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T. McClinton, H.A. Mathewson, S.K. McDowell, and J.D. Hall
22001199 SOUTHEASTERN NATURALIST Vo1l8.( 118):,5 N3–o6. 41
Survival, Recovery, and Reproductive Success of Mottled
Ducks on the Upper Texas Coast
Trey McClinton1,*, Heather A. Mathewson1, Stephen K. McDowell2, and
Jared D. Hall1
Abstract - Anas fulvigula (Mottled Duck) has experienced long-term population declines
due to habitat loss and other anthropogenic factors. Our objectives were to (1) generate
annual survival and recovery estimates, while examining the influence of age and sex, and
(2) examine the influence of rainfall and drought on reproductive success. We followed
the Brownie approach using the RMark package in R to analyze 4967 bandings and 705
recoveries from 2004–2015. We examined linear and curvilinear relationships between
precipitation variables and a reproductive index. Hatch-year (HY) males had the highest
annual recovery probability, while after-hatch-year (AHY) females had the lowest. Annual
survival varied predominately by sex but also with age. Hatch-year females had the lowest
estimate of survival, while after-hatch-year males had the highest. Total rainfall during
peak nesting season showed a weak negative relationship with our reproductive success
index (β = -0.0085, 95% CI: -0.0240, 0.0070), and was our only competitive model besides
the null. Annual survival and recovery estimates were similar to other studies on Mottled
Ducks. Our reproductive success analysis was inconclusive in that either there is no effect of
precipitation or the measures we used for the reproduction index or the predictor variables
were inadequate.
Introduction
During the 20th century, many North American waterfowl species experienced
population decline in response to anthropogenic factors such as overexploitation
and habitat loss through wetland conversion. Considering these declines, federal,
state, and non-governmental organizations established regulations and began
managing wetlands to promote waterfowl prosperity (Anderson et al. 2018). Most
populations have recovered well, yet the status of others remain uncertain or below
long-term goals (US Fish and Wildlife Service 2017). Today researchers utilize
various modeling methods and surveys to monitor nest and brood-rearing success,
as well as annual survival. These monitoring techniques provide data to determine
the success of current management practices and suggest changes that may be
needed to insure future prosperity.
Anas fulvigula Ridgway (Mottled Duck) is a medium-large waterfowl species
similar to Anas platyrhynchos L. (Mallard), and most closely related to Anas
diazi Ridgway (Mexican Duck). Its continental range is isolated to 2 endemic
populations, along the Western Gulf Coast (i.e., Texas, Louisiana, Mississippi,
1Department of Wildlife, Sustainability, and Ecosystem Sciences, Tarleton State University,
Stephenville, TX 76402. 2Texas Parks and Wildlife Department, Port Arthur, TX 77640.
*Corresponding author - mcclin73@msu.edu.
Manuscript Editor: Frank Moore
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2019 Vol. 18, No. 1
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and Alabama) and Florida (McCraken et al. 2001), and an introduced population
along coastal South Carolina (Shipes et al. 2015). Mottled Ducks exhibit a unique
non-migratory characteristic that requires them to meet all life-cycle needs in the
habitats and associated marshlands of these areas. This year-round dependency
exposes the species to seasonal stresses that may not normally be associated with
birds that migrate to and from breeding and wintering grounds. Potentially due to
its limited range and additional stressors, the Mottled Duck is a species of historically
small population size, relative to other dabbling ducks (e.g., Mallard; Wilson
2007). In addition, multiple factors have led to long-term population declines on
the upper Texas coast in recent decades; including habitat loss due to urban development
and changes in land use (Stutzenbaker 1988), sea-level rise and changes in
hydrology (Moon 2014), low nest success in adjacent regions (Durham and Afton
2003), hybridization with Mallards (Stutzenbaker 1988), continued susceptibility
to lead poisoning decades after the use of lead shot was banned for waterfowl
hunting (McDowell et al. 2015, Wilson 2007), and low recruitment (Johnson 2009,
Stutzenbaker 1988, Wilson 2007). Considering these influencing factors and historically
low numbers, long-term population-monitoring protocols are in place so
that we can observe the effectiveness of our adaptive management plans. Ballard et
al. (2001) suggested that there might be substantially more Mottled Ducks in Texas
than previously thought. However, significant negative trends have been observed
in the number of Mottled Ducks detected in the US Midwinter Survey (1970–2003)
and in the Breeding Bird Survey (1966–2002; Sauer et al. 2003), the number of
Mottled Ducks killed per hunter per day (1966–2002; Martin and Padding 2002),
and the number of Mottled Duck breeding pairs per square mile on national wildlife
refuges along the upper Texas Gulf Coast (1985–2004; Wilson 2007).
Banding programs are an important part of waterfowl conservation in North
America (Blohm 2006, Haukos 2015, Smith et al. 1989). Though waterfowl banding
efforts have been taking place since the early 20th century, it was not until 1994 and
1997 that extensive and standardized Mottled Duck banding programs were implemented
in Louisiana and Texas, respectively (Haukos 2015). Banding data is used to
observe movements, monitor harvest pressure and vulnerability for age classes, estimate
species recruitment, and estimate annual survival rates (Haukos 2015).
Due to mild weather conditions found within their range, the timing of Mottled
Duck breeding is highly variable. Nests have been documented as early as February,
with peak activity from March to May (Finger et al. 2003, Stutzenbaker 1988), and
renesting attempts through August (Stutzenbaker 1988). Grand (1992) discussed
the influences of weather conditions on Mottled Duck nest initiation. He noted
initiation delays in association with years of low autumn and winter precipitation.
Multiple studies (Durham 2001, Engling 1950, Grand 1992) have noted that in addition
to affecting initiation date, heavy rainfall events cause nest failures through
flooding. By monitoring rainfall and analyzing it in conjunction with banding data,
managers can determine the effects of precipitation on recruitment.
Considering these declines and influencing factors, the objectives for this project
were to (1) determine survival and recovery probabilities for Mottled Ducks banded
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T. McClinton, H.A. Mathewson, S.K. McDowell, and J.D. Hall
2019 Vol. 18, No. 1
on the J.D. Murphree Wildlife Management Area (WMA), using the best predicting
variables, and (2) examine the influence of rainfall and drought on Mottled Duck
reproductive success. We predicted that Mottled Duck recovery probabilities on the
property would be higher in hatch-year (HY) birds, but not significantly affected by
sex because the species is relatively monomorphic. We predicted that Mottled Duck
survival probabilities would be influenced by sex due to additional hazards faced
by females in nest incubation and brood rearing. We also hypothesized that years
of excessively high and excessively low rainfall totals during peak nesting season
would reduce recruitment. High rainfall results in flooding of nests, whereas low
rainfall results in drought conditions that could negatively impact brood survival.
Field-site Description
The focal point for our study was the J.D. Murphree WMA near Port Arthur,
TX. The WMA is ~9915 ha of fresh, intermediate, and brackish coastal marshes
that have long been an important wintering habitat for various species of waterfowl
and year-round habitat for Mottled Ducks. The J.D. Murphree WMA is located in
the Chenier Plain where Mottled Duck population densities along the western gulf
coast are the highest (Stutzenbaker 1988), and roughly 85% of all annual bandings
have occurred since the early 2000s (Haukos 2015). Some data used in this study
was also gathered from neighboring marshes, including the Anahuac and McFaddin
National Wildlife Refuges, and a few privately owned properties.
Methods
Data acquisition
We obtained banding data from the Texas Parks and Wildlife Department
(TPWD) gathered by the J.D. Murphree WMA staff from 2001 to 2016. Biologists
captured Mottled Ducks using rocket-nets (Dill and Thornsberry 1950), portable
swim-in traps (Szymczak and Corey 1976), and nightlight airboat captures (Stutzenbaker
1988) every summer from June to September. Nightlight capture was the
most successful method for catching birds. Due to the considerable amount of food
resources available during the summer, the large number of flightless molting adults
and juvenile birds have no need to utilize bait at trap and net sites. Upon capture,
biologists aged and sexed Mottled Ducks by observing morphological and cloacal
characteristics (Hochhaum 1942, Stutzenbaker 1988). They fitted birds with a
uniquely numbered United States Geological Survey (USGS) size-7 aluminum leg
band. After banding, they immediately released birds to minimize stress associated
with being captured. We obtained all recoveries from USGS Bird Banding Lab in
Laurel, MD, at the Patuxent Wildlife Research Center, using TPWD’s Master Banding
Permit for Mottled Ducks banded from 2001 to 2016. We included only healthy,
uninjured, wild-caught birds from banding surveys and dead recoveries obtained
from the USGS Bird Banding Lab. Since the waterfowl hunting season falls on 2
calendar years, we set each hunting season from the fall of the year it began until 15
February of the following year to allow for late band-reporting from hunters.
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We obtained daily rainfall data from the National Oceanic and Atmospheric
Administration’s (NOAA) Port Arthur City station (~5 km from the WMA) from
2001 to 2016. We obtained standardized precipitation–evapotranspiration index
(SPEI) data from a digital CSIC database (Vicente-Serrano et al. 2010) for the same
timeframe. SPEI data can be used to measure the intensity and duration of droughts
and how they vary over time, so we used this as an index of marsh condition while
Mottled Ducks were attempting to nest and rear broods.
Data analyses
We used the RMark package (Laake 2013) of R (Version 3.3.2, R Development
Core Team, Vienna, Austria), which is an interface for Program MARK (White and
Burnham 1999), to conduct survival and recovery analyses using the Brownie deadrecovery
approach (Brownie et al. 1985). We lacked data to support a live–dead
approach as we only had a total of 15 individuals recaptured outside of their banding
year. Variables considered for both analyses included year, sex (male, female),
and age class (hatch-year [HY], after-hatch-year [AHY]). The HY cohort includes
both HY birds (first-year bird capable of flight) and local birds (first-year bird incapable
of sustained flight) (Haukos 2015, Johnson et al. 1995). The AHY cohort
includes any bird of at least 1 year of age.
We used an information-theoretic approach for model selection (Burnham and
Anderson 2002). We evaluated support for models using Akaike’s information criterion
adjusted for small sample size (AICc). We derived a candidate set of 30 a priori
models to test specific biological hypotheses. Our candidate model set included
various additive and interactive combinations of the aforementioned variables, as
well as main effects, a null model, and a general model. We adjusted for overdispersion
using median ĉ (Cooch 2017). We considered models with ΔQAIC of less than 2
as competitive (Burnham and Anderson 2002). We used the top model to generate
estimates of annual survival and recovery and respective standard errors. We also
generated estimates by age class and sex.
To determine how rainfall affects recruitment through reproductive success, we
analyzed J.D. Murphree banding data in conjunction with rainfall data and SPEI
data. We used the proportion of HY birds banded relative to AHY birds banded as
an index of reproductive success (Peery et al. 2007). We tested correlations between
the proportion of HY birds and the total birds banded and banding days to rule out
any bias in our index with effort. We used linear regression and an information-theoretic
approach to evaluate candidate models representing our a priori predictions
about climatic influences on reproductive success. We determined support for a
model using the AICc. We identified competitive models as those models with a
ΔAICc of less than 2. We conducted these analyses in R (Version 3.3.2). Our prediction
is that reproductive success would be low when conditions are excessively dry and
excessively wet, resulting in a curvilinear relationship between some measure of
precipitation and reproductive success. Thus, we evaluated 9 models that included
the null model, and linear and curvilinear models that included 4 measures of precipitation:
(1) total rainfall during the nest season (March–July), (2) total rainfall
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2019 Vol. 18, No. 1
during the peak nesting season (March–May), (3) the number of significant rainfall
events during each peak nesting season, and (4) drought index during the nesting
season. We defined significant rainfall events as any event (day) in which the
measured rainfall was greater than the long-term average daily rainfall (1.32 centimeters
for 2001–2016 at our study location).
Results
For our survival and recovery analyses, we omitted 3 years (2001–2003) due to
small sample size (e.g., only 1 AHY bird was recovered in 2001) and 1 year (2016)
because recoveries from the 2016–2017 hunting season was not available at the
time of data acquisition (i.e., recoveries were truncated after the 2015–2016 hunting
season). Ultimately, we analyzed 4967 bandings and 705 recoveries (Table 1)
spanning 12 years (2004–2015). We adjusted for overdispersion using a correction
factor of 2.99 as determined by median ĉ. Model selection uncertainty resulted in
5 competitive models, all of which included various combinations of the age and
sex variables. The additive effect of bird age and sex best explained bird recovery
(Table 2); probability of recovery was greater for HY birds, and for males within
the age categories (Fig. 1). The main effect of sex was most influential on annual
survival (Table 2), and our estimate of annual survival was greatest for males
(0.628; Fig. 2). Using the additive effect of sex and age, survival is highest for AHY
males (0.637) and lowest for HY females (0.387), but there is overlap in standard
errors for all other age and sex categories (Fig. 3).
For our reproductive success analyses, we used the 16 years of banding data
acquired from TPWD. Since we were using proportions derived from banding data,
the lack of recoveries would have no effect on our results, thus there was no need
to subset. There was variation among years on the WMA in the number of birds
(HY and AHY; min–max =117–1068), the number of days banding (min–max =
9–45), and the proportion of HY to AHY (min–max = 0.33 to 0.97). Model selection
indicated that the null model outcompeted our predictive models (Table 3).
Table 1. Banding and recovery totals for Mottled Ducks in J.D. Murphree Wildlife Management Area
during years included in survival and recovery analyses. HY = hatch year, AHY = after hatch year.
Year HY banded AHY banded HY recovered AHY recovered
2004 282 103 49 9
2005 401 63 64 10
2006 441 121 60 18
2007 99 18 24 10
2008 157 178 29 17
2009 697 371 64 29
2010 662 140 65 18
2011 141 45 47 15
2012 155 46 26 14
2013 257 97 46 8
2014 129 49 31 8
2015 235 81 33 11
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Table 2. Model selection results for the top 12 Brownie-approach survival and recovery models of
Mottled Duck banded pre-hunting season from 2004 to 2015 at the J.D. Murphree Wildlife Management
Area in Texas. QAICc = Akaike’s information criterion with a correction for finite sample sizes
and over dispersion (median ĉ correction), ΔQAICc = change in QAICc relative to the model with the
smallest QAICc value, ω = model weight relative to the other models considered in this model set, K
= number of parameters, sex = male or female, age = AHY or HY, and t = year.
Model QAICc Δ QAICc ω K -2Log(L)
S(sex) f(age + sex) 1919.599 0.000 0.271 5 5710.427
S(age + sex) f(age + sex) 1920.417 0.818 0.180 6 5706.878
S(sex) f(age) 1920.644 1.045 0.161 4 5719.546
S(age + sex) f(age) 1921.525 1.926 0.104 5 5716.188
S(sex) f(age*sex) 1921.588 1.989 0.100 6 5710.381
S(age*sex) f(age + sex) 1921.659 2.060 0.097 7 5704.595
S(age*sex) f(age) 1923.351 3.753 0.042 6 5715.654
S(age) f(age + sex) 1924.750 5.152 0.021 5 5725.832
S(sex) f(age + t) 1926.505 6.907 0.009 15 5671.018
S(age + sex) f(sex) 1927.063 7.464 0.006 5 5732.748
S(age + sex) f(age + t) 1927.532 7.933 0.005 16 5668.069
S(sex) f(sex) 1929.603 10.005 0.002 4 5746.338
Figure 1. Mottled
Duck recovery
es t i -
mates (AHY
F: 0.046, AHY
M: 0.060, HY
F: 0.080, HY
M: 0.104) and
standard errors,
derived from
the best-fitting
model, by age
and sex class
from 2004 to
2015 at the J.D.
Murphree Wildlife
Management
Area in
Texas. AHY =
after hatch year,
H Y = h a t c h
year, F = female,
M = male.
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Table 3. Model selection results for precipitation variables influencing an index of reproductive success
(proportion of HY to AHY birds banded) of Mottled Ducks from 2001 to 2016 at the J.D. Murphree
Wildlife Management Area in Texas. AICc = Akaike’s information criterion with a correction
for finite sample sizes, ΔAICc = change in AICc relative to the model with the smallest AICc value,
ω = AICc model weight, K = number of parameters, Peak season rainfall = total rainfall during peak
nesting season (March–May), Season rainfall = total rainfall during nesting season (March–July),
Significant event = number of days when rainfall total was greater than the long-term daily average
(1.32 cm), and SPEI = standardized precipitation–evapotranspiration index.
Model AICc Δ AICc ω K -2Log(L)
Null -9.515 0.000 0.394 2 7.219
Peak season rainfall -7.972 1.543 0.182 3 7.986
Season rainfall -7.048 2.467 0.115 3 7.524
Significant event -6.686 2.829 0.096 3 7.343
SPEI index -6.510 3.005 0.088 3 7.255
Season rainfall non-linear -4.790 4.725 0.037 4 8.213
Significant event non-linear -4.649 4.865 0.035 4 8.143
Peak season rainfall non-linear -4.404 5.111 0.031 4 8.020
SPEI index non-linear -3.755 5.760 0.022 4 7.696
Figure 2. Mottled
Duck survival
estimates
(F: 0.473, M:
0.628) and
standard errors,
derived from
the best-fitting
model, by sex
class from 2004
to 2015 at the
J.D. Murphree
Wildlife Management
Area
in Texas. F =
female, and M
= male.
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The second competitive model suggested a linear, negative relationship between
reproductive success and peak nesting season rainfall (β = -0.0085), but the 95%
confidence interval overlapped zero (95% CI: -0.024, 0.007) suggesting uncertainty
in the direction of the effect.
Discussion
Our study supported our predictions that recovery primarily differed by age,
while survival primarily differed by sex. The influence of age on recovery is
potentially due to the fact that older birds have been exposed to hunting, so they
may be wiser to avoid suspicious bird congregations (i.e., decoy spreads), poor
or excessive calling, and heavily hunted areas all together. We predicted that
sex would not influence recovery because sexual dimorphism is less apparent in
Mottled Ducks than other species, so targeting of males by hunters may not be as
common. This targeting theory is supported in Johnson et al. (1992), where the
males of obviously sexual dimorphic species are said to be subjected to greater
hunting mortality. However, the slight influence of sex on recovery (Table 2) could
perhaps be indicative of an underlying ecological factor that makes males more
inclined to subject themselves to hunting danger. Survival was most influenced
Figure 3. Mottled
Duck survival
estimates
(AHY F: 0.495,
AHY M: 0.637,
HY F: 0.387,
HY M: 0.531)
and standard
e r r o r s , d e -
rived from the
second bestfitting
model,
by age and
sex class from
2004 –2015 at
the J.D. Murphree
Wildlife
Management
Area in Texas
AHY = after
hatch year, HY
= hatch year, F
= female, M =
male.
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by sex. This finding is likely due to the energetic costs and additional hazards that
hens are exposed to during nest care and brood rearing (Johnson et al. 1992) and is
commonly shown in studies comparing duck survival by sex (Franklin et al. 2002).
Additional life experience leading to better survival likelihood could explain the
moderate effect of age on survival (Table 2), and why Johnson et al. (1995) found
age class to be an influential factor on Mottled Duck survival i n Florida.
Our recovery estimates (Fig. 1) are similar the recovery rates exhibited in another
western Gulf Coast population study (Haukos 2015). In Johnson et al. (1995), the
authors found both AHY and HY male recovery probabilities that are comparable
to our work; however, they found AHY and HY female recovery probabilities that
are significantly lower than our estimates. Nichols et al. (1987) found relatively
similar recovery probabilities in Mallards and American Black Ducks. However,
Bartzen and Dufour (2017) calculated Anas Acuta L. (Northern Pintail) recovery
probabilities that are significantly lower than our estimates. Our survival estimates
(Figs. 2, 3) are relatively similar to those found in previous studies of the western
Gulf Coast Mottled Duck population (Haukos 2015, Wilson et al. 2003) and other
common Mallard-like species (Nichols et al. 1987). However, Northern Pintail and
Anas Americana Gmelin (American Wigeon) exhibited higher estimates of survival
in Bartzen and Dufour (2017) and Lake et al. (2006), respectively. These findings
could potentially be attributed to the slow life-history strategies of these species
leading to more cautious behavior (Ackerman et al. 2006).
Our data did not support our hypothesis that low and high amounts of precipitation
influenced reproductive success as measured by our reproductive index.
Instead, there was a trend, although weak, suggesting a relationship between increased
rainfall during peak nesting season and increased reproductive success.
The lack of support for our hypothesis and for the linear trend could have been due
to the broad range of values in our data set, inadequacy of our precipitation measures
to capture the effects of precipitation, or bias in our reproductive index such
that the index did not represent reproductive success. Directly monitoring nesting
success and water levels would provide a more direct approach to addressing these
hypotheses; however, the time and effort required to accumulate this data set over
many years is often a limitation.
Haukos (2015) included data from the J.D. Murphree WMA in his analyses of
the Western Gulf Coast Population’s survival and recovery probabilities, but to our
knowledge, this study is the first to exclusively examine a long-term data set from
this area. So, this work provides estimates most indicative of the Mottled Ducks
on the J.D. Murphree WMA. That being said, the daily Mottled Duck movements
between the associated marshlands make these estimates plausible indices for all
of the upper Texas Coast. The comparison of our study results to those encompassing
larger regions (e.g., the western gulf coast) indicate that Mottled Ducks on the
J.D. Murphree WMA and surrounding areas are potentially representative of other
populations. However, declaring our results to be anything more than an index or
representation of larger scale populations would be extrapolating beyond the scope
of our study area.
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Also, to our knowledge, this is the first study to model the proportion of HY birds
banded as an index of reproductive success against various measure of precipitation
to predict recruitment in Mottled Ducks. Though we did not find a suitable model,
we provided an avenue for future works to explore different precipitation measures
or other indices of reproductive success. Upon finding a suitable variable and index
combination, the J.D. Murphree WMA managers will be able to determine yearly
Mottled Duck reproductive success and trends more precisely than current monitoring
allows.
Acknowledgments
We thank Shaun Oldenburger, Master Bander with TPWD, for use of the banding data
collected under his permit. We thank Michael Rezsutek, the TPWD Waterfowl Program, and
the many TPWD biologists, fish and wildlife technicians, and interns who spent countless
hours in the field collecting data. We thank Brendan Shirkey of the Winous Point Marsh
Conservancy, for his advice and guidance with manuscript composition. Lastly, we thank
Tarleton State University, Tarleton State University’s College of Agriculture and Environmental
Sciences, and the Department of Wildlife, Sustainability, and Ecosystem Sciences
for funding conference travel throughout this research process.
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