Southeast Regional Wild Turkey Reproductive Decline Study
Progress Report – December 2012
Investigators: Michael E. Byrne and Michael J. Chamberlain
Warnell School of Forestry and Natural Resources
University of Georgia
180 E Green St
Athens, GA 30602
Bret A. Collier
Institute of Renewable Natural Resources
Texas A&M University
1500 Research Parkway, Suite 110
College Station, TX 77843
Data collection and quality
Research activity began in April 2012 and to date has focused on the collection and
synthesis of relevant data from participating states in the region. We are using this information
to form hypotheses and guide the direction of future analysis, as well as to provide
recommendations for future data collection protocols. At the initiation of the study, each state
was asked to provide the University of Georgia (UGA) with any relevant data. Because the
primary focus of this study is the perceived decline in reproductive productivity, we were most
interested in historical records of productivity estimates. We also requested any other available
data that may serve as an indicator of overall population size or provide information on historical
changes in population, such as harvest data, gobbling surveys, and restocking information.
As of December 1, we have received data from 14 of the 15 participating states. The last
state to provide data was Kentucky (3 October), and no data has yet been received from West
Virginia (although those data should be received soon). Eleven states have collected
productivity data over a large enough temporal scale to provide insight into historical trends.
Alabama began a summer brood survey program in 2010, whereas Texas and Florida have never
collected such data (Table 1). All states with the exception of Virginia used poult-per-hen (PPH)
ratios calculated from summer brood surveys to estimate production. The methods of data
collection and PPH calculation among states varies in several respects. For example, Tennessee
calculates PPH ratios based on observations collected during August, Kentucky bases PPH ratios
on observations collected during July and August, whereas the remaining states use observations
from June, July, and August. Historical PPH ratios in Missouri have been calculated based on
observation of brood groups consisting of only ≤ 2 hens whereas other states use all
observations. Virginia calculates PPH ratios based on the ratio of adult and juvenile females
checked during the fall either-sex hunting season.
In addition to productivity data, all states maintain some form of long term harvest
records, although these data are highly variable among states. Estimation of harvest numbers is
often based on check station returns, and/or hunter surveys. In many states the method of data
collection has changed over time and more than one method may be used simultaneously. In
some states, a measure of success per hunter, or success per unit effort, can be calculated based
on survey information, whereas in others this information is lacking.
Preliminary findings
Although we are still in the preliminary stages of analysis, 2 interesting trends have
emerged as we have summarized data for individual states. Generally, estimates of population
size or indices of population size (e.g. harvest records) tend to indicate that turkey populations in
many states are stable or increasing (Fig.1). As previously mentioned, the lack of consistency
used to estimate population sizes is an issue. This has led us to consider incorporating data from
the USGS Breeding Bird Survey (BBS). The BBS provides a long term data set of estimated
population indices collected in a methodologically consistent manner across all of North
America (Sauer et al. 2003). In many states turkey population indices based on the BBS
corroborate the observation of increasing population sizes as indicated from harvest information
(Fig. 2). Additionally, BBS indices correlate well with spring harvest numbers (Fig. 3). This
indicates that BBS data may provide an accurate measure of population change through time, at
least at the state-level.
In contrast to population size, productivity estimates indicate that in many states
reproductive output is in a state of decline, or has leveled off following a decline. This trend of
increasing population size concurrent with declines in productivity has led us to hypothesize that
density-dependent forces may be acting on turkey reproduction in the region. In a densitydependent scenario one may expect a negative relationship to exist between population size and
reproduction, and plots of reproductive indices as a function of population size based on BBS
data do indicate such a relationship in many states (Fig. 4). When plotted over time, the decline
in reproductive output as determined by PPH ratios tends to coincide with the increase in BBS
values (Fig. 5). Considering population models for wild turkey populations have traditionally
ignored density-dependence (Roberts and Porter 1996, Alpizar-Jara et al. 2001), strong evidence
of a density-dependent influence on reproduction would improve population models and better
inform management strategies.
We also recognize that reproduction is influenced by density-independent forces such as
habitat quality and weather conditions. As of now we have not been able to detect any
relationships between temperature and precipitation in a given year and estimates of productivity
for any state. Temperature and precipitation are known to influence turkey reproductive success
(Vangilder 1992). Our inability to detect such a relationship is likely an artifact of the spatial
scale in which we are working. Temperature and precipitation likely act on turkey reproduction
at a local level, and at the state level such relationships may be obscured.
Ongoing work and Future plans
Currently we are assessing the methodologies associated with data collection and
productivity estimation that the states have provided. Our aim is to develop recommendations
for future data collection and analysis that the states could adopt that would serve 2 functions 1)
improve the accuracy of production estimates and 2) standardize the process among states.
Standardization of methodologies may be particularly useful for future comparisons among
states as well as regional analyses. Currently, the differences among states do not allow for direct
comparisons of reproductive output. We plan to present our recommendations at the next
meeting of the Southeast Wild Turkey Working Group Technical Committee this coming spring.
Data analysis is ongoing. We are currently exploring the best possible analytical
techniques to apply to the data. The variation in quantity and quality of data is certainly an
obstacle to developing a comprehensive model that uses information on a regional scale, and as
such a meta-analysis approach may be the best course of action. For instance, we are exploring
the development of a suite of competing time-series models that would attempt to quantify the
nature of productivity trends through time while assessing the importance of covariates such as
BBS indices, spring harvest, fall harvest (where applicable), and landscape changes. We can
then apply these models separately to each state that has sufficient data, and use the results to
draw broad conclusions at a regional scale. We intend to further investigate the potential of GIS
based land-use data as a possible covariate of productivity; as of now we are looking at what data
sets are available at a regional scale and assessing their potential usefulness in terms of spatial
and temporal resolution through time. Additionally, once we are confident we have all the
available relevant data from each state, we plan on providing a detailed summary to each
respective state.
Literature Cited
Alpizar-Jara, R., E.N. Brooks, K.H. Pollock, D.E. Steffen, J.C. Pack, and G.W. Norman. 2001.
An eastern wild turkey population dynamics model for Virginia and West Virginia.
Journal of Wildlife Management 65:415-424.
Roberts, S.D., and W.F, Porter. 1996. Importance of demographic parameters to annual changes
in wild turkey abundance. Proceedings of the National Wild Turkey Symposium 7:15-20.
Sauer, J.R., J.E. Fallon, and R. Johnson. 2003. Use of North American breeding bird survey date
to estimate population change for bird conservation regions. Journal of Wildlife
Management 67:372-389.
Vangilder, L.D. 1992. Population dynamics. Pages 144-164 in J.G. Dickson, editor. The Wild
Turkey: Biology and Management. Stackpole Books, Harrisburg, Pennsylvania.
Table 1. Availability of historic productivity data for each state, including the number of years of data availability, raw data
availability, and the spatial breakdown of productivity estimates within each state.
Number Raw data
State
Years
of Years availability County/regional estimates
Notes
Alabama
N/A
N/A
N/A
N/A
No productivity data collected
Arkansas
1982-2011
30
2011-12
?
Statewide data taken from old report;
attempting to gain access to historic data
(pre-2010)
Florida
N/A
N/A
N/A
N/A
No productivity data collected
Georgia
1978 -2011
33
All Years
Physiographic Regions
Was able to calculate values in-house from
raw data
Kentucky
1984-2011
28
2005-2011
East/central/west
Surveys conducted during July and August
Louisiana
1994 -2010
16
All Years
Physiographic Regions
Was able to calculate values in-house from
raw data
Mississippi
1995 -2011
16
All Years
Physiographic Regions
Was able to calculate values in-house from
raw data
Missouri
1959 -2011
52
1990 - 2011 Physiographic Regions
PPH ratios only calculated for brood groups
with ≤ 2 hens
North Carolina 1988 -2011
23
2001 - 2011 Physiographic Regions
State biologists have filtered spurious
observations since about 2006
Oklahoma
1985-2010
26
2001-2012
County
Data only includes SE portion of the state
where the eastern sub-species occurs
South Carolina 1982 -2011
30
2006 - 2011 Physiographic Regions
Tennessee
1983 -2011
29
2003 - 2011 Raw data available by
PPH ratios calculated from observations
county since ‘03
during August
Texas
N/A
N/A
N/A
N/A
No productivity data collected
Virginia
1979-2010
32
Don’t have
Physiographic Regions
Productivity calculated from ratio of
adults/young in fall harvest
West Virginia
Data pending
Figure 1. Total spring harvest estimates for Tennessee, North Carolina, Alabama, and Kentucky
illustrating increasing trends over time.
Figure 2. Wild turkey population indices from 1966 – 2010 based on USGS Breeding Bird
Survey data for Tennessee, North Carolina, Alabama, and Kentucky indicating population
increases over time.
Figure 3. Plots of spring harvest numbers against Breeding Bird Survey (BBS) index values for
Tennessee, North Carolina, Missouri, and Kentucky illustrating the high correlation between the
2 metrics.
Figure 4. Plots illustrating the negative relationship between the Breeding Bird Survey (BBS)
population index values and productivity (PPH) for Tennessee, Georgia, Missouri, and Arkansas.
Figure 5. Plots of productivity (PPH ratios) and Breeding Bird Survey (BBS) index values over
time for Georgia, North Carolina, Tennessee, and Missouri; blue lines = PPH ratio, black lines =
PPH moving average, red lines = BBS index with dashed lines indicating the 95% confidence
interval.