waterfowl
87
(30%)
25
(9%)
14
(5%)
11
(4%)
5
(2%)
9
(3%)
10
(3%)
6
(2%)
13
(5%)
8
(3%)
4
(1%)
96
(33%)
6.30 (0.28)
6
Turkey
587 49 (80%) (7%)
17 (2%)
9 (1%)
12 (2%)
15 (2%)
2 (0.5%)
4 (1%)
4 (1%)
4 (1%)
1 (0.5%)
32 (4%)
1.96 (0.10) 1
Quail 91 69 (25%) (19%)
47 (13%)
30 (8%)
19 (5%)
9 (2%)
10 (3%)
10 (3%)
3 (1%)
8 (2%)
0 (0%)
67 (18%)
4.68 (0.21) 3
Bear 15 9 (8%) (5%)
5 (3%)
1 (1%)
5 (3%)
8 (4%)
6 (3%)
10 (5%)
8 (4%)
15 (8%)
9 (5%)
103 (53%)
9.29 (0.27) 12
Elk 6(4%)
1 (1%)
1 (1%)
1 (1%)
1 (1%)
1 (1%)
3 (2%)
2 (1%)
12 (7%)
6 (4%)
17 (10%)
118 (70%)
10.85 (0.19) 12
Squirrel 141 77 (33%) (18%)
48 (11%)
32 (7%)
29 (7%)
14 (3%)
10 (2%)
1 (0.5%)
1 (0.5%)
7 (2%)
0 (0%)
68 (16%)
4.13 (0.19) 2
Dove 45 22 (16%) (8%)
30 (11%)
24 (9%)
26 (9%)
24 (9%)
12 (4%)
7 (3%)
3 (1%)
10 (4%)
0 (0%)
75 (27%)
6.17 (0.25) 5
Rabbit 59 13 (19%) (4%)
32 (10%)
46 (15%)
30 (10%)
20 (6%)
11 (4%)
9 (3%)
5 (2%)
5 (2%)
0 (0%)
80 (26%)
5.93 (0.23) 5
Feral Hogs 42 (19%)
8 (4%)
12 (5%)
6 (3%)
2 (1%)
6 (3%)
7 (3%)
9 (4%)
13 (6%)
12 (5%)
4 (2%)
102 (46%)
8.02 (0.30) 10
Furbearers 19(9%)
4 (2%)
10 (5%)
8 (4%)
17 (8%)
22 (10%)
12 (6%)
11 (5%)
7 (3%)
6 (3%)
2 (1%)
98 (45%)
8.33 (0.27) 9
Non-Game Species 13 (8%)
2 (1%)
9 (6%)
4 (3%)
4 (3%)
4 (3%)
9 (6%)
10 (6%)
9 (6%)
6 (4%)
10 (6%)
75 (48%)
9.02 (0.31) 11
74
Table 26. Response frequencies of management for other wildlife performed by deer camps in the Ozarks DMU. Rank levels are from 1 (managed for the most) to
12 (managed for the least).
Rank Levels Summary Statistics Other wildlife
Managed Most
1
2
3
4
5
6
7
8
9
10
11
Managed Least
12
Mean Rank
(SE)
M Waterfowl
5
(11%)
3
(7%)
4
(9%)
1
(2%)
0
(0%)
2
(4%)
3
(7%)
2
(4%)
6
(13%)
2
(4%)
1
(2%)
17
(37%)
7.93 (0.61)
9
Turkey
161 5 (91%) (3%)
1 (1%)
2 (1%)
1 (1%)
3 (2%)
1 (1%)
1 (1%)
0 (0%)
0 (0%)
1 (1%)
0 (0%)
1.31 (0.09) 1
Quail 30 32 (30%) (32%)
12 (12%)
9 (9%)
3 (3%)
1 (1%)
3 (3%)
2 (2%)
0 (0%)
1 (1%)
0 (0%)
7 (7%)
3.18 (0.30) 2
Bear 7 8 (13%) (15%)
4 (8%)
1 (2%)
2 (4%)
4 (8%)
2 (4%)
3 (6%)
3 (6%)
1 (2%)
1 (2%)
16 (31%)
6.75 (0.61) 6
Elk 3(8%)
1 (3%)
0 (0%)
0 (0%)
1 (3%)
1 (3%)
0 (0%)
1 (3%)
4 (11%)
2 (5%)
4 (11%)
20 (54%)
9.84 (0.57) 12
Squirrel 24 16 (27%) (18%)
13 (15%)
10 (11%)
11 (12%)
3 (3%)
3 (3%)
1 (1%)
0 (0%)
0 (0%)
0 (0%)
8 (9%)
3.74 (0.33) 3
Dove 12 3 (18%) (4%)
8 (12%)
10 (15%)
5 (7%)
12 (18%)
4 (6%)
2 (3%)
1 (1%)
1 (1%)
0 (0%)
9 (13%)
5.22 (0.42) 5
Rabbit 12 3 (18%) (5%)
9 (14%)
9 (14%)
8 (12%)
6 (9%)
2 (3%)
4 (6%)
2 (3%)
0 (0%)
0 (0%)
11 (17%)
5.35 (0.45) 4
Feral Hogs 0 (0%)
0 (0%)
1 (3%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
3 (9%)
3 (9%)
6 (17%)
2 (6%)
20 (57%)
10.74 (0.33) 12
Furbearers 2(4%)
1 (2%)
3 (7%)
2 (4%)
8 (18%)
4 (9%)
2 (4%)
2 (4%)
3 (7%)
1 (2%)
0 (0%)
17 (38%)
7.91 (0.55) 8
Non-Game Species 3 (9%)
0 (0%)
4 (12%)
1 (3%)
1 (3%)
0 (0%)
2 (6%)
4 (12%)
1 (3%)
1 (3%)
5 (15%)
12 (35%)
8.47 (0.67) 10.5
75
Table 27. Response frequencies of management for other wildlife performed by hunt camps in the Ouachitas DMU. Rank levels are from 1 (managed for the most)
to 12 (managed for the least).
Rank Levels Summary Statistics Other wildlife
Managed Most
1
2
3
4
5
6
7
8
9
10
11
Managed Least
12
Mean Rank
(SE)
M Waterfowl
6
(24%)
1
(4%)
0
(0%)
1
(4%)
0
(0%)
2
(8%)
3
(12%)
1
(4%)
2
(8%)
1
(4%)
0
(0%)
8
(32%)
7.08 (0.88)
7
Turkey
45 3 (82%) (5%)
2 (4%)
0 (0%)
1 (2%)
2 (4%)
0 (0%)
0 (0%)
0 (0%)
1 (2%)
0 (0%)
1 (2%)
1.75 (0.29) 1
Quail 8 6 (26%) (19%)
4 (13%)
2 (6%)
3 (10%)
2 (6%)
0 (0%)
1 (3%)
0 (0%)
2 (6%)
0 (0%)
3 (10%)
4.22 (0.65) 3
Bear 1 1 (5%) (5%)
0 (0%)
0 (0%)
3 (14%)
2 (9%)
1 (5%)
2 (9%)
1 (5%)
2 (9%)
1 (5%)
8 (36%)
8.59 (0.75) 9
Elk 1(6%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
2 (12%)
1 (6%)
0 (0%)
1 (6%)
2 (12%)
10 (59%)
10.29 (0.73) 12
Squirrel 6 6 (21%) (21%)
3 (11%)
3 (11%)
1 (4%)
1 (4%)
1 (4%)
0 (0%)
0 (0%)
1 (4%)
0 (0%)
6 (21%)
4.96 (0.80) 3
Dove 5 4 (19%) (15%)
2 (8%)
1 (4%)
2 (8%)
2 (8%)
3 (12%)
1 (4%)
0 (0%)
1 (4%)
0 (0%)
5 (19%)
5.53 (0.79) 5
Rabbit 1 0 (4%) (0%)
3 (13%)
3 (13%)
4 (17%)
4 (17%)
1 (4%)
0 (0%)
0 (0%)
1 (4%)
0 (0%)
6 (26%)
6.74 (0.76) 6
Feral Hogs 1 (6%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
2 (11%)
0 (0%)
2 (11%)
2 (11%)
2 (11%)
9 (50%)
10.17 (0.67) 11
Furbearers 1(4%)
2 (9%)
0 (0%)
3 (13%)
0 (0%)
4 (17%)
4 (17%)
1 (4%)
0 (0%)
0 (0%)
0 (0%)
8 (35%)
7.52 (0.78) 7
Non-Game Species 4 (31%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
3 (23%)
1 (8%)
1 (8%)
0 (0%)
0 (0%)
4 (31%)
6.92 (1.26) 7
76
Table 28. Response frequencies of management for other wildlife performed by hunt camps in the Mississippi Alluvial Plain DMU. Rank levels are from 1
(managed for the most) to 12 (managed for the least).
Rank Levels SummaryStatistics
Other wildlife
Managed Most
1
2
3
4
5
6
7
8
9
10
11
Managed Least
12
Mean Rank
(SE)
M Waterfowl
43
(58%)
9
(12%)
2
(3%)
4
(5%)
1
(1%)
3
(4%)
1
(1%)
0
(0%)
0
(0%)
2
(3%)
0
(0%)
9
(12%)
3.26 (0.44)
1
Turkey
70(69%)
13 (13%)
5 (5%)
3 (3%)
1 (1%)
4 (4%)
0 (0%)
2 (2%)
1 (1%)
0 (0%)
0 (0%)
3 (3%)
2.09 (0.24) 1
Quail 12(20%)
13 (21%)
9 (15%)
3 (5%)
5 (8%)
1 (2%)
3 (5%)
2 (3%)
0 (0%)
24 (7%)
0 (0%)
9 (15%)
4.80 (0.50) 3
Bear 4(14%)
0 (0%)
1 (4%)
0 (0%)
0 (0%)
0 (0%)
1 (4%)
1 (4%)
0 (0%)
1 (4%)
3 (11%)
17 (61%)
9.61 (0.77) 12
Elk 0(0%)
0 (0%)
1 (4%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
1 (4%)
21 (92%)
11.57 (0.39) 12
Squirrel 20(29%)
2 (15%)
9 (13%)
8 (12%)
6 (9%)
2 (3%)
2 (3%)
0 (0%)
0 (0%)
2 (3%)
0 (0%)
9 (13%)
4.16 (0.45) 3
Dove 13(22%)
7 (12%)
10 (17%)
6 (10%)
5 (9%)
3 (5%)
2 (3%)
1 (2%)
0 (0%)
3 (5%)
0 (0%)
8 (14%)
4.68 (0.49) 3
Rabbit 12(23%)
2 (4%)
6 (12%)
9 (17%)
6 (12%)
4 (8%)
1 (2%)
0 (0%)
0 (0%)
3 (6%)
0 (0%)
9 (17%)
5.17 (0.54) 4
Feral Hogs 3 (10%)
2 (7%)
3 (10%)
0 (0%)
0 (0%)
1 (3%)
0 (0%)
1 (3%)
1 (3%)
1 (3%)
0 (0%)
18 (60%)
8.83 (0.80) 12
Furbearers 4(13%)
0 (0%)
2 (6%)
1 (3%)
2 (6%)
3 (9%)
1 (3%)
0 (0%)
1 (3%)
4 (13%)
0 (0%)
14 (44%)
8.31 (0.73) 10
Non-Game 2(8%)
1 (4%)
1 (4%)
2 (8%)
1 (4%)
0 (0%)
0 (0%)
1 (4%)
2 (8%)
1 (4%)
0 (0%)
13 (54%)
8.83 (0.85) 12
77
Table 29. Response frequencies of management for other wildlife performed by hunt camps in the Gulf Coastal Plain DMU. Rank levels are from 1 (managed for
the most) to 12 (managed for the least).
Rank Levels Summary Statistics Other wildlife
Managed Most
1
2
4
5
6
7
8
9
10
11
Managed Least
12
Mean Rank
(SE)
M Waterfowl
28
(21%)
12
(10%)
7
(5%)
5
(4%)
3
(2%)
2
(1%)
3
(2%)
3
(2%)
5
(4%)
3
(2%)
3
(2%)
60
(45%)
7.41 (041)
9
Turkey
295 (77%)
27 (7%)
8 (2%)
4 (1%)
8 (2%)
6 (2%)
1 (0.5%)
1 (0.5%)
3 (1%)
3 (1%)
0 (0%)
25 (7%)
2.19 (0.15) 1
Quail 35(22%)
15 (10%)
22 (14%)
16 (10%)
8 (5%)
3 (2%)
4 (3%)
5 (3%)
3 (2%)
1 (1%)
0 (0%)
45 (29%)
5.71 (0.35) 4
Bear 3(3%)
0 (0%)
0 (0%)
0 (0%)
0 (0%)
1 (1%)
1 (1%)
4 (5%)
4 (5%)
10 (12%)
4 (5%)
59 (69%)
10.88 (0.25) 12
Elk 2(2%)
0 (0%)
0 (0%)
1 (1%)
0 (0%)
0 (0%)
1 (1%)
0 (0%)
8 (9%)
3 (3%)
9 (10%)
64 (73%)
11.16 (0.22) 12
Squirrel 84(37%)
43 (19%)
22 (10%)
10 (4%)
10 (4%)
8 (4%)
4 (2%)
0 (0%)
1 (0.5%)
4 (2%)
0 (0%)
42 (18%)
4.19 (0.27) 2
Dove 14(12%)
5 (4%)
9 (8%)
5 (4%)
14 (12%)
7 (6%)
3 (3%)
3 (3%)
2 (2%)
4 (3%)
0 (0%)
51 (44%)
7.67 (0.40) 8
Rabbit 29(19%)
8 (5%)
11 (7%)
22 (14%)
11 (7%)
6 (4%)
7 (5%)
5 (3%)
3 (2%)
1 (1%)
0 (0%)
51 (33%)
6.46 (0.35) 5
Feral Hogs 36 (27%)
6 (4%)
8 (6%)
6 (5%)
2 (1%)
4 (3%)
5 (4%)
4 (3%)
7 (5%)
3 (2%)
0 (0%)
53 (40%)
6.91 (0.41) 7
Furbearers 11(10%)
1 (1%)
5 (5%)
2 (2%)
7 (6%)
11 (10%)
4 (4%)
8 (7%)
3 (3%)
1 (1%)
2 (0%)
55 (50%)
8.62 (0.38) 11
Non-Game 4(5%)
1 (1%)
3 (4%)
1 (1%)
2 (3%)
4 (5%)
4 (5%)
4 (5%)
4 (5%)
4 (5%)
5 (6%)
43 (54%)
9.62 (0.38) 12
3
78
Table 30. Response frequencies of management practices for other wildlife in use by hunt camps in Arkansas. Rank levels are from 1
(technique most used) to 6 (technique least used).
Rank Levels Summary Statistics
Management Technique
Most Used
1
2
3
4
5
Least Used
6
Mean Rank (SE)
M
Flooding fields for waterfowl
66
(30%)
6
(3%)
9
(4%)
8
(4%)
16
(7%)
117
(53%)
4.14 (0.15)
6
Nest platforms or boxes for waterfowl 36
(16%)
24
(11%)
16
(7%)
23
(10%)
11
(5%
113
(51%)
4.29 (0.13) 6
Feeders or nest boxes for songbirds 61
(24%)
22
(9%)
37
(15%)
16
(6%)
15
(6%)
103
(41%)
3.83 (0.13) 4
Mowing or grassland management 350
(66%)
82
(15%)
42
(8%)
16
(3%)
1
(0.5%)
43
(8%)
1.81 (0.06) 1
Timber Management 208
(51%)
77
(19%)
37
(9%)
11
(3%)
5
(1%)
67
(17%)
2.33 (0.09) 1
79
Table 31. Response frequencies of management practices for other wildlife in use by deer camps in the Ozarks DMU. Rank levels are
from 1 (technique most used) to 6 (technique least used).
Rank Levels Summary Statistics
Management Technique
Most Used
1
2
3
4
5
Least Used
6
Mean Rank (SE)
M
Flooding fields for waterfowl
3
(9%)
0
(0%)
2
(6%)
1
(3%)
3
(9%)
26
(74%)
5.26 (0.26)
6
Nest platforms or boxes for waterfowl 2
(5%)
7
(16%)
5
(11%)
7
(16%)
3
(7%)
20
(45%)
4.41 (0.26) 5
Feeders or nest boxes for songbirds 20
(33%)
7
(12%)
11
(18%)
4
(7%)
2
(3%)
16
(27%)
3.15 (0.26) 3
Mowing or grassland management 104
(76%)
18
(13%)
6
(4%)
2
(1%)
0
(0%)
6
(4%)
1.48 (0.10) 1
Timber Management 37
(42%)
28
(31%)
10
(11%)
2
(2%)
1
(1%)
11
(12%)
2.27 (0.17) 2
80
Table 32. Response frequencies of management practices for other wildlife in use by deer camps in the Ouachitas DMU. Rank levels
are from 1 (technique most used) to 6 (technique least used).
Rank Levels Summary Statistics
Management Technique
Most Used
1
2
3
4
5
Least Used
6
Mean Rank (SE)
M
Flooding fields for waterfowl
5
(26%)
2
(11%)
0
(0%)
0
(0%)
3
(16%)
9
(47%)
4.11 (0.52)
5
Nest platforms or boxes for waterfowl 5
(25%)
2
(10%)
0
(0%)
3
(15%)
1
(5%)
9
(45%)
4.00 (0.49) 4
Feeders or nest boxes for songbirds 6
(27%)
0
(0%)
5
(23%)
2
(9%)
1
(5%)
8
(36%)
3.73 (0.44) 3
Mowing or grassland management 22
(63%)
4
(11%)
3
(9%)
1
(3%)
0
(0%)
5
(14%)
2.09 (0.30) 1
Timber Management 19
(56%)
7
(21%)
4
(12%)
0
(0%)
0
(0%)
4
(12%)
2.03 (0.28) 1
81
Table 33. Response frequencies of management practices for other wildlife in use by deer camps in the Mississippi Alluvial Plain
DMU. Rank levels are from 1 (technique most used) to 6 (technique least used).
Rank Levels Summary Statistics
Management Technique
Most Used
1
2
3
4
5
Least Used
6
Mean Rank (SE)
M
Flooding fields for waterfowl
38
(63%)
3
(5%)
1
(2%)
6
(10%)
0
(0%)
12
(20%)
2.38 (0.26)
1
Nest platforms or boxes for waterfowl 16
(34%)
7
(15%)
6
(13%)
0
(0%)
4
(9%)
14
(30%)
3.23 (0.31) 3
Feeders or nest boxes for songbirds 3
(8%)
4
(10%)
5
(13%)
4
(10%)
7
(18%)
17
(42%)
4.48 (0.27 5
Mowing or grassland management 45
(52%)
26
(30%)
10
(11%)
4
(5%)
0
(0%)
2
(2%)
1.78 (0.11) 1
Timber Management 49
(58%)
13
(15%)
11
(13%)
4
(5%)
1
(1%)
6
(7%)
1.96 (0.16) 1
82
Table 34. Response frequencies of management practices for other wildlife in use by deer camps in the Gulf Coastal Plain DMU. Rank
levels are from 1 (technique most used) to 6 (technique least used).
Rank Levels Summary Statistics
Management Technique
Most Used
1
2
3
4
5
Least Used
6
Mean Rank (SE)
M
Flooding fields for waterfowl
13
(13%)
1
(1%)
6
(6%)
1
(1%)
10
(10%)
68
(69%)
5.00 (0.18)
6
Nest platforms or boxes for waterfowl 11
(11%)
6
(6%)
5
(5%)
13
(13%)
3
(3%)
65
(63%)
4.81 (0.18) 6
Feeders or nest boxes for songbirds 26
(22%)
10
(9%)
16
(13%)
6
(5%)
3
(3%)
58
(49%)
4.04 (0.19) 5
Mowing or grassland management 165
(64%)
34
(13%)
21
(8%)
8
(3%)
1
(0.5%)
28
(11%)
1.94 (0.10) 1
Timber Management 98
(53%)
28
(15%)
9
(5%)
4
(2%)
3
(2%)
43
(23%)
2.54 (0.15) 1
83
84
Table 35. Opinions (number respondents (n) and %) of responding hunt camps on changes in
white-tailed deer population and harvest structure since camp began using harvest and habitat
management practices for white-tailed deer in Arkansas.
Opinions on Deer Herd Yes No
Increase in Total Number of Deer on Camp Property
500 (42%)
684 (58%)
Increase in Number >2.5 years olds Harvested 673 (57%) 511 (43%)
Increase in number >4.5 years old Harvested 268 (23%) 916 (77%)
Increase in Antler Size, Spread, Total Points of Harvested Deer 538 (45%) 646 (55%)
Improvements in Health/Weight of Harvested Deer 559 (47%) 625 (53%)
More Equal Ratio of Bucks to Does 420 (35%) 764 (65%)
Table 36. Responding hunt camps that currently collect biological information on white-tailed
deer harvested by hunt camp members in Arkansas.
Biological information Response Frequency
Yes
327 (28%)
No 857 (72%)
85
DMU
Table 37. Responding hunt camps that currently collect biological information on white-tailed deer
harvested by club members across deer management units (DMUs) in Arkansas.
Biological Records
190 (60%)
Ozarks Ouachitas Mississippi Alluvial Plain Gulf Coastal Plain
Yes
48 (15%)
23 (7%)
54 (17%)
No 187 (22%) 51 (6%) 102 (12%) 496 (59%)
Table 38. Responding hunt camps that currently collect biological information on white-tailed
deer harvested by club members across property types in Arkansas.
Property Type
Biological Records Privately Owned Private Leased Industry Land Public Land
Yes
87 (27%)
41 (13%)
194 (60%)
1 (0.5%)
No 313 (37%) 185 (22%) 336 (40%) 12 (1%)
86
Table 39. Responding hunt camps that currently work with an Arkansas Game and Fish
Commission (AGFC) biologist in establishing harvest and habitat management guidelines for
white-tailed deer in Arkansas.
Work Biologist Response Frequency
Yes
223 (19%)
No 961 (81%)
Table 40. Responding hunt camps that currently work with an Arkansas Game and Fish
Commission (AGFC) biologist in establishing harvest and habitat guidelines for white-tailed
deer across property types in Arkansas.
Property Type
Work Biologist Privately Owned Private Leased Industry Land Public Land
Yes
84 (38%)
46 (19%)
89 (40%)
1 (0.5%)
No 316 (33%) 180 (19%) 441 (46%) 12 (1%)
87
Table 41. Responding hunt camps that currently work with an Arkansas Game and Fish
Commission (AGFC) biologist in establishing harvest and habitat guidelines for white-tailed deer
across deer management units (DMUs) in Arkansas.
DMU
Work Biologist Ozarks Ouachitas Mississippi Alluvial Plain Gulf Coastal Plain
Yes
51 (24%)
10 (5%)
40 (18%)
116 (53%)
No 184 (20%) 64 (7%) 116 (12%) 570 (61%)
Table 42. Number of responding hunt camps currently working with an Arkansas Game and
Fish Commission (AGFC) biologist that collect biological information off white-tailed deer
harvested by hunt camp members in Arkansas.
Biological records
Work Biologist Yes No
Yes
133 (60%)
90 (40%)
No 194 (20%) 767 (80%)
88
Table 43. Number of respondents that have sought advice on white-tailed deer harvest or habitat
management from Arkansas Game and Fish Commission (AGFC) biologists or outside biologists
in Arkansas.
Sought Assistance Response Frequency
Yes
354 (30%)
No 830 (70%)
Table 44. Response frequencies of responding hunt camps on type of AGFC provided management assistance programs that would
most benefit/interest their hunt camps across Arkansas. Rank levels from 1 (most beneficial) to 7 (least beneficial).
Rank Levels Summary Statistics
Management Assistance Type
Most
Benefit
1
2
3
4
5
6
Least
Benefit
7
Mean Rank (SE)
M
Public Information Programs
155
(29%)
28
(5%)
29
(5%)
32
(6%)
87
(16%)
106
(20%)
95
(18%)
4.06 (0.10)
5
Hunter Education Programs 103
(22%)
26
(6%)
40
(8%)
26
(6%)
100
(21%)
110
(23%)
68
(14%)
4.26 (0.10) 5
Wildlife Management Assistance Programs 341
(49%)
99
(14%)
91
(13%)
103
(15%)
24
(3%)
9
(1%)
28
(4%)
2.29 (0.06) 2
Wildlife Biologist Recommendations 430
(56%)
132
(17%)
92
(12%)
46
(6%)
25
(3%)
10
(1%)
30
(4%)
2.02 (0.06) 1
Population Estimation 329
(47%)
109
(15%)
94
(13%)
82
(12%)
35
(5%)
21
(3%)
36
(5%)
2.42 (0.07) 2
Habitat Development Assistance Programs 294
(43%)
93
(14%)
112
(16%)
88
(13%)
34
(5%)
18
(3%)
41
(6%)
2.55 (0.07) 2
Non-game Management Assistance 28
(7%)
6
(1%)
7
(2%)
20
(5%)
56
(14%)
27
(7%)
266
(65%)
5.96 (0.09) 7
89
Table 45. Response frequencies of responding hunt camps on type of AGFC provided management assistance programs that would
most benefit/interest their hunt camps in the Ozarks DMU. Rank levels from 1 (most beneficial) to 7 (least beneficial).
Rank Levels Summary Statistics
2 3
Benefit
7
36 6
Management Assistance Type
Most
Benefit
1
4
5
6
Least
Mean Rank (SE)
M
Public Information Programs
(32%)
3
(3%)
(5%)
3
(3%)
21
(19%)
18
(16%)
25
(22%)
4.11 (0.23)
5
Hunter Education Programs 17
(18%)
3
(3%)
3
(3%)
6
(22%)
5
71 2 1
16
(6%)
21 30
(32%)
15
(16%)
4.69 (0.21)
Wildlife Management Assistance Programs
(50%)
26
(18%)
17
(12%)
23
(16%) (1%) (1%)
2
(1%)
2.08 (0.11) 1.5
Wildlife Biologist Recommendations 86
(56%)
30
(20%)
21
(14%)
10
(7%)
2
(1%)
0
(0%)
4
(3%)
1.88 (0.11) 1
Population Estimation 48
(37%) (12%)
24
(18%)
26
(20%)
8
(6%)
4
(3%)
4
(3%)
2.68 (0.14) 3
Habitat Development Assistance Programs 69
(49%)
19
(14%)
21
(15%)
21
(15%)
5
(4%)
2
(1%)
3
(2%)
2.23 (0.13) 2
Non-game Management Assistance 6
(7%)
0
(0%)
1
(1%)
2
(2%)
17
(20%)
6
(7%)
51
(61%)
5.96 (0.19) 7
90
Table 46. Response frequencies of responding hunt camps on type of AGFC provided management assistance programs that would
most benefit their hunt camps in the Ouachitas DMU. Rank levels from 1 (most beneficial) to 7 (least beneficial).
Rank Levels Summary Statistics
Management Assistance Type
Most
Benefit
1
2
3
4
5
6
Least
Benefit
7
Mean Rank (SE)
M
Public Information Programs
9
(30%)
2
(7%)
2
(7%)
3
(10%)
4
(13%)
6
(20%)
4
(13%)
3.83 (0.42)
4
Hunter Education Programs 13
(41%)
2
(6%)
2
(6%)
3
(9%)
3
(9%)
4
(13%)
5
(16%)
3.41 (0.43) 3
Wildlife Management Assistance Programs 18
(49%)
6
(16%)
4
(11%)
2
(5%)
3
(8%)
1
(3%)
3
(8%)
2.49 (0.32) 2
Wildlife Biologist Recommendations 25
(52%)
8
(17%)
8
(17%)
2
(4%)
1
(2%)
1
(2%)
3
(6%)
2.19 (0.25) 1
Population Estimation 19
(48%)
3
(8%)
8
(20%)
2
(5%)
5
(13%)
1
(3%)
2
(5%)
2.55 (0.29) 2
Habitat Development Assistance Programs 17
(43%)
7
(18%)
(76%)
2
(5%)
5
(13%)
2
(5%)
4
(10%)
3
(7%)
2.80 (0.33) 2
Non-game Management Assistance 2
(8%)
1
(4%)
2
(8%)
0
(0%)
1
(4%)
0
(0%)
19 5.92 (0.42) 7
91
Table 47. Response frequencies of responding hunt camps on type of AGFC provided management assistance programs that would
most benefit/interest their hunt camps in the Mississippi Alluvial Plain DMU. Rank levels from 1 (most beneficial) to 7 (least
beneficial).
Rank Levels Summary Statistics
Management Assistance Type
Most
Benefit
1
2
3
4
5
6
Least
Benefit
7
Mean Rank (SE)
(11%)
M
Public Information Programs
22
(31%)
1
(1%)
4
(6%)
8
8
(11%)
16
(23%)
11
(16%)
4.01 (0.28)
4.5
Hunter Education Programs 13
(23%)
3
(5%)
9
(16%)
1
(2%)
17
(30%)
4
(7%)
9
(16%)
3.96 (0.29) 5
Wildlife Management Assistance Programs 39
(42%)
13
(14%)
18 5
(21%)
12
(13%) (20%)
4
(4%)
1
(1%) (5%)
2.54 (0.18) 2
Wildlife Biologist Recommendations 53
(52%)
21 11
(11%)
4
(4%)
8
(8%)
2
(2%)
3
(3%)
2.13 (0.16) 1
Population Estimation 36
(40%)
16
(18%)
11
(12%)
10
(11%)
6
(7%)
6
(7%)
4
(4%)
2.64 (0.20) 2
Habitat Development Assistance Programs 39
(43%)
11
(12%)
18
(20%)
9
(10%)
3
(3%)
4
(4%)
7
(8%)
2.63 (0.20) 2
Non-game Management Assistance 4
(8%)
2
(4%)
0
(0%)
1
(2%)
5
(10%)
3
(6%)
36
(71%)
6.02 (2.63) 7
92
Table 48. Response frequencies of responding hunt camps on type of AGFC provided management assistance programs that would
most benefit/interest their hunt camps in the Gulf Coastal Plain DMU. Rank levels from 1 (most beneficial) to 7 (least beneficial).
Rank Levels Summary Statistics
Management Assistance Type
Most
Benefit
1
2
3
4
5
6
Least
Benefit
7
Mean Rank (SE)
M
Public Information Programs
84
(28%)
21
(7%)
15
(5%)
17
(6%)
53
(17%)
64
(21%)
51
(17%)
4.08 (0.13)
5
Hunter Education Programs 58
(21%)
17
(6%)
24
(9%)
16
(6%)
57
(21%)
70
(25%)
36
(13%)
4.26 (0.13) 5
Wildlife Management Assistance Programs 202
(50%)
53
(13%)
56
(14%)
57
(14%)
13
(3%)
5
(1%)
17
(4%)
2.28 (0.08) 1
Wildlife Biologist Recommendations 253
(58%)
67
(15%)
49
(11%)
29
(7%)
14
(3%)
7
(2%)
19
(4%)
2.04 (0.08) 1
Population Estimation 217
(51%)
71
(17%)
45
(11%)
43
(10%)
14
(3%)
10
(2%)
25
(6%)
2.28 (0.09) 1
Habitat Development Assistance Programs 162
(42%)
54
(14%)
66
(17%)
51
(13%)
23
(6%)
7
(2%)
27
(7%)
2.61 (0.09) 2
Non-game Management Assistance 15
(6%)
3
(1%)
3
(1%)
13
(5%)
32
(13%)
18
(8%)
156
(65%)
6.01 (0.11) 7
93
Table 49. Response frequencies of responding hunt camps on types of Arkansas Game and Fish Commission (AGFC) provided information that would most assist respondents in managing white-tailed deer across Arkansas. Rank levels from 1 (not interested) to 5 (extremely interested). Rank Levels Summary Statistics Information Type
Not Interested
1
2
3
4
Extremely Interested
5
Mean Rank (SE)
M Hunting Techniques
325
(34%)
143
(15%)
231
(25%)
140
(15%)
104
(11%) 2.53 (0.04)
3
Aging Techniques 111 (11%)
96
102 (11%)
259 (27%)
289 (30%)
335
206 (21%)
3.39 (0.04) 4
Harvest Management (10%)
68 (7%)
206 (21%)
209 (34%)
274
276 (28%)
3.64 (0.04) 4
Deer Behavior 144 (15%)
79 (8%) (22%) (28%)
264 (27%)
3.45 (0.04) 4
Food Plots 79 (7%)
37 (3%)
157 (15%)
315 (30%)
477 (45%)
4.01 (0.04) 4
Forest Management 267 (30%)
118 (13%)
107
154 (17%)
174 (19%)
180 (20%)
2.87 (0.05) 3
Prescribed Burning 408 (46%) (12%)
137 (15%)
113 (13%)
122 (14%)
2.36 (0.05) 2
Deer Genetics 123 (13%)
92 (10%)
210 (22%)
256 (27%)
268 (28%)
3.48 (0.04) 4
Wildlife Plants 95 (10%)
70 (7%)
194 (20%)
296 (30%)
324 (33%)
3.70 (0.04) 4
Quality Deer Management Techniques 134 (15%)
85 (10%)
190 (21%)
237 (27%)
240 (27%)
3.41 (0.05) 4
Supplemental Feeding 86 (8%)
39 (4%)
174 (17%)
349 (33%)
406 (39%)
3.90 (0.04) 4
94
Table 50. Response frequencies of responding hunt camps on types of Arkansas Game and Fish Commission (AGFC) provided information that would most assist respondents in managing white-tailed deer in the Ozarks DMU. Rank levels from 1 (not interested) to 5 (extremely interested). Rank Levels Summary Statistics Information Type
Not Interested
1
2
3
4
Extremely Interested
5
Mean Rank (SE)
M Hunting Techniques
58
(32%)
27
(15%)
49
(27%)
21
(11%)
28
(15%)
3.64 (0.11)
3
Aging Techniques 19 (10%)
20 (11%)
54 (29%)
51 (27%)
44 (23%)
3.43 (0.09) 4
Harvest Management 14 (7%)
13 (7%)
37 (20%)
62 (33%)
63 (33%)
3.78 (0.09) 4
Deer Behavior 30 (16%)
15 (8%)
39 (21%)
50 (27%)
50 (27%)
3.41 (0.10) 4
Food Plots 16 (8%)
7 (3%)
26 (13%)
49 (24%)
106 (52%)
4.09 (0.09) 5
Forest Management 26 (14%)
17 (9%)
39 (21%)
41 (22%)
60 (33%)
3.50 (0.10) 4
Prescribed Burning 49 (26%)
16 (9%)
14
36 (19%)
34 (18%)
51 (27%)
3.12 (0.11) 3
Deer Genetics 18 (10%) (8%)
41 (22%)
48 (26%)
63 (34%)
3.67 (0.09) 4
Wildlife Plants 17 (9%)
12 (6%)
33 (17%)
53 (28%)
75 (39%)
3.83 (0.09) 4
Quality Deer Management Techniques 20 (11%)
16 (9%)
41 (23%)
40 (22%)
61 (34%)
3.60 (0.10) 4
Supplemental Feeding 18 (9%)
12 (6%)
32 (16%)
62 (30%)
81 (40%)
3.86 (0.09) 4
95
Table 51. Response frequencies of responding hunt camps on types of Arkansas Game and Fish Commission (AGFC) provided information that would most assist respondents in managing white-tailed deer in the Ouachitas DMU. Rank levels from 1 (not interested) to 5 (extremely interested).
Information Type
Not Interested
1
2
3
4
Extremely Interested
5
Mean Rank (SE)
M Hunting Techniques
19
(32%)
18
(31%)
3
(5%)
13
(22%) 6
(10%)
2
Aging Techniques 5 (8%)
11 (17%)
14 (22%)
23 (37%)
10 4 (16%)
3.35 (0.15)
Harvest Management 6 (10%)
11 (17%)
14 (22%)
23 (37%)
9 (14%)
3.29 (0.15) 4
Deer Behavior 6 (9%)
6 (9%)
11 (17%)
21 (33%)
20 (31%)
3.67 (0.16) 4
Food Plots 2 (3%)
1 (2%)
12 (18%)
25 (38%)
26 (39%)
4.10 (0.12) 4
Forest Management 13 (22%)
7 (12%)
15 (26%)
16 (28%)
7 (12%)
2.95 (0.18) 3
Prescribed Burning 28 (45%)
8 (13%)
11 (18%)
8 (13%)
7 (11%)
2.32 (0.18) 2
Deer Genetics 10 (16%)
12 (20%)
14 (23%)
13 (21%)
12 (20%)
3.08 (0.18) 3
Wildlife Plants 10 (16%)
3 (5%)
11 (18%)
25 (41%)
12 (20%)
3.43 (0.17) 4
Quality Deer Management Techniques 15 (26%)
7 (12%)
11 (20%)
15 (26%)
10 (17%)
2.97 (0.19) 3
Supplemental Feeding 4 (6%)
6 (9%)
12 (17%)
22 (31%)
26 (37%)
3.86 (0.14) 4
Rank Levels Summary Statistics
2.47 (0.18)
96
Table 52. Response frequencies of responding hunt camps on types of Arkansas Game and Fish Commission (AGFC) provided information that would most assist respondents in managing white-tailed deer in the Mississippi Alluvial Plain DMU. Rank levels from 1 (not interested) to 5 (extremely interested). Rank Levels Summary Statistics Information Type
Not Interested
1
2
3
4
Extremely Interested
5
Mean Rank (SE)
M Hunting Techniques
52
(40%)
21
(16%)
35
(27%)
16
(12%)
5
(4%)
2.23 (0.11)
2
Aging Techniques 17 (13%)
11 (8%)
37 (28%)
39 (29%)
30 (22%)
3.40 (0.11) 4
Harvest Management 17 (13%)
4 (3%)
30 (22%)
37 (28%)
46 (34%)
3.68 (0.11) 4
Deer Behavior 22 (16%)
11 (8%)
36 (26%)
40 (29%)
28 (20%)
3.30 (0.11) 3
Food Plots 16 (11%)
5 (4%)
17 (12%)
46 (32%)
58 (41%)
3.88 (0.11) 4
Forest Management 36 (28%)
14 (11%)
22 (17%)
26 (20%)
29 (23%)
2.98 (0.14) 3
Prescribed Burning 64 (51%)
14 (11%)
15 (12%)
16 (13%)
16 (13%)
2.25 (0.13) 1
Deer Genetics 22 (17%)
12 (9%)
20 (15%)
41 (32%)
35 (27%)
3.42 (0.12) 4
Wildlife Plants 15 (11%)
10 (7%)
30 (22%)
36 (27%)
44 (33%)
3.62 (0.11) 4
Quality Deer Management Techniques 22 (18%)
8 (7%)
21 (17%)
32 (26%)
38 (31%)
3.46 (0.13) 4
Supplemental Feeding 19 (13%)
3 (2%)
25 (18%)
40 (28%)
55 (39%)
3.77 (0.11) 4
97
Table 53. Response frequencies of responding hunt camps on types of Arkansas Game and Fish Commission (AGFC) provided information that would most assist respondents in managing white-tailed deer in the Gulf Coastal Plain DMU. Rank levels from 1 (not interested) to 5 (extremely interested). Rank Levels Summary Statistics Information Type
Not Interested
1
2
3
4
Extremely Interested
5
Mean Rank (SE)
M Hunting Techniques
185
(34%)
77
(14%)
136
(25%)
86
(16%)
62
(11%)
2.57 (0.06)
3
Aging Techniques 68 (12%)
59 (11%)
145 (26%)
169 (30%)
114 (21%)
3.36 (0.05) 4
Harvest Management 56 (10%)
39 (7%)
119 (21%)
203 (36%)
151 (27%)
3.62 (0.05) 4
Deer Behavior 83 (15%)
45 (8%)
117 (21%)
155 (28%)
160 (29%)
3.47 (0.06) 4
Food Plots 43 (7%)
22 (4%)
97 (16%)
186 (30%)
275 (44%)
4.01 (0.05) 4
Forest Management 187 (37%)
76 (15%)
74 (15%)
86 (17%)
77 (15%)
2.58 (0.07) 2
Prescribed Burning 257 (52%)
67 (14%)
71 (14%)
52 (11%)
44 (10%)
2.10 (0.06) 1
Deer Genetics 68 (12%)
52 (10%)
128 (23%)
148 (27%)
149 (27%)
3.47 (0.06) 4
Wildlife Plants 50 (9%)
41 (7%)
115 (20%)
173 (31%)
186 (33%)
3.72 (0.05) 4
Quality Deer Management Techniques 75 (15%)
50 (10%)
110 (22%)
144 (28%)
128 (25%)
3.39 (0.06) 4
Supplemental Feeding 44 (7%)
16 (3%)
95 (16%)
219 (36%)
234 (38%)
3.96 (0.05) 4
98
99
Table 54. Response frequencies on value of delivery method of white-tailed deer management information to responding hunt camps
across Arkansas. Rank levels from 1 (not valuable) to 5 (extremely valuable).
Rank Levels Summary Statistics
Delivery Method
Not
Valuable
1
2
3
4
Extremely
Valuable
5
Mean Rank (SE)
M
AGFC Seminar
212
(22%)
197
(20%)
302
(31%)
189
(19%)
74
(8%)
2.71 (0.04)
3
Biologist Contact 104
(10%)
87
(9%)
202
(20%)
280
(28%)
344
(34%)
3.66 (0.04) 4
Book or Magazine 74
(7%)
99
(10%)
309
(30%)
340
(33%)
217
(21%)
3.51 (0.04) 4
Video 86
(9%)
82
(8%)
268
(27%)
326
(32%)
243
(24%)
3.56 (0.04) 4
Research Publications 81
(8%)
72
(7%)
273
(26%)
339
(33%)
270
(26%)
3.62 (0.04) 4
100
Table 55. Response frequencies on value of delivery method of white-tailed deer management information to responding hunt camps
in the Ozarks DMU. Rank levels from 1 (not valuable) to 5 (extremely valuable).
Rank Levels Summary Statistics
Delivery Method
Not
Valuable
1
2
3
4
Extremely
Valuable
5
Mean Rank (SE)
M
AGFC Seminar
39
(21%)
30
(16%)
61
(33%)
32
(17%)
25
(13%)
2.86 (0.10)
3
Biologist Contact 15
(8%)
13
(7%)
38
(19%)
55
(28%)
75
(38%)
3.83 (0.09) 4
Book or Magazine 12
(6%)
21
(10%)
49
(24%)
70
(34%)
55
(27%)
3.65 (0.08) 4
Video 12
(6%)
16
(8%)
48
(25%)
59
(31%)
58
(30%)
3.70 (0.08) 4
Research Publications 14
(7%)
10
(5%)
55
(28%)
47
(24%)
72
(36%)
3.77 (0.09) 4
101
Table 56. Response frequencies on value of delivery method of white-tailed deer management information to responding hunt camps
in the Ouachitas DMU. Rank levels from 1 (not valuable) to 5 (extremely valuable).
Rank Levels Summary Statistics
Delivery Method
Not
Valuable
1
2
3
4
Extremely
Valuable
5
Mean Rank (SE)
M
AGFC Seminar
16
(24%)
11
(16%)
21
(31%)
15
(22%)
4
(6%)
2.70 (0.15)
3
Biologist Contact 9
(13%)
5
(7%)
14
(21%)
24
(35%)
16
(24%)
3.49 (0.16) 4
Book or Magazine 6
(9%)
9
(13%)
21
(30%)
20
(29%)
14
(20%)
3.38 (0.14) 3
Video 18 7 10
(11%) (15%)
20
(30%) (27%)
11
(17%)
3.24 (0.15) 3
Research Publications 9
(13%)
6
(9%)
16
(24%)
26
(38%)
11
(16%)
3.35 (0.15) 4
102
Table 57. Response frequencies on value of delivery method of white-tailed deer management information to responding hunt camps
in the Mississippi Alluvial Plain DMU. Rank levels from 1 (not valuable) to 5 (extremely valuable).
Rank Levels Summary Statistics
Delivery Method
Not
Valuable
1
2
3
4
Extremely
Valuable
5
Mean Rank (SE)
M
AGFC Seminar
32
(24%)
28
(21%)
43
(32%)
25
(19%)
6
(4%)
2.59 (0.10)
3
Biologist Contact 15
(11%)
11
(8%)
28
(20%)
39
(28%)
45
(33%)
3.64 (0.11) 4
Book or Magazine 11
(8%)
9
(7%)
47
(34%)
46
(34%)
24
(18%)
3.46 (0.09) 4
Video
(19%)
12
(29%)
16 10
(12%) (7%)
41
(30%)
45
(32%)
27 3.41 (0.10) 4
Research Publications
(9%)
6
(4%)
40 44
(32%)
36
(26%)
3.62 (0.10) 4
103
Table 58. Response frequencies on value of delivery method of white-tailed deer management information to responding hunt camps
in the Gulf Coastal Plain DMU. Rank levels from 1 (not valuable) to 5 (extremely valuable).
Rank Levels Summary Statistics
Delivery Method
Not
2
M
120 2.69 (0.05)
Valuable
1
3
4
Extremely
Valuable
5
Mean Rank (SE)
AGFC Seminar
(21%)
120
(21%)
166
(30%)
116
(21%)
37
(7%)
3
Biologist Contact 62
(11%)
53
(9%)
117
(20%)
157
(27%)
196
(34%)
3.64 (0.05)
(24%)
4
Book or Magazine 43
(7%)
57
(10%)
183
(31%)
193
(32%)
121
(20%)
3.49 (0.05) 4
Video 49
(8%)
44
(8%)
152
(26%)
190
(33%)
145
(25%)
3.58 (0.05) 4
Research Publications 43
(7%)
46
(8%)
155
(26%)
212
(35%)
146 3.62 (0.05) 4
104
Table 59. Number of responding hunt camps that feel that the Arkansas Game and Fish
Commission (AGFC) is doing a good job managing the Arkansas white-tailed deer herd to meet
AGFC white-tailed deer program goals?
Meeting Goals Response Frequency
Yes
944 (80%)
No 240 (20%)
Table 60. Response frequencies of responding hunt camps opinions on future management options available to the Arkansas Game and Fish Commission (AGFC)
for white-tailed deer management across Arkansas. Rank levels from 1 (most important) to 8 (least important).
Rank Levels Summary Statistics
Management Options
Most
Important
1
2
3
4
5
6
7
Least
Important
8
Mean Rank (SE)
M
Increasing Antlerless Hunting Opportunities
280
(30%)
67
(7%)
63
(7%)
133
(14%)
96
(10%)
45
(5%)
37
(4%)
207
(22%)
4.09 (0.09)
4
Antler Restrictions (other than 3 point rule) 248
(27%)
92
(10%)
58
(6%)
105
(11%)
132
(14%)
57
(6%)
49
(5%)
174
(19%)
4.11 (0.09) 4
Expanding Education Efforts on Deer Management
Assistance for Private Lands
343
(35%)
176
(18%)
141
(15%)
109
(11%)
55
(6%)
50
(5%)
36
(4%)
62
(6%)
2.96 (0.07) 2
Increasing Deer Research and Survey Work to Solve Deer
Management Problems
233
(24%)
185
(19%)
178
(18%)
138
60
(14%)
92
(10%)
54
(6%)
33
(3%)
53
(5%)
3.23 (0.06) 3
Increasing Public Information and Education on Deer
Management Techniques
261
(27%)
148
(15%)
172
(17%)
159
(16%)
111
(11%)
37
(4%)
37
(4%) (6%)
3.27 (0.07) 3
Reducing Antlered Buck Bag Limit from 2 Deer/Hunter to
1 Deer/Hunter
108
(12%)
46
(5%)
30
(3%)
42
(5%)
41
(5%)
127
(14%)
146
(16%)
357
(40%)
5.91 (0.08) 7
Reducing Number of Days Antlered Bucks Can Be
Harvested With Modern Gun
135
(15%)
42
(5%)
47
(5%)
59
(6%)
72
(8%)
135
(15%)
176
(19%)
255
(28%)
5.47 (0.08) 6
Implementing Hunting Permit Quotas for Antlered Bucks 56
(7%)
16
(2%)
28
(3%)
53
(6%)
75
(9%)
109
(13%)
101
(12%)
419
(49%)
6.39 (0.07) 7
105
Table 61. Response frequencies of responding hunt camps opinions on future management options available to the Arkansas Game and Fish Commission (AGFC)
for white-tailed deer management in the Ozarks DMU. Rank levels from 1 (most important) to 8 (least important).
Rank Levels Summary Statistics
Management Options
Most
Important
1
2
Important
8 Mean Rank (SE)
47 11
(6%)
13 23 19 9 46
3
4
5
6
7
Least
M
Increasing Antlerless Hunting Opportunities
(27%)
(7%)
(13%)
(11%)
(5%)
9
(5%)
(26%)
4.41 (0.20)
4
Antler Restrictions (other than 3 point rule) 57
(32%)
20
(11%)
16
(9%)
21
(12%)
19
(11%)
14
(8%)
8
(4%)
24
(13%)
3.66 (0.19) 3
Expanding Education Efforts on Deer Management
Assistance for Private Lands
61
(32%) (9%)
12
37
26
44
(23%)
27
(14%)
17 13
(7%) (6%)
5
(3%)
9
(5%)
2.88 (0.15) 2
Increasing Deer Research and Survey Work to Solve Deer
Management Problems (21%)
31
(17%)
43
(24%)
27
(15%)
20
(11%)
8
(4%)
4
(2%)
9
(5%)
3.26 (0.14) 3
Increasing Public Information and Education on Deer
Management Techniques
47
(25%)
30
(16%)
28
(15%)
33
(18%) (14%)
10
(5%)
6
(3%)
7
(4%)
3.27 (0.14) 3
Reducing Antlered Buck Bag Limit from 2 Deer/Hunter to
1 Deer/Hunter
27
(15%)
9
(5%)
9
(5%)
6
(3%)
7
(7%)
31
(17%)
34
(19%)
56
(56%)
5.60 (0.19) 7
Reducing Number of Days Antlered Bucks Can Be
Harvested With Modern Gun
40
(22%)
8
(4%)
8
(4%)
10
(5%)
18
(10%)
21
(11%)
39
(21%)
41
(22%)
5.06 (0.20) 6
Implementing Hunting Permit Quotas for Antlered Bucks 9
(5%)
4
(2%)
5
(3%)
11
(7%)
14
(8%)
26
(16%)
18
(11%)
78
(47%)
6.38 (0.16) 7
106
Table 62. Response frequencies of responding hunt camps opinions on future management options available to the Arkansas Game and Fish Commission (AGFC)
for white-tailed deer management in the Ouachitas DMU. Rank levels from 1 (most important) to 8 (least important).
Rank Levels Summary Statistics
Management Options
Most
Important
1
2
3
4
5
6
7
Least
Important
8
Mean Rank (SE)
M
Increasing Antlerless Hunting Opportunities
18
(30%)
5
(8%)
4
(7%)
6
(10%)
7
(12%)
6
(10%)
2
(3%)
12
(20%)
4.08 (0.35)
4
Antler Restrictions (other than 3 point rule) 6
(10%)
11
(18%)
4
(7%)
8
(13%)
7
(12%)
3
(5%)
5
(8%)
16
(27%)
4.80 (0.33) 5
Expanding Education Efforts on Deer Management
Assistance for Private Lands
27
(41%)
11
(17%)
9
(14%)
6
(9%)
4
(6%)
1
(2%)
4
(6%)
4
(6%)
2.82 (0.27) 2
Increasing Deer Research and Survey Work to Solve Deer
Management Problems
17
(26%)
11
(17%)
11
(17%)
11
(17%)
8
(12%)
3
6
(54%)
3
(5%)
2
(3%)
3
(5%)
3.21 (0.24) 3
Increasing Public Information and Education on Deer
Management Techniques
19
(29%)
9
(14%)
12
(18%)
8
(12%)
8
(12%)
5
(8%)
2
(3%)
3
(5%)
3.22 (0.25)
Reducing Antlered Buck Bag Limit from 2 Deer/Hunter to
1 Deer/Hunter
7
(12%)
3
(5%)
1
(2%)
4
(7%)
1
(2%)
9
(15%)
11
(18%)
24
(40%)
6.00 (0.32) 7
Reducing Number of Days Antlered Bucks Can Be
Harvested With Modern Gun
4
(7%)
2
(3%)
5
(8%)
6
(10%)
5
(8%)
15
(25%)
7
(12%)
16
(27%)
5.65 (0.28)
Implementing Hunting Permit Quotas for Antlered Bucks 3
(5%)
3
(5%)
1
(2%)
4
(7%)
5
(9%)
4
(7%)
6
(11%)
31 6.43 (0.29) 8
107
Table 63. Response frequencies of responding hunt camps opinions on future management options available to the Arkansas Game and Fish Commission (AGFC)
for white-tailed deer management in the Mississippi Alluvial Plain DMU. Rank levels from 1 (most important) to 8 (least important).
Rank Levels Summary Statistics
Management Options
Most
Important
1
2
3
4
5
6
7 8 M
(8%)
Least
Important
Mean Rank (SE)
Increasing Antlerless Hunting Opportunities
23
(18%)
10
8
(6%)
31
(24%)
17
(13%)
7
(6%)
2
(2%)
29
(23%)
4.44 (0.22)
4
Antler Restrictions (other than 3 point rule) 40
(31%)
12
(9%)
9
(7%)
18
(14%)
21
(16%)
4
(3%)
7
(5%)
17
(13%)
3.73 (0.22) 4
Expanding Education Efforts on Deer Management
Assistance for Private Lands
50
(37%)
28
(21%)
23
(17%)
13
(10%)
5
(4%)
8
(6%)
3
(2%)
6
(4%)
2.71 (0.17) 2
Increasing Deer Research and Survey Work to Solve Deer
Management Problems
28
(21%)
33
(24%)
25
(18%)
18
(13%)
15
(11%)
11
(8%)
4
(3%)
2
(1%)
3.13 (0.15) 3
Increasing Public Information and Education on Deer
Management Techniques
36
(26%)
25
(18%)
25
(18%)
17
(12%)
16
(12%)
7
(5%)
7
(5%)
5
(4%)
3.19 (0.17) 3
Reducing Antlered Buck Bag Limit from 2 Deer/Hunter to
1 Deer/Hunter
11
(9%)
2
(2%)
6
(5%)
8
(7%)
9
(7%)
21
(17%)
17
(14%)
48
(39%)
6.06 (0.20) 7
Reducing Number of Days Antlered Bucks Can Be
Harvested With Modern Gun
14
(11%)
6
(5%)
4
(3%)
9
(7%)
16
(13%)
12
(9%)
31
(24%)
36
(28%)
5.71 (0.21) 7
Implementing Hunting Permit Quotas for Antlered Bucks 11
(9%)
2
(2%)
4
(3%)
8
(7%)
16
(13%)
20
(17%)
9
(8%)
49
(41%)
6.00 (0.21) 6
108
Table 64. Response frequencies of responding hunt camps opinions on future management options available to the Arkansas Game and Fish Commission (AGFC)
for white-tailed deer management in the Gulf Coastal Plain DMU. Rank levels from 1 (most important) to 8 (least important).
Rank Levels Summary Statistics
Management Options
Most
Important
1
2
3
4
5
6
7
Least
Important
8
Mean Rank (SE)
M
Increasing Antlerless Hunting Opportunities
182
(34%)
40
(7%)
36
(7%)
69
(13%)
50
(9%)
23
(4%)
24
(4%)
114
(21%)
3.93 (0.12)
4
Antler Restrictions (other than 3 point rule) 140
(27%)
48
(9%)
27
(5%)
53
(10%)
82
(16%)
36
(7%)
26
(5%)
112
(21%)
4.26 (0.12) 4
Expanding Education Efforts on Deer Management
Assistance for Private Lands
199
(36%)
87
(16%)
81
(15%)
69
(12%)
30
(5%)
28
(5%)
22
(4%)
41
(7%)
3.04 (0.09) 2
Increasing Deer Research and Survey Work to Solve Deer
Management Problems
143
(26%)
108
(19%)
95
(17%)
79
(14%)
43
(8%)
29
(5%)
23
(4%)
38 3.25 (0.09)
78 15
(4%)
3.30 (0.09)
Reducing Antlered Buck Bag Limit from 2 Deer/Hunter to
1 Deer/Hunter
31
(3%)
23
(12%)
218 5.94 (0.11)
5.51 (0.11)
250
(7%)
3
Increasing Public Information and Education on Deer
Management Techniques
154
(27%) (14%)
102
(18%)
98
(17%)
58
(10%) (3%)
21 43
(8%)
3
62
(12%) (6%)
14 24
(5%) (4%)
61 80
(16%) (43%)
7
Reducing Number of Days Antlered Bucks Can Be
Harvested With Modern Gun
75
(14%)
26
(5%)
29
(6%)
32
(6%)
31
(6%)
83
(16%)
95
(18%)
154
(29%)
6
Implementing Hunting Permit Quotas for Antlered Bucks 31
(6%)
7
(1%)
17
(3%)
30
(6%)
40
(8%)
55
(11%)
63
(13%) (51%)
6.46 (0.09) 8
109
110
Table 65. Number of responding hunt camps (%) that offer wildlife related recreational
opportunities for members and the number of members (mode (sample size)) involved across
Arkansas.
Response Frequency No. Members Involved
Wildlife Related Opportunities Yes Mode and sample size (n)
Fishing
404 (34%)
6: n=311
Swimming 109 (9%) 5: n=76
Hiking 294 (25%) 5: n=213
Wildlife Observation 472 (40%) 6: n=341
Bird Watching 255 (22%) 2: n=168
Table 66. Number of responding hunt camps that allow guests of camp members to harvest
antlerless deer on hunt camp property by DMU and statewide in Arkansas.
Guest
Hunting
Ozarks
Ouachitas
Mississippi Alluvial
Plain
Gulf Coastal
Plain
Statewide
Yes
183 (78%)
49 (66%)
130 (83%)
586 (85%)
974 (82%)
No 52 (22%) 25 (34%) 26 (17%) 100 (15%) 210 (18%)
Table 67. Response frequencies of problems occurring on responding hunt camps property across Arkansas. Rank levels from 1 (greatest problem) to 7
(least problem).
Rank Levels Summary Statistics
Camp Problems
Greatest
Problem
1
2
3
4
5
6
Least
Problem
7
Mean Rank (SE)
M
Unauthorized Hunting of Deer
285
(30%)
142
(15%)
116
(12%)
126
(13%)
101
(11%)
61
(6%)
126
(13%)
3.32 (0.07)
3
Unauthorized Hunting of Other Wildlife 148
(16%)
65
(7%)
114
(13%)
118
(13%)
158
(17%)
117
(13%)
187
(21%)
4.29 (0.07) 5
Illegal Hunting (Poaching) 314
(32%)
171
(18%)
129
(13%)
109
(11%)
69
(7%)
44
(5%)
132
(14%)
3.11 (0.07) 2
Dog Hunting Forcing Deer off Camp
Property
191
(21%)
60
(7%)
80
(9%)
62
(7%)
81
(9%)
134
(15%)
291
(32%)
4.50 (0.08) 5
Non-Member Hunting Near Camp Boundary 293
(30%)
131
(13%)
112
(11%)
95
(10%)
100
(10%)
99
(10%)
145
(15%)
4.47 (0.07) 3
Trespassing 316 160
(32%)
140
(14%) (16%)
135
(14%)
85
(9%)
62
(6%)
99
(10%)
3.12 (0.06) 3
Safety of Members While Hunting 59
(7%)
18
(2%)
20
(2%)
28
(3%)
56
(7%)
109
(13%)
566
(66%)
6.03 (0.06) 7
111
Table 68. Response frequencies of problems occurring on responding hunt camps property in the Ozarks DMU. Rank levels from 1 (greatest problem) to 7
(least problem).
Rank Levels Summary Statistics
Camp Problems
Problem
1
2
Mean Rank (SE)
M
Unauthorized Hunting of Deer
31 12
(6%)
21 59
(30%)
(16%)
21
(11%)
28
(14%)
23
(12%)
(11%)
3.23 (0.15)
3
Unauthorized Hunting of Other Wildlife 27
(15%) (13%)
23
12
(7%)
21
(12%)
23 35
(19%) (13%)
40
(22%)
4.41 (0.15) 5
Illegal Hunting (Poaching) 54
(28%)
42
(22%)
24
(13%)
23
(12%)
13
(7%)
9
(5%)
27
(14%)
3.18 (0.15) 2
Dog Hunting Forcing Deer off Camp
Property
52
(28%)
15
(8%)
16
(9%)
10
(5%)
22
(13%)
22
(13%)
49
(26%)
4.06 (0.18) 4
Non-Member Hunting Near Camp Boundary 57
(30%)
24
(13%)
26
(14%)
21
(11%)
16
(8%)
22
(12%)
24
(13%)
3.41 (0.16) 3
Trespassing 61 37
(31%)
28
(14%) (19%)
25
(13%)
15
(8%)
15
(8%)
19
(10%)
3.13 (0.14) 3
Safety of Members While Hunting 13
(8%)
4
(2%)
3
(2%)
8
(5%)
12
(7%)
19
(11%)
109
(65%)
5.95 (0.14) 7
Greatest
3
4
5
6
Least
Problem
7
112
Table 69. Response frequencies of problems occurring on responding hunt camps property in the Ouachitas DMU. Rank levels from 1 (greatest problem)
to 7 (least problem).
Rank Levels Summary Statistics
Camp Problems
Greatest
Problem
1
2
3
4
5
6
Least
Problem
7
Mean Rank (SE)
M
Unauthorized Hunting of Deer
23
(37%)
6
(10%)
7
(11%)
7
(11%)
10
(16%)
5
(8%)
5
(8%)
3.16 (0.26)
3
Unauthorized Hunting of Other Wildlife 11
(19%)
4
(7%)
2
(3%)
10
(17%)
15
(25%)
8
(14%)
9
(15%)
4.25 (0.27) 5
Illegal Hunting (Poaching) 23
(35%)
11
(17%)
11
(17%)
6
(9%)
5
(8%)
5
(8%)
4
(6%)
2.85 (0.24) 2
Dog Hunting Forcing Deer off Camp Property 19
(31%)
5
(8%)
8
(13%)
6
(10%)
4
(6%)
6
(10%)
14
(23%)
3.73 (0.30) 3
Non-Member Hunting Near Camp Boundary 11
(17%)
8
(13%)
7
(11%)
9
(14%)
8
(3%)
12
(19%)
8
(13%)
4.00 (0.26) 4
Trespassing 24 13
(36%)
12
(18%) (19%)
8
(12%)
3
(4%)
4
(4%)
4
(6%)
2.69 (0.22) 2
Safety of Members While Hunting 5
(8%)
1
(2%)
0
(0%)
2
(3%)
3
(5%)
8
(13%)
41
(68%)
6.08 (0.23) 7
113
Table 70. Response frequencies of problems occurring on responding hunt camps property in the Mississippi Alluvial Plain DMU. Rank levels from 1
(greatest problem) to 7 (least problem).
Rank Levels Summary Statistics
Camp Problems
Greatest
Problem
1
2
3
4
5
6
Least
Problem
7
Mean Rank (SE)
M
Unauthorized Hunting of Deer
34
(27%)
21
(17%)
19
(15%)
15
(12%)
12
(10%)
8
(6%)
17
(13%)
3.33 (0.19)
3
Unauthorized Hunting of Other Wildlife 10
(8%)
13
(10%)
18
(15%)
20
(16%)
21
(17%)
20
(16%)
22
(18%)
4.43 (0.17) 5
Illegal Hunting (Poaching) 50
(37%)
26
(19%)
22
(16%)
13
(9%)
12
(9%)
4
(3%)
10
(7%)
2.73 (0.16) 2
Dog Hunting Forcing Deer off Camp Property 8
(7%)
6
(5%)
14
(12%)
13
(11%)
11
(9%)
27
(23%)
41
(34%)
5.15 (0.18) 6
Non-Member Hunting Near Camp Boundary 43
(32%)
23
(17%)
18
(13%)
11
(8%)
12
(9%)
11
(8%)
16
(12%)
3.17 (0.18) 3
Trespassing 47
(34%)
25
(18%)
21
(15%)
23
(17%)
8
(6%)
9
(6%)
6
(4%)
2.79 (0.15) 2
Safety of Members While Hunting 7
(6%)
1
(1%)
5
(4%)
5
(4%)
8
(7%)
15
(13%)
77
(65%)
6.04 (0.16) 7
114
Table 71. Response frequencies of problems occurring on responding hunt camps property in the Gulf Coastal Plain DMU. Rank levels from 1 (greatest
problem) to 7 (least problem).
Rank Levels Summary Statistics
Camp Problems
Greatest
Problem
1
2
3
4
5
6
Least
Problem
7
Mean Rank (SE)
M
Unauthorized Hunting of Deer
160
(29%)
81
(15%)
61
(11%)
72
(13%)
55
(10%)
35
(6%)
82
(15%)
3.39 (0.09)
3
Unauthorized Hunting of Other Wildlife 91
(18%)
33
(6%)
68
(13%)
61
(12%)
83
(16%)
65
(13%)
115
(22%)
4.29 (0.09) 5
Illegal Hunting (Poaching) 177
(32%)
86
(16%)
70
(13%)
62
(11%)
38
(7%)
24
(4%)
90
(16%)
3.24 (0.09) 3
Dog Hunting Forcing Deer off Camp Property 109
(21%)
32
(6%)
40
(8%)
32
(6%)
42
(8%)
75
(15%)
178
(35%)
4.58 (0.11) 5
Non-Member Hunting Near Camp Boundary 175
(31%)
70
(13%)
59
(11%)
52
(9%)
61
(11%)
50
(9%)
91
(16%)
3.48 (0.10) 3
Trespassing 171
(31%)
69
(12%)
86
(15%)
74
(13%)
56
(10%)
35
(6%)
69
(12%)
3.28 (0.09) 3
Safety of Members While Hunting 32
(7%)
12
(2%)
11
(2%)
13
(3%)
32
(7%)
66
(14%)
321
(66%)
6.05 (0.08) 7
115
116
Appendix 1
117
In order to categorize the data more effectively, please indicate which of the following most
closely applies to you.
(___) Land Owner – person who owns the land that the hunt club is located on.
(___) Land Manager – person who owns the land and is responsible for the management of the
club and wildlife management practices used on the land.
(___) Club Manager – person who does not own the land but is responsible for the management
of the club and wildlife management practices used on the land.
Arkansas Deer Club Contact Questionnaire
Club Information
Club Name______________________________________________________________
1) What is your AGFC hunt club identification number? #_____________
2) Where is the property that you manage (or hunt) located?
Deer Zone-__________ County-_______________
3) How many acres is your hunt club?
Acres-__________
4) Which type of property is a majority of the hunt club located on?
(___) – Privately owned land (club member owned)
(___) – Privately owned land the club leases (non-member owned)
(___) – Industry Land (e.g. timber company land)
(___) – Public Lands
5) How many members does your club have?
Number of Club Members -__________
6) How many white-tailed deer did members of your club harvest last season?
(___) – Antlered Bucks (___) – Does (___) – Fawns (under 12 months old)
7) Is your club under a Quality Deer Management (QDM) program?
(___) – Yes (___) – No
118
8) If yes to question seven (7), what is your clubs management objective (check only one)?
(___) – Maintain present deer herd density (deer harvest used to prevent herd growth,
maintain current age-sex ratios, and maintain herd health).
(___) – Increase deer density (deer harvest restricted to allow for increase in total deer
numbers on the club property).
(___) – Improve antler development/physical condition of the deer herd (deer harvest
restricted to allow more bucks to reach older age classes of >2.5 years old).
(___) – Trophy deer (deer harvest restricted to allow more bucks to reach mature age
classes of >4.5 years old)
(___) – Other (please explain) _______________________________________________
9) Does your club attempt to control hunter pressure or density (hunters per acre(s)) on your
clubs land?
(___) – Always (___) – Usually (___) – Sometimes (___) – Never
If so what is the maximum number of hunters per acre(s)?
Number of hunters (________) per (________) acre(s)
10) Does your club practice more restrictive deer management practices than those set by the
AGFC, and if so what are they? (Please Rank all that apply from 1 (practice most
used) to 7 (practice least used)).
(___) – Do not practice more restrictive deer management.
(___) – Mandatory doe harvest
(___) – Mandatory doe harvest prior to buck harvest
(___) – Minimum 4-point rule or greater
(___) – Minimum antler spread
(___) – Restricted buck harvest
(___) – Restricted antlerless harvest (no “button” bucks harvested)
(___) – Other (please list) __________________________________________________
119
11) What types of habitat management practices does your club use for white-tailed deer
(Please Rank all that apply from 1 (practice most used) to 9 (practice least used)).
(___) – Summer food plots
(___) – Winter food plots
(___) – Fertilizing of natural vegetation
(___) – Supplemental feeding (automatic feeders) of corn, beans, etc (not through normal
agricultural practices)
(___) – Supplemental salt/mineral blocks
(___) – Prescribed burns
(___) – Timber management/timber harvest
(___) – Set-aside programs (e.g. CRP, WRP, Acres for Wildlife (AFW))
(___) – Other (list)________________________________________________________
12) How long has your hunt club been using these habitat management practices (please fill
in the number of years that a particular management practices has been used)?
Practice No. Years
Summer Food Plots (_______)
Winter Food Plots (_______)
Fertilizing natural vegetation (_______)
Supplemental feeding (corn, beans, etc.) (_______)
Supplemental salt/mineral blocks (_______)
Prescribed burns (_______)
Timber harvest/timber management (_______)
Set-aside programs (CRP, WRP, AFW) (_______)
Other- (from previous question) (_______)
120
13) In addition to management practices for white-tailed deer, does your club manage for any
other wildlife? (Please Rank all that apply from 1 (managed the most) to 12
(managed the least)).
(___) – Ducks and Geese (___) – Dove
(___) – Turkey (___) – Rabbit
(___) – Quail (___) – Feral Hogs
(___) – Bear (___) – Furbearers
(___) – Elk (___) – Non-game/endangered species
(___) – Squirrels
(___) – Other (please explain)______________________________
14) What management practices does your club use for other wildlife on the club property?
(Please Rank all that apply from 1 (technique used most) to 6 (technique used
least)).
(___) – Flooding fields for waterfowl
(___) – Nest platforms or boxes for waterfowl
(___) – Feeders/nest boxes for songbirds
(___) – Mowing or grassland management
(___) – Timber management
(___) – Other (please explain)-_______________________________________________
15) Since your club began using different management practices for white-tailed deer, have
you seen (please check all that apply)?
(___) – An increase in the total number of deer on the club property
(___) – An increase in the number of bucks on the club property (2.5 years and older)
(___) – An increase in the number of bucks on the club property (4.5 years and older)
(___) – An increase in the overall antler size/spread/total points of harvested bucks
(___) – An improvement in harvested deer health/weight (both does and bucks)
(___) – A more equal number of bucks and does on the club property
121
16) Does your hunt club keep harvest totals and biological records of deer harvested by the
club members (e.g. total points, beam length, tine length, inside spread, jawbones aged,
dressed weight)?
(___) – Yes (___) - No
17) If your club keeps harvest records, would you make them available for research
purposes?
(___) – Yes (___) – No
18) Does your club work with an AGFC wildlife biologist in establishing white-tailed deer
harvest and habitat management guidelines?
(___) – Yes (___) – No
19) Do you feel that your club would benefit from increased management assistance from the
AGFC?
(___) – Yes (___) – No
20) What type of management assistance from the AGFC do you feel would benefit/interest
your club? (Please Rank from 1 (most beneficial) to 7 (least beneficial)).
(___) – Public Information Programs
(___) – Hunter Educational Programs
(___) – Wildlife Management Assistance Programs
(___) – Management recommendations from a Wildlife Biologist
(___) – Population/Density Estimation of clubs white-tailed deer herd
(___) – Habitat Development and Management Assistance
(___) – Non-game/endangered species management
(___) – Other (please explain) - ______________________________________________
122
21) Has your club sought outside assistance or advice on harvest or habitat management for
the clubs property (including AGFC assistance or other wildlife biologists)?
(___) – Yes (___) - No
22) As the club contact, what type of information provided by the AGFC would interest you
and assist you in managing the white-tailed deer on the club? Please circle the number for
each statement that best describes the type of information that interests you.
Not Slightly Moderately Very Extremely Interested Interested Interested Interested Interested
Hunting Techniques 1 2 3 4 5
Aging Techniques 1 2 3 4 5
Harvest Management 1 2 3 4 5
Deer Behavior 1 2 3 4 5
Food Plots 1 2 3 4 5
Forest Management 1 2 3 4 5
Prescribed Burning 1 2 3 4 5
Deer Genetics 1 2 3 4 5
Wildlife Plants 1 2 3 4 5
QDM Techniques 1 2 3 4 5
Supplemental Feeding 1 2 3 4 5
23) Circle the number that best describes how valuable each method of information delivery
is to you.
Not Slightly Moderately Very Extremely Valuable Valuable Valuable Valuable Valuable
AGFC Seminar 1 2 3 4 5
Biologist Contact 1 2 3 4 5
Book or Magazine 1 2 3 4 5
Video 1 2 3 4 5
Research Publications 1 2 3 4 5
123
24) The current goal of the AGFC deer program is to “maintain a healthy deer herd with a
balanced sex and age structure at a level that is consistent with long-term habitat
capability; and to maintain deer populations and parameters at levels that are consistent
with public satisfaction and acceptance.” Do you feel that the AGFC is doing a good job
of managing the white-tailed deer herd in the state to meet this objective.
(___) – Yes (___) – No
25) The AGFC has many different management options available to increase herd quality in
the future. Which of these management options do you feel would be best for the state of
Arkansas (please Rank from 1 (most important) to 8 (least important)?
(___) – Increasing antlerless hunting opportunities for the modern firearm season and
allow antlerless harvest at the beginning of the firearm season
(___) – Antler restrictions (other than the state 3 point rule)
(___) – Expanding efforts to educate hunters and hunt clubs on deer management
assistance programs for private lands
(___) – Increasing deer research and survey work to help solve deer management
programs
(___) – Increasing public information and educational materials on proper deer
management techniques
(___) – Reducing the annual antlered buck bag limit from 2 deer/hunter to 1 deer/hunter
each year.
(___) – Reducing the number of days antlered bucks may be harvested with modern
firearms.
(___) – Implementing hunting permit quotas for antlered bucks
124
26) Does your club offer other wildlife-related recreational opportunities on the club
property? If so please provide the following information.
Yes No Number members involved
Fishing (___) (___) (___)
Swimming (___) (___) (___)
Hiking (___) (___) (___)
Wildlife Observation (___) (___) (___)
Bird Watching (___) (___) (___)
27) Does your club make any of its lands available to public hunting by individually issuing
permits?
(___) – Yes (___) – No
If yes, how many acres are involved?
Number acres (___)
28) Does your club allow guests of members to hunt for antlerless deer?
(___) – Yes (___) – No
29) Please rank problems that occur on your club’s property. Please Rank all that apply
from 1 to 7 (1 being the greatest problem and 7 being the least).
(___) – Unauthorized hunting of deer
(___) – Unauthorized hunting of other game species
(___) – Illegal hunting (Poaching on the club property)
(___) – Dog hunting in the area forcing deer off club boundaries
(___) – Non-club members harvesting deer near club boundaries (private lands
surrounding club)
(___) – Trespassing
(___) – Safety of members while hunting