Embed Size (px)
Citation preview
ECOLOGY AND POPULATION GENETICS OF MOTTLED DUCKS WITHIN
THE SOUTH ATLANTIC COASTAL ZONE
by
GUO-JING WENG
(Under the Direction of Sara H. Schweitzer)
ABSTRACT
The mottled duck (Anas fulvigula maculosa) is a non-migratory waterfowl species native to
Texas and Louisiana. The subspecies, A. f. fulvigula, is endemic to Florida. About 1,200 mottled
ducks were introduced to the Santee River Delta and the ACE (Ashepoo, Combahee, and Edisto
Rivers) Basin of South Carolina during 1975-82 from their native habitats for hunting
opportunities. Impacts of translocation and establishment of mottled ducks on the introduced
population per se, on other native species, and on ecosystem processes were not considered. I
collected harvest data and survey data to evaluate the change in abundance and distribution of
mottled ducks along the South Atlantic Coastal Zone (SACZ). Abundance of mottled ducks in
South Carolina has increased since the end of the introduction. Distribution of mottled ducks
expanded southward and two new breeding populations were established by the introduced birds
in Savannah, South Carolina and Rhetts Island, Altamaha Wildlife Management Area (WMA) in
Georgia. I studied factors affecting habitat use by mottled ducks at Bear Island WMA. Water
depth, submerged vegetation, and aquatic invertebrates were measured at locations used and not
used by mottled ducks. Water depth was the only factor associated with habitat use by mottled
ducks and they seldom used water deeper than 25 cm. I used nine microsatellite DNA loci to
analyze 807 mottled ducks collected from South Carolina, Georgia, Florida, Louisiana, and
Texas. The genetic data showed a clear hierarchical population structure reflecting the
geographic relationship of mottled ducks along the SACZ. The two subspecies of mottled ducks
were separated in a cluster analysis using the genetic data except that mottled ducks from Guana
River WMA in Florida were in the cluster of Texas-Louisiana subspecies. Gene flow from the
introduced birds to native populations in Florida was revealed by the population structure,
smaller genetic distance between Georgia and Florida populations than that among native
populations, negative correlation between genetic and geographic distances, and private alleles
found in Guana River population. Management practices for mottled ducks may seek to control
this directional gene flow.
INDEX WORDS: Mottled ducks, Anas fulvigula, Habitat, Microsatellites, Population structure,
Gene flow, South Carolina, Georgia
ECOLOGY AND POPULATION GENEITCS OF MOTTLED DUCKS WITHIN
THE SOUTH ATLANTIC COASTAL ZONE
by
GUO-JING WENG
B.S., National Taiwan University, Taiwan, 1994
M.S., National Taiwan University, Taiwan, 1997
M.S., University of Georgia, 2006
A Dissertation Submitted to the Graduate Faculty of the University of Georgia in Partial
Fulfillment of the Requirements for the Degree
DOCTOR OF PHILOSOPHY
ATHENS, GEORGIA
2006
© 2006
Guo-Jing Weng
All Rights Reserved
ECOLOGY AND POPULATION GENETICS OF MOTTLED DUCKS WITHIN
THE SOUTH ATLANTIC COASTAL ZONE
by
GUO-JING WENG
Major Professor: Sara H. Schweitzer
Committee: Darold P. Batzer Campbell Joseph Nairn James L. Shelton
Electronic Version Approved: Maureen Grasso Dean of the Graduate School The University of Georgia December 2006
ACKNOWLEDGEMENTS
This research was funded by the Georgia Department of Natural Resources, Delta
Waterfowl Foundation, Georgia Waterfowl Association, Wildlife Forever, and Georgia
Ornithological Society. I thank the University of Georgia, Daniel B. Warnell School of Forestry
and Natural Resources for assistantship funds. Additional funds for travel and meetings were
from the Graduate School at the University of Georgia.
I thank my advisor, Dr. Sara Schweitzer, for this opportunity to work with her on this
project and her instruction and support. I also thank Drs. Joseph C. Nairn, Darold P. Batzer, and
James L. Shelton for their guidance on this project and thorough review of this dissertation.
Brant Faircloth designed primer sets for this research and taught me all the necessary lab
techniques. Dr. John Carroll allowed me to work in his lab. I especially thank Mr. Phil
“Rosebud” Hale who spent tremendous amount of time helping me in the field and provided a
cordial friendship.
I am grateful to people who provided me duck samples, survey data, field assistance, and
information about the study sites. They are Diane Eggeman, Joe Benedict, Jamie Feddersen,
Justin Ellenberger, Ron Bielefeld, and Matthew Hortman from Florida Fish and Wildlife
Conservation Commission, Jeb Linscombe, Steven Reagan, and James Harris from Louisiana
Department of Wildlife and Fisheries, Patrick Walther from U.S. Fish and Wildlife Service,
McFaddin National Wildlife Refuge in Texas, Derrell Shipes, Walt Rhodes, Dean Harrigal,
Felicia Sanders, and Jim Westerhold from South Carolina Department of Natural Resources,
Russ Webb from U.S. Fish and Wildlife Service, Savannah National Wildlife Refuge in South
iv
Carolina, David Griffin from the Department of Transportation in Georgia, and James Steve
Calver from the U.S. Army Corps of Engineers. Carmen Martin and Greg Balkcom from
Georgia Department of Natural Resources joined this project from the beginning, assisted me in
the field, provided me survey data, and let me join the survey flight over Rhetts Island, Altamaha
Wildlife Management Area in Georgia. I also thank staff in the Warnell School of Forestry and
Natural Resources for their assistance in the graduate program.
v
TABLE OF CONTENTS
Page
ACKNOWLEDGEMENTS........................................................................................................... iv
LIST OF TABLES......................................................................................................................... ix
LIST OF FIGURES .........................................................................................................................x
CHAPTER
1 INTRODUCTION AND LITERATURE REVIEW ...........................................................1
Introduction......................................................................................................................1
Literature Review.............................................................................................................4
2 CHANGES IN ABUNDANCE AND DISTRIBUTION OF MOTTLED DUCKS
WITHIN THE SOUTH ATLANTIC COASTAL ZONE ..............................................10
Introduction....................................................................................................................10
Study Areas....................................................................................................................12
Methods..........................................................................................................................13
Results............................................................................................................................13
Discussion......................................................................................................................15
3 HABITAT USE OF MOTTLED DUCKS AT THE BEAR ISLAND WILDLIFE
MANAGEMENT AREA ...............................................................................................23
Introduction....................................................................................................................23
Methods..........................................................................................................................25
Results............................................................................................................................28
vi
Discussion......................................................................................................................29
4 POPULATION STRUCTURE AND GENE FLOW OF MOTTLED DUCKS WITHIN
THE SOUTH ATLANTIC COASTAL ZONE..............................................................38
Introduction....................................................................................................................38
Methods..........................................................................................................................41
Results............................................................................................................................49
Discussion......................................................................................................................53
5 CONCLUSIONS................................................................................................................81
LITERATURE CITED ..................................................................................................................84
vii
LIST OF TABLES
Page
Chapter 3
3.1 Density of aquatic invertebrates and fish in locations used and unused by
mottled ducks at Bear Island Wildlife Management Area, South Carolina,
June-July 2003 ..................................................................................................................34
Chapter 4
4.1 Mottled duck sample sources, seasons, and sample sizes from South
Carolina, Georgia, Louisiana, Texas, and Florida during 2001-05 ..................................65
4.2 Sequences and motifs of the nine primer sets used for the final genotyping
of mottled ducks ...............................................................................................................66
4.3 Descriptive statistics for each locus across 10 newly defined mottled duck
populations........................................................................................................................67
4.4 P-values for the Hardy-Winberg Equilibrium (HWE) test for each locus
and sample ........................................................................................................................68
4.5 Ten newly defined mottled duck populations and samples combined .............................69
4.6 Pair-wise FST (above diagonal) and p-values for G-based test (below
diagonal) for the 10 newly defined populations ...............................................................70
4.7 Genetic characteristics of microsatellite loci in ten mottled duck
populations........................................................................................................................71
4.8 Partition of the total genetic variance of mottled duck populations .................................72
viii
4.9 Results of tests of bottleneck events in mottled duck populations ...................................73
4.10Estimated number of migrants per generation between each pair of mottled
duck populations...............................................................................................................74
ix
LIST OF FIGURES
Page
Chapter 2
2.1 Locations from which aerial survey and harvest data were collected on
mottled ducks ..................................................................................................................19
2.2 Number of mottled ducks harvested per 100 hunters in four wildlife
management areas ...........................................................................................................20
2.3 Harvest data for mottled ducks from Guana River WMA...............................................21
2.4 Recovery locations of mottled ducks banded in Florida..................................................22
Chapter 3
3.1 Frequencies of mottled ducks observed at 10 of 25 impoundments at Bear
Island Wildlife Management Area, South Carolina, June-July 2003 ..............................35
3.2 Frequencies of behaviors exhibited by mottled ducks at Bear Island
Wildlife Management Area, South Carolina, June-July 2003 .........................................36
3.3 Frequencies of distance to nearest vegetation from mottled ducks at Bear
Island Wildlife Management Area, South Carolina, June-July 2003 ..............................37
Chapter 4
4.1 Locations from which samples of mottled ducks were obtained, 2001-
2005, for genetic analysis ................................................................................................75
x
4.2 Population structure of the 10 newly defined mottled duck populations.
The structure was established using Reynold’s (1983) genetic distance and
UPGMA algorithm...........................................................................................................76
4.3 Population structure of the 10 newly defined mottled duck populations
established by using Reynold’s (1983) genetic distance and Neighbor-
Joining algorithm .............................................................................................................77
4.4 Log10(number of migrants) plotted against log10(geographic distance) for
the five mottled duck populations (SCR, Bear, Rhetts, Orange, and Guana)
along South Atlantic Coastal Zone ..................................................................................78
4.5 Allelic pattern across 10 newly defined mottled duck populations in South
Carolina, Georgia, Florida, Louisiana, and Texas ...........................................................79
4.6 Average assignment index correction (AIc) for sex and age categories of
mottled ducks in Florida, Louisiana, and Texas ..............................................................80
xi
CHAPTER 1
INTRODUCTION AND LITERATURE REVIEW
INTRODUCTION
Translocation is broadly defined as moving a living organism from one area and releasing it
freely in another (IUCN 2006). Translocations can be a conservation strategy that increases
genetic diversity of small populations (Griffith et al. 1989, Newman and Tallmon 2001),
establishes satellite populations to reduce the risk of extinction (Goodman 1987), or re-
establishes or augments wild populations (Kleiman et al. 1991). However, most motivations to
translocate animals have been based on human needs. Griffith et al. (1989) found that among 93
species of birds and mammals translocated between 1973 and 1986, 90% were game species and
only 7% were threatened, endangered, or sensitive species.
Mottled ducks (Anas fulvigula) were introduced to the Santee River Delta and the ACE
(Ashepoo, Combahee, and Edisto Rivers) Basin of South Carolina from Texas, Louisiana, and
Florida during 1975 and 1982 (T. Strange, South Carolina Department of Natural Resources, pers.
comm.). The introduction was driven by the desire to increase hunting opportunities in South
Carolina. Impacts of translocation and establishment of mottled ducks on the introduced
population per se, on other native species, and on ecosystem processes were not considered.
This was not uncommon in the 1970s and 1980s because 73% of wildlife agencies surveyed by
Griffith et al. (1987) did not specify any monitoring or evaluation protocols.
Without careful evaluation of possible impacts, translocation may damage the ecosystem,
native species, or translocated species. Alien species could introduce diseases or parasites to the
1
new ecosystem (Dobson and May 1986, Szabo 2003), alter the habitat (Danell 1979, Jackson
1988, Moore et al. 1999), out compete native species (Moyle 1973), or suffer from increased
mortality due to disease after translocation (Nolet et al. 1997). Stress from translocation could
induce abnormal behaviors displayed by released individuals (Fitch and Shirer 1971, Reinert
1991). Although translocation is a conservation strategy to bring about human-induced gene
flow and enhance genetic diversity of small populations, it also breaks down the genetic isolation
among species, interferes with the dynamics of ecosystems, and causes extinction of species.
Genetic isolation has been essential for the evolution and maintenance of the diversity of plants
and animals composing the biological wealth of our planet (IUCN 2006). A well-known
example is the Ibex (Capra ibex ibex) that was re-introduced to Czechoslovakia from Austria,
Turkey, and Sinai. Fertile hybrids produced offspring in winter and the population eventually
went extinct (Greig 1979). Such an unfortunate outcome resulted from a conservation-oriented
translocation. For those translocations motivated by human benefits without thorough
consideration, unexpected negative effects are likely to happen.
A translocation is defined as successful when the translocated population is self-sustainable
(Griffith et al. 1989). Foose (1991) listed genetic and demographic objectives of a conservation
program to establish a self-sustainable population: 1) the probability of survival of the population;
2) the kinds and amounts of genetic diversity to be preserved; and 3) the period of time over
which this genetic diversity and survival probability are to be maintained. To prevent potential
damage caused by misused translocations, the IUCN (2006) suggested special attention should
be paid before conducting a translocation. Some specific considerations are: 1) the probability of
the alien species increasing in number, 2) the probability that the alien species will spread
2
beyond the habitat into which it will be introduced and the species’ mode of dispersal, and 3) the
capacity of the species to reduce native species by interbreeding with them.
The above questions are not easy to answer before a species is actually translocated.
However, the mottled ducks introduced to South Carolina provide an excellent opportunity for us
to investigate and answer the questions. Our data collected from hunters’ harvests and monthly
aerial surveys by Georgia Department of Natural Resources (DNR) from 2002-2005, identified a
resident population on Rhetts Island, about 64 km north of the border between Georgia and
Florida. This southward expansion of the mottled duck population from South Carolina to
Georgia is a great concern to ornithologists because of efforts to maintain the Florida mottled
duck as a distinct population (Florida Fish and Wildlife Conservation Commission 2006a).
Although gene flow was not detected between Florida and Texas/Louisiana populations of
mottled ducks by using mitochondrial DNA (McCracken et al. 2001), the South
Carolina/Georgia populations are geographically near Florida and gene flow may occurr.
Shortly after the introduction, a banded individual from the birds released in South Carolina was
found in Florida (U.S. Geological Survey, Biological Resources Division, Patuxent Wildlife
Research Center, Laurel, Maryland, cited in McCracken et al. 2001). Based on these
observations, it is possible that the introduction of mottled ducks in the South Atlantic Coastal
Zone (SACZ) has broken the isolation of the Florida mottled duck population.
This project aimed to answer questions that could not be evaluated before the introduction
of mottled ducks. Specifically,
1) How the abundance and distribution of mottled ducks released in South Carolina changed
over the past 30 years,
3
2) How mottled ducks use habitats in the SACZ and the critical factors that determine their
habitat use, and
3) How mottled ducks in SACZ are structured genetically, their genetic composition compared
with source populations, and the possibility of gene flow between Florida and GA-SC
populations.
Overall, this project aimed to understand how an introduced waterfowl species changed in
abundance and distribution, its genetic structure and demography, and its impacts on the genetics
of closely related species and themselves. Subsequent to this research the goal was to provide
suggestions for management practices for the introduced and native mottled duck populations.
LITERATURE REVIEW
Classification
The mottled duck (Anas fulvigula maculosa) is regarded as one of more than 20 kinds of
mallards worldwide (Scott 1972, Palmer 1976). Five other North American mallards are the
Florida duck (A. f. fulvigula), the Mexican duck (A. f. diazi), the mallard (A. platyrhynchos), and
the black duck (A. rubripes). The classification status of mottled ducks in North America has
long been a debate among ornithologists. The Florida mottled duck was first described by
Ridgway (1874) and was considered a subspecies of the black duck (Anas obscura, currently
Anas rubripes). It later was designated as a full species, Anas fulvigula (Ridgway 1878 as cited
in Johnsgard 1961). The mottled duck in Texas was first found by Sennett (1889) at Corpus
Christi Bay near Padre Island in 1882 and was considered a new species, Anas maculosa. The
mottled duck was added to the American Ornithologists’ Union (AOU) Check-list in 1890 as
Anas fulvigula maculosa (Johnsgard 1961). There were some arguments about the classification
status of mottled ducks and the Florida mottled duck in 1920s-1930s (Johnsgard 1961). Bellrose
4
(1980) considered the mottled duck and Florida duck as two subspecies, A. f. maculosa and A. f.
fulvigula, respectively, and Florida Fish and Wildlife Conservation Commission (2006a) also
considers the Florida duck a unique subspecies in a conservation plan for the population. But
current AOU Check-list recognizes only one species (Anas fulvigula) for mottled ducks.
Moorman and Gray (1994) did not separate the species either.
Description
Both the Florida duck and mottled duck are non-migratory, different from other mallard
species. Morphology of the Florida duck is so similar to that of the mottled duck that they can
hardly be identified at a distance. According to Bellrose (1980), both subspecies are darker than
the hen mallard, but the mottled duck has darker plumage and darker streaking on the checks and
neck than the Florida duck. The speculum of both subspecies is green but the mottled ducks’ is
more bluish. The speculum is not bordered by white as it is in the mallards, but sometimes a
narrow white bar occurs at the trailing edge of the speculum of both subspecies. Both sexes have
a mottled dark brown body plumage and females have orange bills with black spots across the
saddle. Male mottled ducks have olive-green bills but male Florida ducks have bright yellow
bills with a black spot at the base (Bellrose 1980).
Distribution and Abundance
Annual, systematic population surveys are only conducted in Florida. These survey data
and other studies (Zwank et al. 1989, Neaville 1993, cited in Moorman and Gray 1994) reveal
that populations may fluctuate widely in response, primarily, to drought conditions. The mottled
duck population may be stable or declining within its range, but systematic population data are
not available.
5
Florida ducks are endemic to the Florida peninsula (Gray 1993). Most Florida ducks occur
on prairies near Lake Okeechobee, St. Johns River and Everglades Agricultural Area (Johnson et
al. 1991). Florida ducks use freshwater emergent wetlands, ditches, wet prairies, and seasonally
flooded marshes associated with major rivers, and Everglades Agricultural Area (Lotter 1969,
Johnson et al. 1991), and also inhabit mosquito control impoundments in coastal areas such as
Tampa Bay, Charlotte Harbor, and the Mosquito and Indian River Lagoons (Stieglitz and Wilson
1968, LaHart and Cornwell 1969, Breininger and Smith 1990). Ditches is also an important
habitat for Florida duck (Johnson et al. 1991). Florida ducks select water <15 cm deep and
inhabit the same locations and environments year-round, but they move to more permanent
wetlands during remigial molt or during the winter dry season (Fogarty and LaHart 1971,
Johnson 1973, Johnson et al. 1991, Gray 1993). Lotter (1969) believed that Florida ducks
moved to coastal areas in response to dry conditions in the prairies.
The range of mottled duck begins at the Laguna de Tamiahua south of Tampico, Mexico,
and extends north along the Gulf Coast into Hancock and Jackson counties, Mississippi. The
range extends inland about 161 km (100 miles) along the middle Texas Coast and 80 km (50
miles) in southwest Louisiana (Stutzenbaker 1988).
Habitat Use
Mottled ducks frequently use non-tidal, fresh to brackish ponds of coastal marshes, and
agricultural areas adjacent to coastal freshwater marshes (Grand 1988 as cited in Moorman and
Gray 1994; Zwank et al. 1989). In coastal Louisiana and southeastern Texas, greatest densities
of mottled ducks are found in fresh and intermediate marshes (Paulus 1988). Brackish marsh
with irregular ponds supports the highest mottled duck breeding and wintering densities
(Stutzenbaker 1988).
6
Mottled ducks are usually found in shallow water (1-30 cm) areas near shorelines with
abundant vegetation including grasses (Paspalum spp., Panicum spp.), bulrush (Scirpus
californicus), rice cutgrass (Leersia hexandra), and bulltongue (Sagitaria lancifolia) (White and
James 1978). In Louisiana, mottled ducks rarely used habitats where water depth exceeded 15
cm (Paulus 1984). From late August to early October, large postbreeding concentrations may
occur coincident with harvest of rice fields in Louisiana and Texas (Stutzenbaker 1988). Similar
to Florida ducks, movement to coastal areas in response to dry conditions has been reported for
mottled ducks (Stutzenbaker 1988).
Genetic Studies and Hybridization
McCracken et al. (2001) analyzed 5’ control region sequences from the mitochondrial DNA
of 219 mottled ducks, 4 Mexican ducks, 13 American black ducks, and 10 mallards. They
constructed a neighbor-joining tree to reveal the phylogenetic relationships of the ducks. They
delineated two major clades on the tree. One clade was composed of two groups of haplotypes;
one was composed of 48.9% mottled ducks from Texas and Louisiana and two mallards, and the
other was composed of 72.7% mottled ducks from Florida only. Another clade was composed of
all the remaining ducks without clear geographic or species-specific patterns. The authors made
two conflicting conclusions relative to the two clades. For the clade with clear geographic
structure, they concluded that gene flow was not happening or it was undetectable across the
central Gulf Coast. For the intermingled clade, they interpreted that the clade may result from
hybridization across species or incomplete lineage sorting from a polymorphic ancestral gene
pool.
Williams et al. (2005) compared allozyme and microsatellite variation of mottled duck
populations in Florida and Texas and found overall significant differentiation between the two
7
populations. Heterozygosity and allelic diversity for allozymes were lower in the Florida
population, but those for microsatellites were similar in the two populations. The number of
migrants between the two populations was estimated to be 2.2 (microsatellite) or 1.1 (allozyme)
per generation and only 5-6 % of the variation was partitioned between populations. They
suggested that the results indicated limited gene flow between the two populations and the two
populations should be managed separately.
For the Florida mottled duck population, Williams et al. (2002) did not find significant
genetic differentiation among local populations in a microsatellite study. They suggested that
short range adult dispersal and a lack of natal philopatry may explain the limited population
differentiation.
Williams et al. (2005) found asymmetric hybridization between mottled ducks and mallards
in Florida. Their results estimated that about 11% of mottled ducks and 3.4% of mallards were
hybrids. They were not able to distinguish mallards and mottled ducks from a South Carolina
sample, indicating severe hybridization or simply a result of low sample size (n = 24 for mottled
ducks, n = 33 for mallards), number of loci (n = 5), and heterozygosity (He = 0.52 for mottled
ducks, He = 0.60 for mallards).
The introduction of mottled ducks to South Carolina was motivated by increasing hunting
opportunities. It is important both to conservation and recreation to formulate a sound
management practice for game species. Especially when managing a localized and non-
migratory species, regional differences due to the heterogeneity among habitats should be taken
into account because region-specific situations may call for different management approaches.
However, since the introduction of mottled ducks to South Carolina in the 1970s, there has been
no study on this newly established mottled duck population. This project aimed to investigate
8
how this alien species has reacted to its new environment by estimating their abundance,
distribution, and habitat use. Also, hybridization between the two subspecies of mottled ducks is
likely to happen because the introduction of mottled ducks to South Carolina has reduced the
geographic gap between the Gulf Coast and Atlantic populations. Therefore, this project also
aimed to detect possible gene flow between mottled duck populations in Georgia-South Carolina
and Florida. The new information generated from this project will provide specific suggestions
for the management of the new mottled duck population in the South Atlantic Coastal Zone.
9
CHAPTER 2
CHANGES IN ABUNDANCE AND DISTRIBUTION OF MOTTLED DUCKS WITHIN THE
SOUTH ATLANTIC COASTAL ZONE
INTRODUCTION
Mottled ducks (Anas fulvigula) are endemic to the Gulf Coast marshes of Texas and
Louisiana, and freshwater marshes of Florida (Moorman and Gray 1994). They are one of few
North American dabbling ducks that do not migrate (Bellrose 1980). The Florida mottled duck
(A. f. fulvigula) is considered a sub-species. Almost 1,200 mottled ducks from Texas, Louisiana,
and Florida were introduced to the Santee River Delta and the ACE (Ashepoo, Combahee, and
Edisto Rivers) Basin of South Carolina 1975-1982, mostly to increase hunting opportunities (T.
Strange, South Carolina Department of Natural Resources [DNR], unpublished data). The
impacts of introducing mottled ducks on ecosystem processes, other duck species, and the
introduced population per se were not considered.
Two potential impacts of these introductions could include: 1) Dispersal from sites
where the species was introduced, and 2) an increase in abundance such that the population
negatively influences the environment, especially to the biotic community into which it was
introduced (IUCN 2006). Potential negative impacts are difficult to predict before an
introduction. The introduction of mottled ducks to the South Atlantic Coastal Zone (SACZ)
provides a good opportunity to understand how non-migratory waterfowl might disperse beyond
release sites.
10
The establishment of introduced species breaks down the genetic isolation of
communities of co-evolving species of plants and animals. Such isolation has been essential for
the evolution and maintenance of the diversity of plants and animals composing the biological
wealth of our planet (IUCN 2006). The introduction, establishment, and dispersal of mottled
ducks in the SACZ may have broken the isolation of the Florida mottled duck population.
Although there is no gene flow between Florida and Texas-Louisiana populations of mottled
ducks (McCracken et al. 2001), a banded individual from birds released in South Carolina was
found in Florida (U.S. Geological Survey, Biological Resources Division, Patuxent Wildlife
Research Center, Laurel, Maryland, cited in McCracken et al. 2001), thus the possibility of
southward dispersal exists. Such southward dispersal of mottled ducks concerns ornithologists
because of the desire to maintain the Florida mottled duck as a distinct population (Florida Fish
and Wildlife Conservation Commission 2006a).
Information on changes in mottled ducks’ abundance and distribution in the SACZ has
not been collected systematically, but this information is important for the management of
mottled ducks and conservation of native species. The only possible sources of this information
are survey and harvest data from state wildlife agencies. Survey data may not be reliable due to
inconsistent survey methods, different observers, different survey areas, irregular survey
frequencies, and unknown precision of estimates and detectability of birds (R. Kaminski,
Mississippi State University, pers. comm.). Harvest data might not be directly related to the
overall abundance of mottled ducks in South Carolina due to redistribution of birds caused by
weather events or changes in habitat availability (R. Kaminski, Mississippi State University, pers.
comm.). However, harvest data have their merit in that data were collected at same locations and
seasons, bird species were examined in hand, and numbers of birds and hunters were recorded
11
precisely. After standardization, harvest data can reflect a change in abundance of mottled ducks
at certain wildlife management areas. The objective of this research was to evaluate the change
in abundance and distribution of mottled ducks released in South Carolina over the past 30 years.
STUDY AREAS
Harvest data were collected from Samworth, Santee Coastal Reserve, Santee Delta,
Hatchery, Sandy Beach, Donnelley, and Bear Island WMAs in South Carolina and Guana River
WMA in Florida (Fig. 2.1).
Altamaha WMA was a 11,857-ha managed marsh complex in McIntosh County, Georgia.
The WMA included 3 management units consisting of Butler Island, Champney Island, and
Rhetts Island. Butler and Champney Islands were tidal, freshwater areas that were drained
seasonally and managed as moist soil impoundments for migratory and wintering waterfowl.
Rhetts Island was a tidal, fresh to brackish site with three diked impoundments in the Altamaha
River Delta.
Bear Island WMA was part of the ACE Basin, located within the estuary of the Ashepoo
River, South Carolina, and was owned and operated by South Carolina DNR. The WMA was
partitioned into three units: East, West, and Springfield marsh. The brackish marsh area was
managed to provide quality habitat for wintering waterfowl and other wetland wildlife.
Santee Delta was about 24 km south of Georgetown, South Carolina, and composed of
managed brackish wetland impoundments and unmanaged tidal freshwater, brackish, and salt
marsh. Santee Coastal Reserve, located on the south side of Santee Delta, was composed of
managed brackish impoundments and surrounding tidal wetlands.
The Guana River WMA was a coastal barrier beach and a sea island located about 66 km
south of the border of Georgia and Florida. The land was privately owned and open to the public
12
for hunting before being purchased by the State of Florida in 1984. Upstream marshes were
dammed in 1957 to enhance wintering waterfowl habitat, resulting in the current Guana Lake.
The lake water was brackish near its south end and a freshwater reservoir to north.
METHODS
WMA harvest data, including number of hunters and mottled ducks harvested, were
available only from South Carolina (Strange 1979-2003) and Guana River WMA (M. Hortman,
Florida Fish and Wildlife Conservation Commission [FL FWCC], unpublished data). Harvest
data were collected at each WMA by SC DNR or FL FWCC managers at check stations.
Abundance information derived from harvest data was expressed as number of mottled ducks
harvested per 100 hunters to standardize the data and was defined as “harvest per unit effort”
(HPUE). For Guana River WMA, harvest data were not available before 1984 and in 1993 and
1994. For all WMAs in South Carolina, although harvest data were available after 2001, the
number of hunters was unknown in 1999 and after 2001. Therefore, harvest data for these years
were not analyzed. Springfield marsh was incorporated into the Bear Island hunting program in
the 1994-1995 waterfowl season, and harvests were recorded separately from other areas in Bear
Island WMA. The Wilcoxon 2-sample test (Sokal and Rohlf 1995) was used to test pair-wise
HPUE between WMAs or two periods of time to release the assumption of normality and
requirement of a large sample size. The overall harvest trend in South Carolina was tested using
regression. All statistical analyses were conducted using SAS/STAT software Version 9 for
Windows (SAS Institute Inc., Cary, NC, USA).
RESULTS
Since their introduction in 1975, mottled ducks have been harvested from eight WMAs in
South Carolina. Mottled ducks were harvested rarely in Donnelley (1992, 1994, 1996, and 1997),
13
Hatchery (1991), Sandy Beach (2001), and Samworth (1989-1991 and 1993) WMAs. In other
WMAs, mottled ducks have been harvested almost every year since 1978 (Fig. 2.2).
In Santee Delta, HPUE remained low (average = 1.78, SE = 1.69) since the 1970s (Fig.
2.2). HPUE in Santee Coastal Reserve (average = 1.11, SE = 1.62) and Bear Island (average =
0.78, SE = 0.68) were both low during 1978-1987. Since 1988, HPUE has significantly (p <
0.001, Wilcoxon 2-sample test) increased in both Santee Coastal Reserve (average = 9.85, SE =
4.51) and Bear Island (average = 9.22, SE = 3.52), and the value was higher than that for Santee
Delta in any year (Fig. 2.2). At Springfield marsh, HPUE for 1997 (5.68) and 1998 (1.30) were
lower than those for Santee Coastal Reserve (9.74 and 6.34, respectively) and Bear Island WMA
(9.12 and 9.72, respectively), but the HPUE at Springfield marsh increased in 2000 (22.00) and
2001 (41.43) and was the greatest among all WMAs (Fig. 2.2). When all WMAs were
considered, average HPUE in South Carolina has increased from the introduction years to 2001
in a nonlinear manner. The fitted quadratic regression line was significant (p = 0.0001) (Fig. 2.2).
In addition to the above locations, breeding populations of mottled ducks have been
observed since 1997 at Savannah NWR (R. Webb, USFWS Savannah Coastal Refuge, Savannah,
Georgia, pers. comm.) and since 2001 at Savannah Confined Disposal Facilities (G.-J. Weng,
pers. obs.), both about 65 km south of the ACE Basin and 85 km north of the Rhetts Island.
Monthly aerial surveys conducted by the Georgia DNR from 2002-2005 also identified a resident
population of mottled ducks on Rhetts Island, Altamaha WMA, about 64 km north of the border
of Georgia and Florida (Fig. 2.1).
In Guana River WMA, mottled ducks were harvested rarely before 1995. From 1995-
2001, mottled ducks were harvested every year in Guana River WMA, but the HPUE (average =
2.54, SE = 1.07) was much lower than that in Bear Island (average = 10.94, SE = 3.85), Santee
14
Coastal Reserve (average = 10.20, SE = 3.06), and Springfield WMAs (average = 17.60, SE =
18.21) in South Carolina (Fig. 2.3). From 2002-2005, average HPUE was 2.62 in Guana River
WMA (SE = 0.73), but data are not available from other WMAs.
DISCUSSION
Abundance of mottled ducks reflected in harvest data indicated that the mottled duck in
South Carolina has increased in several WMAs since their introduction. The small bag limit
(one duck per hunter) may reduce the ability to detect the changes in mottled duck abundance
evaluated from harvest data, but some differences among WMAs and apparent increase in
harvest were found. Although Santee Delta and Santee Coastal Reserve were less than 1 km
apart and were on either side of the Santee River, more mottled ducks were harvested in Santee
Coastal Reserve than Santee Delta WMA. In the ACE Basin region, Bear Island WMA was the
only location where mottled ducks were harvested annually. In Springfield marsh, a unit of Bear
Island WMA, harvests quickly increased and were higher than any other WMA in recent years.
These differences indicated that mottled duck distribution was not homogeneous over time and
space. Despite the differences among WMAs, average HPUE from 1978-2001 indicated an
increase in mottled duck abundance in these WMAs.
Mottled ducks have been found at several locations outside the release sites. Apparent
southward expansion of their distribution was revealed by breeding populations of mottled ducks
at Savannah NWR, Savannah CDFs, and Rhetts Island in Altamaha WMA. Although systematic
harvest data were not available from Rhetts Island, mottled ducks have been harvested there
since 2000. Rhetts Island was the southern-most breeding population established by mottled
ducks released in South Carolina. These populations were not established by mottled ducks from
Florida because their distribution has confined to Florida since they were first described by
15
Ridgway (1874). There is no documentation of mottled ducks in Georgia and South Carolina
before they were introduced to South Carolina.
Mottled ducks were also found north and west of the release sites by occasional harvests.
Samworth WMA was the northernmost location (about 36 km north of Santee Coastal Reserve)
where mottled ducks were harvested. Westward movement of mottled ducks was found at Sandy
Beach WMA and Hatchery WMA (both about 80 km from the coast or Santee Coastal Reserve),
and Donnelley WMA (about 20 km from the coast). However, this direction of movement was
rarely documented and these records were winter harvest data, not breeding populations.
Southward expansion was the most apparent movement of mottled ducks and new breeding
populations were established only within the coastal area south of release sites.
Although mottled ducks do not migrate for all practical purposes, relatively short
movements have been documented (Stieglitz and Wilson 1968, Lotter 1969, Stutzenbaker 1988).
Hyde (1958, as cited in Stieglitz and Wilson 1968) reported 13 recoveries of banded Florida
mottled ducks. Within an average time lapse of 6 months between banding and recovery,
mottled ducks moved from 0 to 208 km from the banding location with an average of 72 km.
Based on 105 band returns, Fogarty and LaHart (1971) found an average dispersal distance of 56
km, but 71.4% of the ducks were recovered within 78 km of the release sites. The only and the
longest dispersal outside of the normal range was 432 km (Fogarty and LaHart 1971). These
reports demonstrate a great potential of long distance dispersal by mottled ducks, and the current
distribution of mottled ducks in the SACZ could have been established in a short time after
mottled ducks were released. The distance between Rhetts Island, Altamaha WMA, and the
northern limit of the distribution of Florida mottled ducks is about 216 km, within the dispersal
limit of mottled ducks. Before mottled ducks were introduced in South Carolina, none were
16
reported north of Florida. Therefore Florida mottled ducks do not appear to naturally disperse
northward into Georgia. A fact overlooked by Fogarty and LaHart (1971) in their paper was that
82% of the ducks released from sites south of Lake Okeechobee dispersed northward and 66% of
the ducks released from sites north of Lake Okeechobee dispersed southward (Fig. 2.4). The
convergence of dispersed birds corresponds with the core breeding area in inland Florida (Florida
Fish and Wildlife Conservation Commission 2006b), in contrast to southward expansion of
mottled duck populations in South Carolina and Georgia. Although the phenomenon has not
been investigated, we suspect that this has been the reason Florida mottled ducks stay in the
peninsula even though Rhetts Island, where the introduced mottled ducks established the
southernmost breeding population, was within their dispersal limit. Given the dispersal ability of
mottled ducks, the southward expansion of their distribution, and their tendency to move toward
inland Florida, further southward expansion of the mottled duck distribution from Rhetts Island
is possible. The possibility is also supported by the harvest data in Guana River WMA. Before
1995, there were virtually no mottled ducks harvested in Guana River WMA, but since 1995 the
harvests on mottled ducks have been consistent, although much lower than those in South
Carolina, indicating the mottled duck population in Guana River WMA might be established by
small number of migrants from Georgia.
I conclude that mottled ducks have a great potential to disperse long distances but
successful breeding populations were established only south of release sites in the SACZ. HPUE
has increased since mottled ducks were introduced to South Carolina, indicating their increase in
abundance. The differences in mottled duck abundance at different locations provide good
opportunities to study factors associated with the abundance of mottled ducks in the SACZ. I
suggest that wildlife agencies incorporate standardized and consistent survey efforts to provide
17
improved estimates of mottled duck abundance and distribution in the SACZ. The southward
expansion and increase in abundance of this introduced population should concern biologists
because of the possible contact between two subspecies of mottled ducks.
18
Figure 2.1. Locations from which aerial survey and harvest data were collected on mottled
ducks. 1: Samworth Wildlife Management Area (WMA), 2: Santee-Delta and Santee
Coastal Reserve WMAs, 3: Sandy Beach WMA, 4: Hatchery WMA, 5: Bear Island and
Springfield WMA, 6: Donnelley WMA, 7: Savannah National Wildlife Refuge (NWR)
and Savannah Confined Disposal Facilities (CDFs), 8: Altamaha WMA, 9: Guana River
WMA. New breeding populations were found at Savannah NWR, Savannah CDFs, and
Altamaha WMA.
19
0
5
10
15
20
25
30
35
40
45
78 80 82 84 86 88 90 92 94 96 98 00
Year
Har
vest
per
100
hun
ters
Bear IslandSantee Coastal ReserveSantee DeltaSpringfieldAverage harvestPredicted average harvest
Figure 2.2. Number of mottled ducks harvested per 100 hunters in four wildlife management
areas. Bear Island and Santee Coastal Reserve were closed in 1980. Bear Island, Santee Coastal
Reserve, and Santee-Delta were closed in 1981. Springfield WMA was not open before 1994 and
data were not available until 1997. Number of hunters was unknown for 1999 and after 2001.
20
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05
Har
vest
per
100
hun
ters
Figure 2.3. Harvest data for mottled ducks from Guana River WMA. Data were not
available in 1993 and 1994 and before 1986.
21
Figugre 2.4. Recovery locations of mottled ducks banded in Florida. 1: Merritt Island, 2:
Andytown, 3: Sanibel Island, and 4: Kissimmee Chain of Lakes (after Fogarty and LaHart
1971).
22
CHAPTER 3
HABITAT USE OF MOTTLED DUCKS AT THE BEAR ISLAND WILDLIFE
MANAGEMENT AREA
INTRODUCTION
Since private owners and the government acquired old rice plantations in the South Atlantic
Coastal Zone (SACZ) in the late 1930s, rice fields in this area have been managed to benefit
wildlife (Gordon et al. 1989). Midwinter waterfowl surveys conducted by United States Fish and
Wildlife Service (USFWS) revealed that on average, 30% of dabbling ducks in the Atlantic
Flyway wintered in South Carolina from 1954 to 1987 (Gordon et al. 1989). The SACZ also
served as important staging areas for migrating waterfowl due to its geographic location
(Bellrose 1980). Therefore, managing habitats for migrating and wintering waterfowl is
currently the primary goal of many land owners and public wildlife management areas (WMAs)
along the SACZ (Gordon et al. 1989).
Before introducing mottled ducks (Anas fulvigula) to the Santee River Delta and the ACE
(Ashepoo, Combahee, and Edisto Rivers) Basin of South Carolina from Texas, Louisiana, and
Florida (T. Strange, South Carolina Department of Natural Resources, unpublished data), this
management goal sufficed the major function of the coastal wetlands along the SACZ. However,
the mottled duck is a non-migratory dabbling duck (Bellrose 1980) that is predominantly
sedentary (Stutzenbaker 1988). A mottled duck may depend on the same environment from
hatching, fledging, wintering, and breeding for life. Management practices that provide winter
23
food and habitat for waterfowl may not be optimal for mottled ducks in other seasons, especially
in June and July when peak numbers of flightless ducklings occur (Stutuzenbaker 1988).
Many researchers have suggested variables that determine waterfowl habitat selection.
Among the variables, food resources are critical for many stages in life history such as
reproduction (Lack 1967, Ryder 1970), growth of ducklings (Sedinger 1992, Cox et al. 1998),
molting (King 1980), and wintering (Joyner et al. 1984, Thompson and Baldassarre 1990) when
abundant energy and nutrients are needed. Vegetation structure is also an important factor
determining waterfowl habitat selection. A “hemi-marsh” with equal percentage of vegetation
coverage and open water attracts most dabbling ducks (Kaminski and Prince 1981), but each
different species has its own niche in vegetation-open water combinations (White and James
1978). Water depth is critical to waterfowl habitat selection because different species use
different feeding depths (White and James 1978). Even 5 to 10-cm change in water depth can
affect waterfowl use (Gordon et al. 1989).
Traditionally, however, habitat selection studies were based on the overall habitat
characteristics or measurements at random locations within a sampling unit such as an
impoundment instead the exact area occupied by birds (e.g., Murkin and Kadlec 1986, Cooper
and Anderson 1996). The variables measured by investigators may vary within the sampling unit.
For example, aquatic invertebrate composition, water depth, vegetation coverage, and salinity
may differ at various locations within a wetland. Waterfowl may concentrate on a specific and
small spot without using other areas in the vicinity. At Bear Island WMA, mottled ducks
repeatedly used certain locations in impoundments (G.-J. Weng, pers. obs.). Water depth in an
impoundment may vary over time due to management purposes such as widgeongrass (Ruppia
maritima) growth, algae control, mosquito control, etc. Average water depth over time may not
24
reflect the water depth preferred by mottled ducks. Also, overall food abundance may not
represent food availability for waterfowl due to their behavior (Cooper and Anderson 1996) or
morphology (Batzer et al. 1993). Therefore, measuring the overall character of a sampling unit
may miss the exact habitat characters truly preferred by waterfowl. For habitats used by mottled
ducks, previous researches only provided general description of vegetation composition (White
and James 1978), water depth (Paulus 1984), and habitat types (rice fields, pasture and fallow
fields, ditches and canals, fresh and brackish water, etc.) (LaHart and Cornwell, 1969, Zwank et
al. 1989). There has been no study on the habitat characteristics chosen by mottled ducks.
The objective of this study was to investigate habitat characteristics preferred by mottled
ducks during summer in one of the managed wetlands where they were released 30 years ago,
hoping to provide suggestions for the management of this year-round residential species in
summer. Because during summer, ducks rely on high amounts of protein provided by aquatic
invertebrates for growth of broods (Sedinger 1992, Cox et al. 1998) and molting (King 1980),
this study also estimated abundance of aquatic invertebrates available for mottled ducks at the
study site.
METHODS
Bear Island WMA was part of the ACE Basin, located within the estuary of the Ashepoo
River, South Carolina, and was owned and operated by South Carolina Department of Natural
Resources (DNR). The 4,810-ha WMA consisted of 2,150 ha of 25 managed impoundments,
2,000 ha of tidal marsh, 490 ha of woodlands, and 160 ha of agricultural lands. The
impoundments were managed for widgeongrass, dwarf spikerush (Eleocharis parvula), and
saltmarsh bulrush (Scirpus robustus) to provide quality habitat for wintering waterfowl and other
wetland wildlife (D. Harrigal, pers. comm.).
25
Direct observations of mottled ducks were conducted using a 20-60x spotting scope from a
vehicle along dike roads in June and July 2003. Each of the 25 impoundments was surveyed in
one day, 3 days a week during 7:00 a.m. and 6:00 p.m. When mottled ducks were detected,
activities of ducks were observed using scan sampling method (Martin and Bateson 1986) until
they left. All individuals visible were rapidly scanned and activity of each individual at that
instant was recorded. Behaviors of ducks were broadly categorized as foraging, resting (standing
or sitting), locomotor, comfort movements (preening, flapping, bathing), and alert (Kaminski and
Prince 1981), but only the behavior performed by > 50% of the individuals was recorded for the
flock. Number of ducks, water depth, distance of ducks to the nearest vegetation, and percent of
vegetation coverage within a 5-m radius were also recorded. Distance to vegetation was
categorized as <5 m, 5-10 m, 10-20 m, 20-50 m, and >50 m. After ducks left, one aquatic
invertebrate sample was taken at the exact location of ducks. Only one sample was taken
because ducks usually occupied a small area (<10 m radius) and collecting multiple samples in a
small area may produce pseudo-replication (Hurlbert 1984). Water depth in some impoundments
was as ≤ 5 cm, therefore, aquatic invertebrates were sampled with a hand net (20 cm x 15 cm,
mesh size 0.5 mm). A 1-m-long, 15-cm deep sweep was taken along the surface of the water at
each location. When water depth was < 15 cm, the net dragged on the bottom of water and water
depth was measured to adjust the volume of the net sweep. The net sweep was limited to the
depth of 15 cm because tip-up (up-side-down) feeding behavior was never observed in this
research and deeper food resources were considered unavailable to mottled ducks. Therefore,
this sampling method revealed only the availability of aquatic invertebrates for mottled ducks,
similar to the approach used by Cooper and Anderson (1996). After a sample was collected at a
location of ducks, another sample was taken immediately at a random location 50-100 m away in
26
the same or different impoundment where ducks were not observed. This approach of sampling
aimed to reveal the exact and real time characters of habitats used and not used by mottled ducks.
Sample locations were classified as used and unused. Used locations were those in which
ducks were observed ≥ 3 times regardless of the behaviors they exhibited to prevent a location
being used by chance. Only one sample was taken at each location. Unused locations were
those at which no ducks were recorded during the entire fieldwork period. Samples were
immediately preserved in 70% ethanol in the field until processed in the laboratory. Samples
were identified to the lowest taxonomic level possible using Brigham et al. (1982), Heard (1982),
Thorp and Covich (1991), and Merritt and Cummins (1996). In addition to aquatic invertebrates,
submerged plants, water depth, and number of ducks at each sample location were recorded.
Vegetation coverage of the impoundments used by mottled ducks was estimated by interpretation
of aerial photos and direct observation.
Because there was much variation in numbers of aquatic invertebrates and water depth
and sample size was small, a normal distribution could not be assumed for parametric tests. The
Wilcoxon 2-sample test (Sokal and Rohlf 1995) was used to test differences in densities (number
per liter) of aquatic invertebrates, except Chironomidae, and water depths between used and
unused locations as well as between locations with and without submersed vegetation.
Availability of Chironomidae was compared using average number per location because the
sampling method may not have captured bottom-dwelling species when water was > 15 cm and
density (number per liter) may not reflect their real abundance. Simple linear regression was
used to examine the correlation between water depth and availability of aquatic invertebrates.
Chi-square test was used to test correlation between presence of submersed vegetation and use
by mottled ducks.
27
RESULTS
A total of 60 observations (flocks x times) of mottled ducks were recorded in 10 of the 25
impoundments available at Bear Island WMA and another 9 observations were recorded flying.
Mottled ducks were detected four to 21 times in 7 of the 10 impoundments where mottled ducks
were observed and only one time in each of the other three (Fig. 3.1). Most (45%) mottled ducks
were in small flocks (≤ 5 individuals) and the largest flock consisted of 38 birds (average = 7.9,
SE = 7.1). Feeding and locomotor were observed > 70% of the time (Fig. 3.2). Ducks were
close to vegetation (≤ 10 m) about 70% of the time (Fig. 3.3).
Seventeen used and 20 unused locations were sampled for aquatic invertebrates. Use at
each of the 17 locations was foraging. Widgeongrass was the only submersed vegetation found
in the impoundments. We did not detect correlations between presence of widgeongrass or
availability of any aquatic invertebrate taxa and locations used by mottled ducks (χ2 = 0.033, p =
0.856 for widgeongrass, p>0.05 for aquatic invertebrate taxa). For the seven impoundments used
by mottled ducks at least twice, emergent vegetation coverage ranged from 20% to 80% with an
average of 52% (SE = 22.1%). Water depth was greater (Wilcoxon 2-sample test, p = 0.012) at
locations not used by mottled ducks (average = 23.05 cm) than those used by mottled ducks
(average = 14.24 cm). Mottled ducks were never observed using ditches where water depth was
> 1 m.
Aquatic invertebrates were classified into four phyla and five classes; each taxon was
identified to different levels of classification. Small fish were also found in the impoundment
(Table 3.1). For taxa with low number of individuals (Oligochaeta, Palaemonidae,
Hydrophilidae, Ceratopogonidae, Heteroptera, Odonata, and Pelecypoda), samples were pooled
to increase sample sizes. The densities (numbers per liter) of eleven taxa of aquatic invertebrates,
28
except Chironomidae, and one taxon of fish were compared between used and unused locations
(Table 3.1). The average availability of Chironomidae were not significantly different between
used and unused locations (p>0.05). Heteroptera, except Corixidae, were more abundant (p =
0.05) at locations unused by mottled ducks. Densities of other taxa were not different between
used and unused locations. Chironomidae were less abundant in deep water (p < 0.0001), but
water depth was not correlated with any other aquatic invertebrate availability (p>0.05) or total
aquatic invertebrate density (p = 0.165).
DISCUSSION
Mottled ducks used less than half of the impoundments at the Bear Island WMA (10 of 25
impoundments). The uneven distribution of mottled ducks in the 10 used impoundments
suggested strong preference of habitat by mottled ducks. Feeding was the most frequently
observed behavior in this study as it was in mottled ducks’ native habitats (Paulus 1984).
Locomotor behavior was observed more frequently at Bear Island WMA than at locations within
mottled ducks’ native range. A possible reason is that mottled ducks spent much time searching
for aquatic invertebrates and their behavior was determined at the instant when they were
observed. Therefore, in many occasions mottled ducks were recognized locomoting when they
were actually feeding. More locomotion time might reflect low densities of aquatic invertebrates,
but there are no available data on the relationship between food availability and locomotion time.
However, low numbers of mottled ducks at Bear Island WMA may make food a non-limiting
factor of the habitat for mottled ducks and allow mottled ducks to select habitat based on other
factors.
Total amount of submersed vegetation has been positively associated with waterfowl use of
an area (Joyner, 1980, McKinstry and Anderson 2002). Submersed vegetation provides habitat
29
for epiphytic or phytophilous invertebrates (Downing 1986, Cyr and Downing 1988) and the
abundance of invertebrates is positively correlated with biomass of submersed vegetation
(Bergey et al. 1992). Aquatic invertebrates in turn are important food sources for waterfowl
(Evans and Kerbs 1977, as cited in McKinstry and Anderson 2002, Batzer and Wissinger 1996
and citations therein). Additionally, submersed vegetation is an important food source for
waterfowl. For example, waterfowl consume seeds of widgeongrass, sago pondweed
(Potamogeton pectinatus), and redhead grass (Potamogeton perfoliatus) (Perry and Uhler 1988,
Euliss et al. 1991, Cox and Kadlec 1995). In this research, the existence of widgeongrass was
only correlated with distribution of Heteroptera, but not Corixidae. However, Heteroptera was
rare at Bear Island WMA – only 10 individuals were found at five locations. Thus this result did
not show any biological significance. The lack of association between widgeongrass and
densities of aquatic invertebrates in this study may explain why mottled ducks did not show
preference for locations with widgeongrass, the only submersed vegetation found at Bear Island
WMA. Another possibility is that mottled ducks did not use widgeongrass as a food source at
Bear Island WMA in summer.
Hemi-marsh, a marsh with equal amount of open water and emergent vegetation coverage,
supports more waterfowl than more open or vegetated wetlands (Murkin et al. 1982). The
attraction of waterfowl to hemi-marsh has been attributed to higher aquatic invertebrate
abundance in hemi-marsh (Voigts 1976, Murkin et al. 1992). In this study, however, the
impoundments used by mottled ducks were covered by emergent vegetation in 20% to 80% of
the area and mottled ducks mostly stayed close to vegetation. This fact indicates that mottled
ducks may use the edges between open water and emergent vegetation of a wetland regardless of
the overall coverage by emergent vegetation. Probably, because this research was conducted in
30
summer when mottled ducks were the only waterfowl using the impoundments, mottled ducks
could freely choose any locations with preferred vegetation in close proximity and/or other
habitat characters instead of selecting a hemi-marsh. During winter when abundant waterfowl
winter at Bear Island WMA, hemi-marsh may support more individuals because it provides more
open water-vegetation edges.
Waterfowl may selectively feed on certain aquatic invertebrates that are not the most
abundant at feeding sites (Batzer et al. 1993). Because the esophageal contents of mottled ducks
were not examined, it is not clear whether aquatic invertebrates consumed by mottled ducks were
correlated with their density at feeding sites. Because the size of flocks was small, however,
mottled ducks may selectively feed on certain invertebrate taxa without dramatically changing
their density. Hence, aquatic invertebrates may not be a limiting factor affecting the selection of
habitats by mottled ducks, and we did not detect a relationship between mottled ducks and
aquatic invertebrate densities among habitats.
McKinstry and Anderson (2002) found that puddle ducks used wetlands with deeper water
(mean = 1.51 m). In this research, water was deeper at unused than used locations, indicating a
preference for shallow (3-45 cm, average = 14.24 cm) water by mottled ducks. Among the
aquatic invertebrate taxa and widgeongrass, availability of Chironomidae was the only taxon that
was associated with water depth, with more abundant Chironomidae in shallow water. This
taxon exhibits diel vertical migration in vegetation. Some epiphytic species of Chironomidae
stay close to the bottom of water during daytime and move to the vegetation surface at night
(Marklund et al. 2001), probably due to the adaptation to the predation pressure or the reduced
number as a result of predation (Becket et al. 1992). In this study, availability of Chironomidae
was not different in used and unused locations by mottled ducks. Therefore, avoidance of
31
predation or reduction by predation by mottled ducks was not a likely reason explaining lower
availability of Chironomidae in deeper water. Availability of Chironomidae was higher in
shallow water probably because the sampling method did not adequately collect benthic species
in deeper water and at the soil surface, indicating that in shallow water these food resources are
more readily available to mottled ducks than in deep water. Also, average water depth at
locations used by mottled ducks showed that free-swimming and benthic aquatic invertebrates
are both within the reach of mottled ducks.
Shallow water possibly also provides protection for mottled ducks against predators. Elsey
et al. (2004) found that the American alligator (Alligator mississippiensis) preys on mottled
ducks more frequently than previously realized. They collected alligators at shallow water
habitats preferred by mottled ducks during summer when flightless ducklings and molting adults
were present. Mottled duck remains were found in about 21% of alligators, far more frequent
than other studies conducted at deep-water areas in fall or winter (Elsey et al. 2004). Choosing
shallow water areas may provide mottled ducks more visual surveillance against predators such
as alligators because it is more difficult for alligators to hide and ambush mottled ducks from
shallow water. On the other hand, water depth preferred by mottled ducks in summer is usually
too low to support abundant alligators (Elsey et al. 2004).
Sampling at the exact locations and time of use revealed that mottled ducks selected certain
locations instead of overall characters of an impoundment. Future studies on habitat selection
may apply this approach and find more specific habitat characteristics preferred by waterfowl.
We found that water depth was the only factor associated with habitat preference by mottled
ducks at Bear Island WMA during summer. Aquatic invertebrates were not more abundant in
shallow water but shallow water ensured higher availability of aquatic invertebrates to mottled
32
ducks. Management practices for this mottled duck population during summer do not need to
consider the density of aquatic invertebrates. Instead, water depth should be maintained at a
preferred level for mottled ducks. If management practices seek to increase the number of
mottled ducks, further researches should focus on why the mottled duck population was low at
Bear Island WMA.
33
Table 3.1. Density of aquatic invertebrates and fish in locations used and unused by
mottled ducks at Bear Island Wildlife Management Area, South Carolina, June-July 2003.
P-values were the exact p-values from Wilcoxon 2-sample test.
Mean density (number/liter)
Phylum Class Order Family Unused (n=20) Used (n=17) p-value
Annelida Oligochaeta 0.46 0.47 0.935
Arthropoda Crustacea Conchostraca 33.93 50.58 0.635
Decapoda Palaemonidae 0.07 0.08 0.900
Arthropoda Insecta Coleoptera Hydrophilidae 0.42 1.34 0.388
Diptera Ceratopogonidae 0.59 0.19 0.658
Heteroptera Corixidae 1.84 8.93 0.306
others 0.11 0.00 0.050
Odonata Coenagrionidae 1.17 0.99 0.879
others 0.03 0.12 0.427
Mollusca Gastropoda 6.79 15.97 0.611
Pelecypoda 0.07 0.08 0.900
Total aquatic invertebrates 49.68 81.94 0.498
Chordata Actinopterygii Perciformes 1.64 2.29 0.370
34
0
5
10
15
20
25
30
35
40
Mid
dle
Spr
ingf
ield
Blu
ff
Mos
quito
Shan
ty
Low
er H
og
Low
er P
ine
Cro
oked
cree
k
Sar
a
Hou
se
Impoundments
Freq
uenc
ies
of m
ottle
d du
cks
obse
rved
(%)
Figure 3.1. Frequencies of mottled ducks observed at 10 of 25 impoundments at Bear Island
Wildlife Management Area, South Carolina, June-July 2003. Frequencies were based on 60
observations (flocks x times).
35
0
10
20
30
40
50
feeding locomotor resting comfort
Behavior
Freq
uenc
y (%
)
Figure 3.2. Frequencies of behaviors exhibited by mottled ducks at Bear
Island Wildlife Management Area, South Carolina, June-July 2003.
Frequencies were based on 60 observations (flocks x times). Resting
behavior included sitting and standing. Comfort behavior included
preening, flapping, and bathing.
36
0
10
20
30
40
50
<5 5-10 10-20 20-50 >50
Distance to vegetation (m)
Freq
uenc
y (%
)
Figure 3.3. Frequencies of distance to nearest vegetation from mottled ducks at
Bear Island Wildlife Management Area, South Carolina, June-July 2003.
Frequencies were based on 60 observations (flocks x times).
37
CHAPTER 4
POPULATION STRUCTUR AND GENE FLOW OF MOTTLED DUCKS WITNIN THE
SOUTH ATLANTIC COASTAL ZONE
INTRODUCION
Translocation is broadly defined as moving a living organism from one area and releasing it
freely in another (IUCN 2006). It has been used as a tool of conservation to increase genetic
diversity of small populations (Griffith et al. 1989, Newman and Tallmon 2001), establish
satellite populations to reduce the risk of extinction (Goodman 1987), or re-establish or augment
wild populations (Kleiman et al. 1991). However, without careful consideration, translocation
can be a threat to native species and ecosystems. For example, alien species have introduced
diseases or parasites to a new ecosystem (Dobson and May 1986, Szabo 2003), altered the
habitat (Danell 1979, Jackson 1988, Moore et al. 1999), and out-competed native species (Moyle
1973). For introduced species themselves, a small founder population size can result in
decreased genetic diversity, and interbreeding with native populations may cause extinction of
the species (Greig 1979, Hughes et al. 2003).
When a translocated population is self-sustainable, the translocation is considered
successful (Griffith et al. 1989). To establish a self-sustainable population, Foose (1991)
suggested that a conservation program should consider the kinds and amounts of genetic
diversity are to be preserved, and the period of time over which this genetic diversity is to be
maintained. To reduce the impacts of translocation on recipient ecosystems, the IUCN (2006)
suggested some critical considerations to be assessed before conducting a translocation. One is
38
to consider capacity of the introduced species to reduce the genetic uniqueness of native species
by interbreeding with them. D’Antonio et al. (2001) also listed this consideration as one of the
top research questions that needs to be answered in this decade. These questions are hard to
answer before a translocation is conducted and very few translocations have been evaluated
during the whole process (Griffith et al. 1989). However, we can investigate these questions
from translocations with a known history.
The mottled duck (Anas fulvigula) is one of few non-migratory waterfowl species in North
America. The Florida mottled duck (A. f. fulvigula) and mottled duck (A. f. maculosa) in Texas
and Louisiana are considered two naturally-occurring subspecies (Bellrose 1980). Individuals
from these populations were captured and introduced to the Santee River Delta and the ACE
(Ashepoo, Combahee, and Edisto Rivers) Basin of South Carolina from 1975-1982. The
individuals were from Texas (126 birds), Louisiana (1,045 birds), and Florida (26 birds) (T.
Strange, South Carolina Department of Natural Resources, pers. comm.). The introduction was
driven by the desire to increase hunting opportunities in South Carolina. Impacts of this
translocation and establishment of mottled ducks on the introduced population per se and on
other native species were not considered.
The introduced mottled duck population was a small fraction of its source populations and
it has been isolated for about 30 years. Newly established populations in Georgia of mottled
ducks introduced to South Carolina may have experienced even more severe reduction in
population size (bottleneck) than those in South Carolina. Mottled ducks generally have a strong
sedentary nature; in a study by Stutzenbaker (1988), 82% of the birds in Texas and Louisiana
were shot in the county where they were banded. Breeding may thus be restricted within small
areas. Small and fragmented populations are expected to experience stronger genetic drift, loss
39
of genetic diversity, and diversification than big populations (Frankham et al. 2002). Therefore,
the reduction in population size and sedentary nature of mottled ducks combined may have
caused genetic drift and reduced genetic diversity in the last 30 years.
Data collected from hunters’ harvests and monthly aerial surveys by the Georgia
Department of Natural Resources (DNR) from 2002-2005, identified a resident population of
mottled ducks on Rhetts Island, about 64 km north of the border between Georgia and Florida.
This southward expansion of the mottled duck population introduced to South Carolina (1975-
1982) is a great concern to ornithologists because of efforts to maintain the Florida mottled duck
as a genetically distinct subspecies (Florida Fish and Wildlife Conservation Commission 2006a).
Analyses of mitochondrial DNA of Louisiana-Texas and Florida mottled ducks did not detect
any gene flow between these populations (McCracken et al. 2001), supporting the idea that these
two populations are genetically distinct. South Carolina and Georgia mottled duck populations
are geographically near Florida so gene flow could occur. For example, shortly after the
introduction to South Carolina, a banded individual was found in Florida (U.S. Geological
Survey, Biological Resources Division, Patuxent Wildlife Research Center, Laurel, Maryland,
cited in McCracken et al. 2001). Thus, it is possible that the introduction of mottled ducks to the
South Atlantic Coastal Zone (SACZ) has broken the isolation of the Florida mottled duck
population.
If management and conservation goals for the Florida mottled duck population focus on
maintaining its status as a distinct subspecies, then we must be certain of its genetic composition,
especially relative to similar populations – the Louisiana-Texas and South Carolina-Georgia
populations. Hence, this research aimed to: 1) reveal genetic population structure of mottled
ducks in the five states where they occur, 2) reveal partition of genetic variation within and
40
between populations, 3) compare genetic diversity and genetic distance between introduced and
source populations, 4) detect possible bottleneck effects on the introduced populations, and 5)
estimate the level and pattern of possible gene flow from Georgia-South Carolina to Florida.
METHODS
Sample Collection
From 2001 to 2005, whole ducks, wings, or feathers were collected from hunters at several
wildlife management areas (WMA) and from wildlife agencies that conducted banding work at
several national or state wildlife refuges (NWR or SWR) (Table 4.1). Samples from hunters
were collected during the hunting season from late November to late January or early February.
Samples from banding work were collected in summer. Sex and age (hatch year or after hatch
year) of some samples and possible hybrids (mallard [Anas playtyrhynchos] x mottled duck)
were identified by biologists who banded the ducks. Sample sources encompassed the entire
distribution and range of mottled ducks (Fig. 4.1).
Microsatellite Loci
Twenty-four primer sets developed for mallards by Fields and Scribner (1997) (Sfiµ 1, 3, 4,
5, and 7), Buchholz et al. (1998) (Bca 6, 11), and Maak et al. (2003) (APH02, 04, 05, 06, 08, 12,
13, 15-21, and 23-25) were modified and tested with respect to their utility on mottled ducks. All
primer sets were examined using Oligo 4.0 (Molecular Biology Insights Inc., West Cascade, CO)
for internal stability, secondary structure, primer-dimer formation, primer length, and agreement
of upper- and lower-primer melting temperatures. Primer pairs falling outside the range of
acceptable values were re-designed using the original sequence. A M13 reverse tag (5’-
GGAAACAGCTATGACCAT-3’) or CAG tag (5’-CAGTCGGGCGTCATCA-3’) (Schable et al.
2002) was added to the 5’ end of one of each primer pair using Oligo 4.0 (Molecular Biology
41
Insights Inc., West Cascade, CO) to obtain the fewest secondary structures. Inclusion of the 5’
tag allowed use of a third primer in the PCR (fluorescently labeled M13 reverse or CAG for
detection on an ABI 3730; cf. Boutin-Ganache et al. 2001) for subsequent amplification. GTTT
“pigtails” were added to the 5’ end of each primer not possessing either the CAG or M13 reverse
tag to facilitate the non-templated addition of adenosine by Taq polymerase (Brownstein et al.
1996, Traxler et al. 2000).
DNA Extraction
DNA was isolated from muscle tissue or feather samples collected from each mottled duck.
DNA from muscle tissues was extracted using the DNeasy Tissue Kit (QIAGEN Inc., Valencia,
California) following the protocol provided by QIAGEN Inc. DNA from feather samples was
collected from the tip of two to five quills and was extracted following the Qiagen protocol with
addition of 0.100 g/ml of DTT (dithiothreitol) to the digestion step.
PCR reactions were carried out using a subset of the microsatellite primers identified
previously. PCR reactions were conducted on a peltier thermal cycler in a reaction mix
containing 0.1 µL Taq Polymerase; 1 µL Taq Reaction Buffer; 0.6 µL MgCl2 (25 mM); 1 µL
dNTP; 0.5 M of untagged primer; 0.05M of M13- or CAG-tagged primer; 0.45 M of
fluorescently labeled M13 or CAG tag (Integrated DNA Technologies, Coralville, IA); 4.8 µL
sterile, distilled water; and 1.5 µL template DNA for a final reaction volume of 10 µL. PCR
cycling was performed in a Bio-Rad Thermal Cycler (Bio-Rad, Hercules, California) with an
initial denaturation of 94°C for 1 min followed by 21 cycles of 96°C for 20 sec; 57°C or 65°C
(highest annealing temperature, Ta) for 30 sec minus 0.5°C per each annealing cycle; and 72°C
for 1 min followed by 15 cycles of 96°C for 20 sec; 47°C for 30 sec; 72°C for 30 sec with a final
extension period of 10 min at 72°C.
42
Fragment analysis was conducted on an Applied Biosystems 3730 DNA Analyzer (Perkin
Elmer Applied Biosystems, Norwalk, Connecticut). Fragment size data were extracted from the
sequencer, and alleles were sized and binned using the GeneMapper™ program (Perkin Elmer
Applied Biosystems, Norwalk, Connecticut). The ROX500™ standard (Perkin Elmer Applied
Biosystems, Norwalk, Connecticut) was included as an in-lane size standard for each run of 96
samples, and negative and positive controls were included in 2 lanes of each scoring run.
Twenty samples, from among those already analyzed, were selected at random for re-scoring to
ensure that consistency was maintained among analyses.
Statistical Analysis
Because spatial and temporal sampling scenarios will affect interpretation of the population
structure, ideally, each sample should represent a deme (breeding unit) and belong to the same
cohort for organisms with overlapping generations (Balloux and Lugon-Moulin 2002). Without
a priori information on the boundaries of demes, all the samples from different locations and
seasons were analyzed separately before they were clustered to reveal population structure. Tests
of Hardy-Weinberg Equilibrium (HWE) and linkage disequilibrium were conducted for each
locus and sample using Genepop ver. 3.4 (updated version of Raymond and Rousset 1995). FST
values for each pair of samples from the same locations were calculated in GENALEX 6
(Peakall and Smouse 2006) using an AMOVA (Analysis of Molecular Variance) -based estimate
because unequal sample size is accounted for in AMOVA in the computation of variance
components and in the permutation-based testing procedure (Excoffier et al. 1992, Excoffier,
pers. comm.). Weir and Cockerham’s (1984) estimator of FST was not used because their
estimator assumes equal population size. Samples from the same location but different seasons
or from different units in the same area were combined if the FST value was not significantly
43
different from zero at alpha = 0.05 via permutation. Possible hybrids identified by wildlife
biologists based on plumage were combined with other individuals from the same locations if
possible hybrids were not different from other individuals (FST = 0). All simultaneous tests were
adjusted for p-values using sequential Bonferroni correction (Rice 1989). Sequential Bonferroni
correction begins with a predetermined significance level divided by number of simultaneous
tests. For example, if significance level is alpha = 0.05 and number of simultaneous tests is 10,
then the correction begins with 0.05/10 = 0.005. If the smallest p-value of the 10 tests is smaller
than 0.005, then the test is significant at alpha = 0.05. After the test with the smallest p-value is
corrected, 9 tests are remained to be corrected and the next corrected p-value is 0.05/9 = 0.0056.
If the smallest p-value of the 9 tests is smaller than 0.0056, then the test is significant at alpha =
0.05. The procedure continues until all the tests are corrected, and the final p-value (the largest
one in the 10 tests) should be compared with 0.05/1 = 0.05. For the HWE tests, there were 225
(25 samples x 9 loci = 225) simultaneous tests and the initial significance level would be
extremely small (0.05/225 = 0.0002) if sequential Bonferroni correction (Rice 1989) was strictly
followed. With such a small significance level, it is virtually impossible to detect any deviation
from HWE due to the conservative procedure. Therefore, sequential Bonferroni correction was
conducted within each locus across 25 samples, and the initial significance level was adjusted to
0.002 (= 0.05/25). For the linkage disequilibrium tests, the same rationale was applied and a
sequential Bonferroni correction was conducted within each sample across all the pair-wise
combinations of loci. There were 36 pair-wise combinations of loci and the initial significance
level was adjusted to alpha = 0.0014 (0.05/36).
Because the populations of mottled ducks introduced to South Carolina have been
separated from source populations for only 30 years and microsatellite DNA is virtually neutral
44
to selection, mutation and selection were negligible as evolutionary forces to change
distributions of allele frequencies in these populations. Genetic drift would be the primary
evolutionary force to possibly change gene frequencies since the introduction of mottled ducks to
South Carolina. Therefore, the Reynold et al. (1983) FST-based genetic distance (D = - log (1-
FST)) was calculated for each pair of samples using GDA (Genetic Data Analysis) ver. 1.1
(updated version of Lewis and Zaykin 2001) because this measurement is appropriate for
divergence due to drift only and approximately proportional to the divergence time (p.197 in
Weir 1996). Populations were then clustered to build a phenogram using the widely-used
UPGMA (Unweighted Pair Group Method using Arithmetic averaging, Sneath and Sokal 1973).
The UPGMA approach has been modified and used by Holsinger and Mason-Gamer (1996) and
Gibbs et al. (2000). Gibbs et al. (2000) recalculated FST for each new cluster during the
construction of the phenogram. In this research, FST was not recalculated because treating
members in the same cluster as one single population and recalculating FST does not make
biological sense. The phenogram reflects the hierarchical relationship among populations but not
exact divergence time between any two populations or clusters. The significance of the
phenogram was tested at each level of the cluster with FST using GENALEX 6 and log likelihood
ratio (G) based exact test (Goudet et al. 1996) using GENEPOP ver. 3.4. The G-based test has
higher power than other exact tests of differentiation when sample sizes are unbalanced (Goudet
et al. 1996) and is robust for microsatellite data (Ryman et al. 2006). Members of the same
cluster were further combined if they were geographically close to each other but not
significantly differentiated. FST values and G-based tests were calculated again at each level of
clustering. The process continued until members in each cluster were significantly differentiated
or not continuous in distribution. The same grouping of populations was used to construct
45
population structure using Neighbor-Joining method (Saitou and Nei 1987) in MEGA 3.1
(Kumar et al. 2004). This procedure inevitably increased FIS and heterozygosity deficiency in
each newly defined population, but the purpose of the procedure was not to define perfect
breeding units. The advantage of this procedure is that it does not arbitrarily assume boundaries
of populations and reveals and simplifies population structure naturally. The populations along
SACZ were examined for the pattern of isolation by distance by plotting log10(number of
migrants) against log10(geographic distance) according to Slatkin (1993) to detect the interaction
of gene flow and genetic drift. The significance of isolation by distance was tested with a Mantel
test (Mantel 1967) using GENALEX 6. Estimation of the number of migrants is stated below.
The following analyses were based on the newly defined populations (see results) and their
structure.
The newly defined populations were compared for observed heterozygosity and unbiased
estimate of expected heterozygosity using GDA ver. 1.1 and average number of alleles across
loci and average number of private alleles across loci using GENALEX 6. The populations were
also compared for the expected number of alleles per locus (allelic richness) using the rarefaction
method (Hurlbert 1971) in FSTAT ver. 1.2 (Goudet 1995) to relieve the effect of sample size
(Mousadik and Petit 1996, Petit et al. 1998, Leberg 2002). This method provides an unbiased
estimate of allelic richness and the greatest statistical power to detect differences in variation
(Leberg 2002).
The newly defined populations were sorted into three groups: Texas-Louisiana, Florida,
and Georgia-South Carolina to represent two sub-species and an introduced population,
respectively. Pair-wise FST and partition of the total genetic variance due to among-group
46
differences and within-group differences were calculated using the analysis of molecular
variance (AMOVA, Excoffier et al. 1992) in GENALEX 6.
To detect possible bottleneck or population expansion events in the newly established
populations in the SACZ, four approaches for microsatellite data were applied to ensure that all
information in the data was used. Cornuet and Luikart (1996) compared the expected
heterozygosity under mutation-drift equilibrium and observed heterozygosity computed from
samples to detect a reduction of effective population size. If a population has experienced a
bottleneck event, allele number is reduced faster than heterozygosity (Nei et al. 1975) because
rare alleles are lost first but they contribute very little to heterozygosity and excess of
heterozygosity would be observed, but this excess will persist only a few generations until new
mutation-drift equilibrium is reached. Tests were performed using the Bottleneck program
(Cornuet and Luikart 1996) with a two-phased mutation model (variance = 30%, proportion of
stepwise mutation model = 70%) and Wilcoxon sign-rank test as suggested by authors in the
documentation for the software.
Reich and Goldstein (1998) developed two statistical tests to detect population expansion.
The expected distribution of allele lengths of a population at mutation-drift equilibrium is
multimodal and heavy-tailed, but for a population that experienced recent expansion, the
distribution tends to be unimodel. This deviation from an expected distribution is detected by a
k-test, or equivalently kurtosis. The kurtosis was calculated for each locus, and the significance
of the proportion of positive k values was based on a binomial distribution with the probability of
a positive k set as 0.515 (Reich et al. 1999). The second test, g-test, is based on the expectation
that the variance of the variance of an allele length distribution is larger for constant-sized
populations than expanding ones assuming the loci follow a stepwise mutation model (Kimura
47
and Ohta 1978). Significance levels for the g-test were given in Reich et al. (1999). Both tests
were performed using programs written in the SAS language (SAS Institute Inc., Cary, NC).
Kimmel et al. (1998) derived the imbalance index (β) using the observed variance in allele
size for a given locus and expected homozygosity for the same locus. Populations that have been
stable for long periods of time have β values close to 1.0, while populations that recently
experienced a bottleneck then expanded are predicted to have β values greater than 1.0. Finally,
Garza and Williamson’s (2001) M value was used to detect reductions in population size. The M
value is the ratio of the number of alleles to the range in allele size. This value decreases when a
population is reduced in size because number of alleles is lost faster than the range in allele size
(Garza and Williamson 2001).
For the detection of possible gene flow, Slatkin’s (1985) private-allele method conducted in
GENEPOP ver. 3.4 and Wright’s FST conducted in GENALEX 6 were used to estimate average
number of migrants between each pair of populations per generation. Migrants were defined as
individuals that move between different populations. The private-allele method uses the
logarithm of the average frequency of private alleles to estimate the average number of migrants
exchanged between populations. This method is not sensitive to the geometries of populations
and is a rough way to correct for differences in sample size (Slatkin 1985). For a FST-based
estimate, average number of migrants per generation is M = (1 – FST )/(4FST). Although the
indirect measure of gene flow based on FST relies on many unrealistic assumptions (Whitlock
and McCauley 1999), no alternative strategy is clearly superior to this approach (Neigel 1997).
Slatkin and Barton (1989) compared both methods and concluded that both methods provide a
reasonably accurate estimate of the average number of migrants under a wide variety of
conditions, but they considered FST more useful than the private-allele method in that FST is less
48
sensitive to electrophoretic errors and uses more information than private-allele method. For
samples with sex and age information, sex-biased and age-biased gene flow was tested using the
assignment test in GENALEX 6 (Peakall and Smouse 2006). Although dispersal is not equal to
gene flow, it is a prerequisite before gene flow occurs. Sex-biased and age-biased gene flow was
therefore interpreted from sex or age-biased dispersal. The assignment test was based on Favre
et al. (1997). A log likelihood assignment index was calculated for each individual. Then, an
Assignment Index correction (AIc) was calculated by deducting the mean log likelihood of the
population from each individual log likelihood. A negative AIc value indicates an individual is
likely an immigrant. Average AIc values of sex and age categories were then compared to detect
biased gene flow.
RESULTS
Hardy-Weinberg Equilibrium and Linkage Disequilibrium
Eight hundred and seven birds were collected from 25 locations x season combinations
(Table 4.1). Nine primer sets modified from Maak et al. (2003) were used for final genotyping
out of 24 sets tested (Table 4.2). All of the nine microsatellite loci were polymorphic, with a
mean number of alleles per locus of 15.2 (Table 4.3) across the 10 newly defined populations
(see below and Fig. 4.1). Average expected heterozygosity was 0.733, and average inbreeding
coefficient was 0.127 (Table 4.3). After the modified sequential Bonferroni correction, six of
nine loci deviated from HWE in one to nine samples (Table 4.4). Three loci (APH08, APH15,
and APH18) did not deviate from HWE and four loci (APH04, APH05, APH17, and APH24)
deviated from HWE in three or fewer samples (Table 4.4). For significance level at alpha = 0.05,
it is reasonable to see one or two out of 25 samples deviate from HWE (25 x 0.05 = 1.25) if the
null hypothesis is, all the samples follow HWE. Therefore, APH17 and APH05 did not
49
significantly deviate from HWE, and APH04 marginally deviated from HWE (Table 4.4). Only
APH02 and APH21 significantly deviated from HWE (Table 4.4). Except for APH21, deviations
from HWE were separated in two subspecies; APH02 deviated from HWE in TX-LA samples or
GA-SC samples that were descendents of TX-LA mottled ducks; APH04 deviated from HWE in
FL samples only (Table 4.4). Linkage disequilibrium of samples for any pair-wise combination
of loci was not detected. The following statistical analyses do not assume HWE. Therefore the
deviation from HWE at APH02 and APH21 did not affect the results.
Population Differentiation and Structure
Possible hybrids identified by wildlife biologists based on plumage were not different from
other individuals collected in the same area (FST = 0). Birds collected from the same
management area or refuge at different times or in different units were also not distinguishable
(FST = 0). Therefore, all birds from the same management area or refuge were combined into 14
populations (Fig. 4.1). These 14 populations were further grouped into 10 populations according
to the procedure described in methods (Table 4.5, Fig. 4.1). The UPGMA and Neighbor-Joining
methods showed similar population structure (Fig. 4.2, 4.3). The populations from TX-LA and
GA-SC were clearly separated from FL populations, except the Guana population was in the TX-
LA cluster (Fig. 4.2 and 4.3). The structure reflects the geographical relationship among
populations (Fig. 4.1) and the origin of the introduced populations. The introduced mottled
ducks were released in the SCR and ACE Basin where Bear Island WMA is located. The
structure indicates that SCR and Bear populations are genetically closest to TX and LA
populations, and the SCR population is genetically closer to the LA population than the TX
population. Along the SACZ, populations geographically closer to SCR were also genetically
closer to the SCR population. One discrepancy between FST and G-based tests was detected at
50
the cluster composed of LA, TX, and SCR populations (Fig. 4.2). Except for the Brevard-Duda
cluster, every cluster had a weak but significant population structure according to the G-based
test. Pairs of populations were either weakly differentiated or not significantly differentiated,
and FST ranged from < 0.001 to 0.052 (Table 4.6). The discrepancies between the two
measurements of population differentiation were between pairs of SCR-Duda, Bear-Rhetts,
Rhetts-Duda, Brevard-IMC, Brevard-Orange, Duda-Orange, and IMC-Orange. The pattern of
isolation by distance for the four populations (SCR, Bear, Rhetts, and Guana) along SACZ was
apparent, revealed by log10(number of migrants) plotted against log10(geographic distance) with
an R2 value of 0.126 (Fig 4.4). The FST and G-based p-values for all Florida populations were
0.030 and p < 0.0001, respectively. The FST for introduced populations was not significantly
different from zero and p-value for the G-based test was 0.0557. Hence, both tests indicated the
introduced populations were not significantly differentiated. The overall FST was 0.022 (p < 0.01)
and p < 0.0001 for the G-based test, indicating significant but weak differentiation for all the
mottled duck populations.
Genetic Variability
The genetic characteristics of the nine microsatellite loci in the ten populations of mottled
ducks were described (Table 4.7) and all populations had high and homogeneous levels of
expected heterozygosity (average = 0.721, SE = 0.017) across loci (Fig. 4.5). The expected
heterozygosity for TX-LA and GA-SC populations (average = 0.729, SE = 0.017) was not
significantly different from that of Florida populations (average = 0.712, SE = 0.014). Observed
heterozygosities were all lower than and roughly parallel to the expected ones (Fig. 4.5), except
the Duda population, indicating homogeneous inbreeding coefficient (FIS) among the populations
(average = 0.117, SE = 0.035). Number of alleles per locus reflected the sample size for each
51
population, but after adjusted for sample size at N = 25, all TX-LA and GA-SC populations had
higher allelic richness (average = 6.24, SE = 0.25) than Florida population (average = 5.30, SE =
0.34) (Fig. 4.5). Private alleles were observed in Guana, Brevard, IMC, LA, and TX. None of
the introduced populations had private alleles, although their allelic richness was higher than
Guana, Brevard, and IMC populations. The FST values were 0.021, 0.004, and 0.025 between
GA-SC and Florida, GA-SC and TX-LA, and Florida and TX-LA populations, respectively. The
FST between GA-SC and Florida and FST between Florida and TX-LA were significantly different
from zero at p = 0.01. AMOVA tests indicated that only 1.9% of the total genetic variance was
due to differences among the three groups of mottled duck populations in TX-LA, GA-SC, and
Florida (Table 4.8). Most (98.1%) of the genetic variance was due to differences within
populations (Table 4.8).
Bottleneck Events
Tests of bottleneck events in the mottled duck populations by different methods revealed
variable results (Table 4.9). Wilcoxon sign-rank tests suggested possible bottleneck history in
Rhetts, IMC, and Orange populations. Because the k-test is based on a binomial distribution and
nine loci, conventional significance levels (alpha = 0.05 or 0.01) are not available and the most
appropriate significance level is alpha = 0.07 with corresponding k-test value of 2. Each
population had four or more numbers of positive k-values, thus none of the populations had a
sign of population expansion. The values for the g-test were larger than any critical values in the
table provided by Reich et al. (1999), indicating the populations have not experienced recent
expansion in size. On the contrary, all the beta-values were much larger than 1.0, indicating all
the populations had a recent bottleneck history. All populations had homogeneous M-value
52
around 0.4, which also strongly indicates recent bottleneck events according to Garza and
Williamson (2001).
Number of Migrants
Estimated numbers of migrants between each pair of populations were one or more per
generation (Table 4.10). Tests on sex- and age-biased dispersal were done on Brevard, TX, and
LA populations that had reasonable sample size for the tests. AIc values showed equal
probabilities for individuals in different sex or age categories to be assigned in the same
population, indicating that there was no significant sex- or age-biased dispersal (Fig. 4.6).
DISCUSSION
Population Structure
The ten newly defined mottled duck populations (Table 4.5, Fig. 4.1 and 4.2) reflected a
shallow but clear genetic structure. The structure is shallow because the FST value at each level
of clustering is very small. Conventionally, a FST value in the range 0-0.05 indicates little
genetic differentiation, but none of the FST values in this research exceeded 0.05. However, FST,
or other parameters such as GST that estimate the relative amounts of between-population and
total diversity, is inherently dependent on the level of genetic diversity; higher level of diversity
results in lower value of the parameter even if absolute divergence is high (Nagylaki 1998, Nei
1987, p.190). For example, Jin and Chakraborty (1995) showed analytically that for completely
isolated populations, the value of GST ranges from zero to unity depending on the amount of
variation (or mutation rate). For highly polymorphic markers such as microsatellite loci, FST
may thus be deflated because of the reduced level of homozygosity (Wright 1978, Charlesworth
1998, Hedrick 1999) and underestimate differentiation in highly structured populations (Balloux
and Lugon-Moulin 2002). Therefore, a low value of FST may suggest significant genetic
53
differentiation. Loci used in this research have a high value of expected heterozygosity (average
= 0.733), which may reduce the estimates of FST. On the other hand, with highly polymorphic
loci, statistically significant differences can be easily detected, but they may not be translated
directly to significantly biological differences (Hedrick 1999). Thus the mottled duck
populations may differentiate more than the FST values appear but may not as significant as the
p-values suggest.
On the contrary, bottleneck events can largely increase genetic distance among populations
due to reduced heterozygosity in populations that have experienced bottleneck events (Hedrick
1999). Possible bottleneck events were restricted to three populations only (see below), and one
of these populations (the IMC population) was not significantly differentiated from its
neighboring populations. Therefore, genetic distance measurement in this research was
minimally affected by bottleneck events.
The genetic structure is especially ambiguous in Florida for populations south to the
Orange population. The G-based test p-values for each pair of the populations and for the cluster
were not significant after sequential Bonferroni correction. Discrepancies between FST and G-
based tests for Brevard-IMC, Brevard-Orange, Duda-Orange, and IMC-Orange populations also
reflect the unclear population genetic structure in Florida south to the Orange population. This
result agrees with Williams et al. (2002) that Florida mottled ducks do not have significant
genetic structure. But Williams et al. (2002) did not collect mottled ducks from northern Florida
where significant differentiation was found in this research. Except for populations south to the
Orange population, clear hierarchical structure among populations along the SACZ is in
accordance with the geographic distance among the populations. The structure was also
supported by the apparent pattern of isolation by distance. Compared with the example of
54
glaucous wing gull (Larus glaucescens) on the west coast of North America in Slatkin (1993),
the patterns of isolation by distance for the two coastal bird species, mottled duck and glaucous
wing gull, are very similar, and the results suggest that the mottled duck is at an approximate
equilibrium under genetic drift and high level of gene flow, although the dispersal distance is not
far enough to homogenize populations along the SACZ.
It was interesting to see that the Guana population (A. f. fulvigula) appears in the same
cluster with another subspecies, the TX-LA and GA-SC populations (A. f. maculosa). Two
possible reasons can explain this similarity between two subspecies across the border of Georgia
and Florida: (1) the similarity can be due to recent common ancestry for the GA-SC population
and Guana population, namely the Guana population was probably established by mottled ducks
from GA-SC, and (2) high levels of gene flow have homogenized microsatellite DNA in the
Guana and GA-SC populations. However, private alleles were found in the Guana population
but not in any GA-SC populations, suggesting that the Guana population has a longer history
than GA-SC population. Therefore, the Guana population should be originally A. f. fulvigula and
have evolved independently from another subspecies. Gene flow is thus the only possible reason
to explain the similarity. The current mottled duck population in Guana should be a mixture of
two subspecies. Importantly, the Guana population has private alleles but GA-SC populations do
not, indicating that gene flow should be directionally from GA-SC to Florida.
Source and Introduced Populations
One of the concerns for a successful translocation is the preservation of genetic variability
for a certain length of time (Foose 1991). Selection, mutation, and genetic drift are three major
evolutionary forces to change the genetic composition in a population. Selection is not
applicable in this research because microsatellite DNA is not subject to selection. The
55
introduced populations did not have any private alleles, indicating that 30 years were not long
enough for mutation to change the allelic composition. Thus mutation can be safely ignored in
this research as stated in the methodology. Genetic drift is therefore the only possible
evolutionary force to change genetic composition or distribution of allele frequencies of mottled
duck populations in these 30 years. But even after 30 years of isolation, both pair-wise FST and
G-based test did not detect significant differences between the SCR population and its source
populations in Texas and Louisiana. Discrepancy between FST and G-based tests for the cluster
composed of SCR, LA, and TX populations was likely because the SCR population was a
mixture of LA and TX populations and the FST did not detect differentiation between them. With
87% of the introduced mottled ducks from Louisiana, the SCR population is still genetically
closest to the Louisiana population, followed by the Texas population. All of the GA-SC and
TX-LA populations were in the same cluster. Although 2% of the introduced mottled ducks were
from Florida (the Brevard population in this research), the genetic structure did not show any
similarity between GA-SC and the Brevard populations. Therefore, genetic drift has not
significantly changed genetic composition of the SCR population. The genetic variability and
distribution of allele frequencies of the introduced population have been well preserved in the
SCR for 30 years.
However, the genetic structure suggests that the genetic composition of the Bear and Rhetts
populations have drifted away from the original population. It is not clear how the 1,197 mottled
ducks were partitioned into the SCR and ACE Basin where the Bear Island is located, but the
occurrence of genetic drift likely was due to the small size of the Bear and Rhetts populations
relative to the SCR population because genetic drift is a stronger force to change allele
frequencies in small populations than in large populations (Frankham et al. 2002). The relatively
56
small population sizes of the Bear and Rhetts populations have allowed genetic drift to be
observed in 30 years.
Genetic Variability among Populations
Expected heterozygosity (He) is a conventional choice for measuring overall genetic
variation because it combines information on both number of alleles and their relative
frequencies (Hedrick et al. 1986). Homogeneous He values among mottled duck populations
showed equally variable genetic composition. However, He is correlated to number of alleles
and number of alleles varies with sample size. Therefore, adjusted number of alleles per locus or
allelic richness can be used as another indicator of genetic variability. In contrast to He values,
allelic richness was higher in TX-LA populations and their descendents in Georgia and South
Carolina than populations in Florida. The higher allelic richness can be explained by the fact that
difference in allelic richness is due to the private alleles in each population because common
alleles will not make any difference in allelic richness, and rare alleles contribute very little to He
because of their low frequencies. This difference can occur by chance, or it can suggest that the
subspecies in Texas and Louisiana probably have a longer history and/or larger population size
so that more alleles evolved. Another possibility is that mottled ducks in Florida had more
unstable demographic history such as bottleneck events (see below) than another subspecies in
Texas and Louisiana, and allelic richness was lost faster than He in the fluctuation of population
size (McCommas and Bryant 1990, Leberg 1992). However, private alleles in both subspecies
demonstrate that the two subspecies have been isolated from each other to some extent.
The FST value between TX-LA and Florida populations showed that only 2.5% of the
genetic variation was apportioned between the native populations of the two subspecies.
McCracken et al. (2001) detected 1.1 % of the mitochondrial DNA (mtDNA) variation
57
partitioned between Florida and TX-LA populations, and Williams et al. (2005) found 1 % and
5.4 % of the allozyme and microsatellite DNA variation, respectively, was partitioned between
Florida and Texas mottled ducks. Not surprisingly, microsatelite DNA exhibit a higher level of
differentiation than mtDNA and allozymes because of its higher mutation rate and neutrality to
selection even though the effective population size for mtDNA is fourfold that for autosomal
markers (Birky et al. 1989). Although the results vary among markers, results from this and
earlier studies showed low levels of differentiation between the two subspecies of mottled ducks.
This “shallow” population genetic structure has been observed on many species complexes
in the southeastern U.S. Avise (1996) illustrated several examples of species endemic to the
Florida peninsula that also exhibit mtDNA divergence between them and their taxonomic
counterpart on the main body of the continent, and many coastal species across a variety of taxa
with disjunct Atlantic and Gulf populations have shown mtDNA divergence also (Avise 1996 and
examples therein). However, not all species exhibited clear genetic differentiation. For species
with a lack of pronounced population differentiation, such as mottled ducks in this research,
similarity between populations may be due to contemporary gene flow or to retention of
ancestral polymorphisms in relatively short evolutionary time (Avise 1996).
With only two populations, it is hard to determine the relative contribution of gene flow
and recent isolation to the current similarity between populations. However, the introduced
population in Georgia and South Carolina has served as a reference to see how fast or how close
the two mottled duck subspecies could converge if gene flow has occurred. The GA-SC
population was originally from the subspecies in Texas and Louisiana. As mentioned previously,
within 30 years, it is expected that only genetic drift will change the composition of
microsatellite DNA. If there is no gene flow between any two of the groups, the FST value
58
between Florida and GA-SC populations should be equal to or larger than that between Florida
and TX-LA populations because the smaller population size in GA-SC may enhance the extent of
genetic drift and inflate FST values. However, the FST value between Florida and GA-SC
populations is smaller than that between Florida and Texas-Louisiana populations. For two
completely isolated populations, it is virtually impossible for the FST value to decline over time
by genetic drift.
The smaller FST value between Florida and GA-SC populations might be due to that 30
years ago, 2% mottled ducks in South Carolina were from Florida. If the 2% of mottled ducks
from Florida have contributed to the reduction of FST, then it is expected to see a larger FST value
between Florida and Rhetts or Bear populations because Rhetts and Bear populations have
experienced genetic drift as mentioned earlier. In contrast to the expectation, the smallest pair-
wise FST value between any Florida and GA-SC populations happened in Rhetts and Guana
populations. This fact demonstrates that the mottled ducks from Florida in the introduced
population did not make FST value between Florida and GA-SC smaller than that between
Florida and Texas-Louisiana populations.
Therefore, gene flow have occurred between Florida and GA-SC populations after mottled
ducks were introduced, and gene flow is most likely to occur between Rhetts and Guana
populations where smallest FST value was observed. Because the reduction of FST can be
observed in this short period of time, gene flow would have homogenized the two subspecies
(FST = 0) if gene flow had occurred between Florida and Texas-Louisiana populations. Thus the
similarity between the two subspecies should be due to a short history of isolation instead of
gene flow.
Bottleneck Events
59
Although the results were incongruent among the four tests for bottleneck events, each test
had homogeneous results for each population. This suggests that all the populations had similar
demographic history, and the bottleneck events were either ubiquitous or did not occur in all the
populations. It is not reasonable to suggest that all the populations had experienced bottleneck
events because severe decline in population size of TX-LA and FL populations have not been
documented. Consequences of bottleneck events on the genetic composition can be erased in a
few generations if the gene flow level is high because heterozygosity is restored quickly (Keller
et al. 2001). Without gene flow, the effects of bottleneck may last thousands of generations or on
the order of 1/u generations, where u is the mutation rate (Nei et al. 1975). If the mottled duck
populations in SACZ are not completely isolated from each other, bottleneck history may not be
resolved due to gene flow.
Assumptions for the four tests can also affect the results. The statistics, except M-value,
can only detect population bottleneck or expansion events that occurred a long time ago so that
allele number, frequency, size range, and distribution have been changed by mutation to some
extent. In this study, however, bottleneck events occurred due to the translocation of mottled
ducks are the major concern, and the history of the introduced populations is about 30 years only.
For these statistics, complete isolation among populations is assumed and the populations should
be at mutation-drift equilibrium before and after the bottleneck events. Also, the change in
population size assumed in the tests is dramatic (> 100 fold). More specifically, Reich et al.
(1999) suggested using 30 or more loci to achieve powers of 0.5 for the k-test and the g-test.
Thus the k-test and the g-test failed to detect any bottleneck events, possibly due to the number
of loci (9) used in this research. Spong and Hellborg (2002) also found these two tests failed to
detect known, moderate bottleneck events in a Scandinavian lynx (Lynx lynx) population. The
60
simulation-based beta-value and M-value depend on parameters such as pre-bottleneck,
bottleneck, and final population sizes as well as the mutation rate in the simulation (Kimmel et al.
1998, Garza and Williamson 2001), making application in real cases difficult. Therefore, these
tests may or may not suitable for the short-term demographic history of the mottled ducks in the
SACZ. The Wilcoxon sign-rank test is a more reasonable approach for this research.
Analysis with eight highly polymorphic microsatellite loci is sufficient to detect a recent
bottleneck event using Wilcoxon sign-rank test (Spencer et al. 2000). It is thus expected to
reveal bottleneck events with nine highly polymorphic loci. The Wilcoxon sign-rank tests
showed possible bottleneck history in Rhetts, IMC, and Orange populations. This result is also
supported indirectly by the beta-value. If LA and TX populations are assumed to be stable for a
long time and their beta-value is a reference, then Rhetts, IMC, and Orange populations have
significantly larger beta-values, indicating possible recent bottleneck events. The Rhetts
population was the southernmost breeding population established by the mottled ducks from
South Carolina (see Chapter I) and was the most possible population to have low number of
founder individuals. As discussed previously, allelic richness is sensitive to bottleneck events.
The Orange population has the lowest allelic richness among all mottled duck populations and it
did not have any private alleles. The IMC population has the second lowest allelic richness,
although by a slight difference, and a very low average number of private alleles. These facts,
combined with the two bottleneck tests, suggest that the three mottled duck populations had
recently experienced bottleneck events.
Gene Flow
Interpreting gene flow between two closely related subspecies is difficult because the low
amount of variation partitioned between populations may indicate that populations have not been
61
isolated long enough or that high level of gene flow has occurred. However, clear hierarchical
genetic structure and isolation by distance of mottled ducks along SACZ, close relationship
between Guana and TX-LA mottled duck populations, the smallest FST value observed between
Guana and Rhetts populations, and private alleles possessed by Guana population as well as
harvest data in Chapter I indicate that the Guana population was a mixture of Florida and TX-LA
mottled ducks and gene flow was directional from GA-SC to Florida. It may not make much
sense to estimate number of migrants between the introduced populations in SACZ and their
source populations in TX and LA because gene flow between the two groups of mottled ducks is
virtually impossible and sharing the same origin makes the estimate lack of biological
significance, but the results from both FST and private allele methods showed how similar they
are after the separation.
Williams et al. (2002) questioned whether the current gene flow among Florida mottled
duck populations is similar to or higher than the historical levels. If gene flow has been at this
high level for a long time, then random, short-range dispersal or lack of natal philopatry should
be the mechanism to cause gene flow. If the current gene flow is more intensive than the
historical level, then the change in land use may be the mechanism to deteriorate habitat quality
and force individuals to disperse (Williams et al. 2002). Because mottled ducks exhibit a high
rate of gene flow in all habitats where they occur, the contemporary gene flow should be similar
to the historical level. Mottled ducks have a potential to disperse despite their non-migratory
nature and small home range (Stutzenbaker 1988), and the dispersal is not sex or age-biased as
revealed in this research. Although this conflicts with mottled ducks’ presumed sedentary nature
(Stutzenbaker 1988), Fogarty and LaHart’s (1971) band recovery data did show a bi-model
pattern of dispersal distance, one within 14 km and one between 48 and 78 km from the release
62
sites (Table 1 in Fogarty and LaHart 1971). This bi-model pattern of dispersal distance may also
explain why gene flow and inbreeding tendency reveal by FIS were both detected.
Williams et al. (2005) were not able to distinguish South Carolina mottled ducks and
mallards using five microsatellite loci. They determined that the result was due to hybridization
between mallards and mottled ducks because their unpublished data showed clear differentiation
between mallards and mottled ducks. But in this research, South Carolina mottled ducks were
not differentiated from their source populations. If South Carolina mottled ducks have widely
hybridized with mallards, differentiation between mottled ducks in South Carolina and TX-LA
should have been obvious. Therefore, this research suggests that hybridization between mottled
ducks and mallards may not be a frequent event in South Carolina. Results from Williams et al.
(2005) may be due to low numbers of microsatellite loci and sample size.
Conclusion and Management Implications
Statistical tools using allele distribution to infer long-term migration rates are limited in
their ability to provide information relevant to short-term management (Moritz 1994). In this
research, these tools have been used to reflect both short-term connectedness among mottled
duck populations since the introduction of mottled ducks to South Carolina as well as long-term
connectedness between the two subspecies of mottled ducks. Results from this research thus are
applicable to management practices and interpretation of the evolutionary history of mottled
ducks.
When all mottled duck populations are considered, genetic structure clearly separates the
two subspecies except that the northernmost population (Guana) in Florida was in the cluster of
the TX-LA subspecies. In Texas, Louisiana, and Florida south to the Orange population, genetic
structure was not clear and mottled ducks can be considered a single population in each state.
63
The clear genetic structure observed along SACZ and multiple evidence have revealed gene flow
directionally from mottled ducks in GA-SC to Florida.
Bottleneck events and genetic drift were not supported by the data in the introduced
mottled duck population in the SCR, indicating that the mottled ducks in the SCR have
maintained the original genetic composition of the source populations for at least 30 years. This
result provides a safe estimate of minimal population size to establish a viable and genetically
stable population to survive 30 years. A population of smaller size may experience bottleneck
effect or genetic drift like the Rhetts population. If management practices seek to maintain a
sustainable mottled duck population without losing genetic variability in at least 30 years, a
minimum population size of 1,200 individuals would be necessary.
The two subspecies of mottled ducks are very similar genetically and the similarity should
be due to their short history of isolation. Slight but clear genetic separation of the two subspecies
indicates that they may be on the course of further differentiation. Gene flow between the two
subspecies was not found in previous research but it was detected in this research at the border of
Georgia and Florida. Management practices should seek to prevent or reduce this trend of gene
flow so A. f. fulvigula and A. f. maculosa can be maintained as distinct subspecies.
64
Table 4.1. Mottled duck sample sources, seasons, and sample sizes from South Carolina,
Georgia, Louisiana, Texas, and Florida during 2001-05.
Sample code Locality Lat °N Long °W Season Sample size
SCW4 Santee Coastal Reserve, SC 33°09’ 79°17’ Winter 04 13
SCW5 Santee Coastal Reserve, SC Winter 05 12
BEW3 Bear Island WMAa, SC 32°35’ 80°28’ Winter 03 13
BEW4 Bear Island WMA, SC Winter 04 36
RHW1 Rhetts Island, GA 31°20’ 81°25’ Winter 01 7
RHW2 Rhetts Island, GA Winter 02 11
ROCR Rockefeller SWRb, LA N/A N/A Winter 04 63
ROCM Rockefeller SWR, Superior Marsh, LA 29°40’ 92°38’ Summer 05 67
ROC2 Rockefeller SWR, Unit 2, LA N/A N/A Summer 04 92
RO14 Rockefeller SWR, Unit 14, LA 29°39’ 92°35’ Summer 05 48
MILR Miller estate (private), LA 29°44’ 92°54’ Summer 05 60
SABI Sabine NWRc, LA 29°53’ 93°34’ Summer 04 16
MCFS McFaddin NWR, Star Lake, TX 29°40’ 94°10’ Summer 04 33
MCFA McFaddin NWR, TX N/A N/A Winter 04 72
ANAH Anahuac NWR, TX 29°34’ 94°31’ Summer 04 61
GUW4 Guana River WMA, FL 30°03’ 81°20’ Winter 04 38
GUW5 Guana River WMA, FL Winter 05 21
MES4 Merritt Island NWR, FL 28°38’ 80°42’ Summer 04 11
MEW4 Merritt Island NWR, FL Winter 04 8
BRS4 T. M. Goodwin WMA, Broadmoor Marsh Unit, FL 27°52’ 80°41’ Summer 04 31
BRW4 T. M. Goodwin WMA, Broadmoor Marsh Unit, FL Winter 04 21
TMW4 T. M. Goodwin WMA, T.M. Goodwin Unit, FL 27°52’ 80°41’ Winter 04 28
DUDA Duda vegetable farm, FL 26°46’ 80°40’ Summer 04 11
IMCP IMC pit mine, FL 27°45’ 81°47’ Summer 04 14
ORAN Orange Creek SGAd FL 29°27’ 82°04’ Summer 04 20
Total 807 a Wildlife management area
b State wildlife refuge
c Nation wildlife refuge
d Small-game hunting area
65
Table 4.2. Sequences and motifs of the nine primer sets used for the final genotyping of mottled
ducks. All primer sets were modified from Maak et al. (2003). Other primer sets tested were five
from Fields and Scribner (1997) (Sfiµ 1, 3, 4, 5, and 7), two from Buchholz et al. (1998) (Bca 6,
11), and eight from Maak et al. (2003) (APH06, 12, 13, 16, 19, 20, 23, and 25).
Locus Motif Primer sequence (F: forward, R: reverse, 5’-3’)
APH02 (CA)3TA(CA)7 F: GGAAACAGCTATGACCAT AAC ACA CGC GCA GCA GAG R: GTTT CTT GTC GTC AGC CAG GGG TTT
APH04 (CA)14 F: GTTT GCC CCT CGG TAT TGT TTT C R: CAGTCGGGCGTCATCA GCT CTG AAG GGC ATT ATT TAG
APH05 (CA)8 F: GTTT CTT GGA CAA AAC AGG ACT T R: CAGTCGGGCGTCATC ACA GGA GAA AAC AGA GGT AA
APH08 (CA)12 F: GTTT AAA GCC CTG TGA AGC GAG CTA R: CAGTCGGGCGTCATCA TGT GTG TGC ATC TGG GTG TGT
APH15 (CA)9 F: GTT TGA ATA TGC GTG GCT GAA R: CAGTCGGGCGTCAT CAG TGA GGA ATG TGT TTG AGT T
APH17 (CA)14 F: CAGTCGGGCGTCATCA GGA CAT TTT CAA CCA TAA ACT C R: GTTT CAT CCA TGA CAG ACA GAA GA
APH18 (CA)8 F: GT TTC TGG CCT GAT AGG TAT GAG R: CAGTCGGGCGTCATCA GAA TTG GGT GGT TCA TAC TGT
APH21 (CA)8 F: GGAAACAGCTATGACCAT CTT AAA GCA AAG CGC ACG TC R: GTTT AGA TGC CCA AAG TCT GTG CT
APH24 (CA)2TA(CA)9 F: CAGTCGGGCGTCATCA TCA ACC AGT GGT CAG AGA AAA ACA G R: GTTT AGG TCA GCC CCC ATT TTA GTA CTT A
66
Table 4.3. Descriptive statistics for each locus across 10 newly defined mottled duck populations.
Mottled duck samples were collected from 2001 thorough 2005 from Santee Coastal Reserve, SC,
Bear Island Wildlife Management Area (WMA), SC, Rhetts Island, Altamaha WMA, GA, Guana
River WMA, FL, Merritt Island National Wildlife Refuge (NWR), FL, T. M. Goodwin WMA,
FL, Duda vegetable farm, FL, IMC pit mine, FL, Orange Creek Small-game Hunting Area, FL,
Rockefeller State Wildlife Refuge, LA, Miller estate (private), LA, Sabine NWR, LA, McFaddin
NWR, TX, and Anahuac NWR, TX.
Locus Number of alleles He Ho FIS Sample size APH02 18 0.859 0.607 0.293 776 APH04 35 0.889 0.843 0.052 804 APH05 8 0.561 0.407 0.275 799 APH08 18 0.860 0.836 0.029 779 APH15 7 0.523 0.555 - 0.060 800 APH17 12 0.813 0.729 0.104 800 APH18 10 0.458 0.474 - 0.036 806 APH21 14 0.850 0.639 0.249 794 APH24 15 0.784 0.668 0.147 802 Average 15.2 0.733 0.640 0.127 795.6
He = expected heterozygosity
Ho = observed heterozygosity
FIS = inbreeding coefficient
67
Table 4.4. P-values for the Hardy-Winberg Equilibrium (HWE) test for each locus and
sample. An asterisk indicates significant deviation from HWE. The sequential Bonferroni
correction was used for each locus and the initial significance level was adjusted to alpha
= 0.002 (= 0.05/25).
Sample codea State APH02 APH04 APH05 APH08 APH15 APH17 APH18 APH21 APH24
SCW4 SC 0.005 0.035 0.344 0.754 0.333 0.384 1.000 0.065 0.555
SCW5 SC <0.001* 0.654 0.203 0.998 0.139 0.018 1.000 0.325 0.431
BEW3 SC 0.016 0.424 1.000 0.414 0.244 0.384 1.000 0.039 0.077
BEW4 SC <0.001* 0.019 0.027 0.730 0.407 0.486 1.000 0.003 0.169
RHW1 GA 0.060 1.000 1.000 1.000 1.000 0.515 1.000 0.044 0.490
RHW2 GA 0.003 0.745 1.000 0.593 0.009 0.943 1.000 0.157 0.238
ROCR LA <0.001* 0.244 0.605 0.834 0.259 0.326 0.423 0.005 0.047
ROCM LA <0.001* 0.602 <0.001* 0.437 0.006 0.101 0.888 <0.001* 0.549
ROC2 LA <0.001* 0.998 0.002 0.378 0.291 0.089 0.002 <0.001* 0.027
RO14 LA <0.001* 0.799 0.212 0.118 0.056 0.772 0.382 <0.001* 0.017
MILR LA 0.024 0.540 0.073 0.811 0.084 0.269 0.505 0.140 0.015
SABI LA <0.001* 0.735 0.383 0.179 0.319 0.488 0.565 0.011 0.010
MCFS TX <0.001* 0.941 0.016 0.433 0.884 0.003 0.266 0.403 <0.001*
MCFA TX 0.090 0.306 0.039 0.470 0.075 0.057 0.602 0.057 0.001
ANAH TX <0.001* 0.852 <0.001* 0.052 0.234 0.175 0.175 <0.001* 0.001
GUW4 FL 0.070 <0.001* 0.011 0.451 0.719 <0.001* 0.198 0.421 0.811
GUW5 FL 0.862 0.308 0.123 0.747 1.000 0.003 0.902 0.123 0.059
MES4 FL 0.018 0.257 0.138 0.807 1.000 0.110 1.000 0.098 0.018
MEW4 FL 0.347 0.283 0.135 0.215 0.217 0.087 1.000 0.037 0.034
BRS4 FL 0.162 <0.001* 0.256 0.478 0.041 0.019 0.034 0.086 0.083
BRW4 FL 0.149 <0.001* 0.010 0.608 1.000 0.044 1.000 0.112 0.911
TMW4 FL 0.050 0.013 0.052 0.084 1.000 0.197 1.000 <0.001* 0.004
DUDA FL 0.220 0.003 0.882 0.263 1.000 0.800 0.307 0.028 0.715
IMCP FL 0.009 0.227 0.240 0.595 1.000 0.674 1.000 <0.001* 0.718
ORAN FL 0.717 0.175 0.014 0.133 1.000 0.830 0.169 0.869 0.866 a Refer to Table 4.1 for location, season, and size for each sample.
68
Table 4.5. Ten newly defined mottled duck populations and samples combined.
Population code Samples combineda Sample size
SCR SCW4, SCW5 25
Bear BEW3, BEW4 49
Rhetts RHW1, RHW2 18
Guana GUW4, GUW5 59
Brevard MES4, MEW4, BRS4, BRW4, TMW4 99
Duda DUDA 11
IMC IMCP 14
Orange ORAN 20
LA MILR, ROCR, ROCM, RO14, ROC2, SABI 346
TX ANAH, MCFS, MCFA 166
Total 807 a Refer to Table 4.1 for location, season, and size of each sample.
69
Table 4.6. Pair-wise FST (above diagonal) and p-values for G-based test (below diagonal) for the
10 newly defined populations. Significant FST values are indicated by asterisk.
SCR Bear Rhetts Guana Brevard Duda IMC Orange LA TX
SCR 0.002 0.011 0.027* 0.029* 0.034* 0.022* 0.034* <0.001 0.001
Bear 0.353 0.018* 0.031* 0.041* 0.037* 0.026* 0.049* 0.006* 0.009*
Rhetts 0.261 0.019 0.019* 0.036* 0.030* 0.033* 0.038* 0.019* 0.017*
Guana <0.001* <0.001* <0.001* 0.043* 0.030* 0.038* 0.052* 0.033* 0.032*
Brevard <0.001* <0.001* <0.001* <0.001* 0.001 0.017* 0.009 0.035* 0.036*
Duda 0.025 0.004* 0.011 <0.001* 0.565 0.005 0.014 0.036* 0.038*
IMC 0.002* <0.001* <0.001* <0.001* 0.006 0.177 0.033 0.028* 0.032*
Orange <0.001* <0.001* <0.001* <0.001* <0.001* 0.003* <0.001* 0.043* 0.043*
LA 0.032 <0.001* <0.001* <0.001* <0.001* <0.001* <0.001* <0.001* 0.002*
TX 0.039 <0.001* <0.001* <0.001* <0.001* <0.001* <0.001* <0.001* 0.001*
70
Table 4.7. Genetic characteristics of microsatellite loci in ten mottled duck populations. A,
observed number of alleles, Ho, observed heterozygosity, He, expected heterozygosity, FIS,
inbreeding coefficient.
Locus Population APH02 APH04 APH05 APH08 APH15 APH17 APH18 APH21 APH24 SCR A 8 16 4 10 4 9 3 10 10 Ho 0.38 0.88 0.44 0.87 0.67 0.60 0.44 0.68 0.72 He 0.83 0.92 0.48 0.87 0.58 0.83 0.37 0.85 0.80 FIS 0.54 0.04 0.08 0.00 -0.16 0.28 -0.19 0.20 0.10 Bear A 10 15 4 13 3 9 3 12 11 Ho 0.53 0.92 0.29 0.84 0.57 0.80 0.47 0.67 0.71 He 0.87 0.88 0.37 0.83 0.48 0.83 0.48 0.86 0.81 FIS 0.39 -0.05 0.22 -0.01 -0.19 0.04 0.02 0.22 0.12 Rhetts A 9 11 4 7 3 8 4 10 9 Ho 0.47 1.00 0.65 0.94 0.28 0.89 0.50 0.59 0.89 He 0.88 0.91 0.63 0.87 0.54 0.82 0.48 0.88 0.81 FIS 0.47 -0.10 -0.03 -0.08 0.48 -0.09 -0.04 0.33 -0.10 Guana A 12 17 5 10 4 7 6 10 9 Ho 0.74 0.76 0.48 0.79 0.51 0.47 0.59 0.69 0.66 He 0.81 0.90 0.59 0.80 0.53 0.73 0.58 0.77 0.77 FIS 0.09 0.16 0.19 0.01 0.04 0.36 -0.02 0.10 0.14 Brevard A 13 22 5 12 4 8 4 9 12 Ho 0.72 0.67 0.44 0.72 0.54 0.67 0.44 0.53 0.63 He 0.83 0.90 0.63 0.78 0.50 0.77 0.38 0.80 0.75 FIS 0.13 0.26 0.30 0.08 -0.08 0.13 -0.16 0.34 0.16 Duda A 8 10 4 7 3 6 3 6 6 Ho 0.64 0.64 0.80 1.00 0.64 0.82 0.45 0.45 0.73 He 0.81 0.86 0.71 0.81 0.57 0.75 0.51 0.81 0.74 FIS 0.21 0.26 -0.13 -0.23 -0.12 -0.09 0.12 0.44 0.01 IMC A 10 10 3 7 2 5 2 4 7 Ho 0.64 0.79 0.57 0.85 0.50 0.64 0.36 0.21 0.71 He 0.87 0.88 0.67 0.87 0.49 0.75 0.39 0.72 0.80 FIS 0.26 0.10 0.15 0.02 -0.02 0.15 0.08 0.71 0.11 Orange A 9 10 4 7 2 4 3 7 4 Ho 0.75 0.70 0.50 0.60 0.50 0.80 0.40 0.75 0.60 He 0.81 0.85 0.73 0.77 0.47 0.69 0.48 0.81 0.63 FIS 0.07 0.18 0.32 0.22 -0.06 -0.16 0.17 0.07 0.05 LA A 15 25 7 16 5 10 8 14 12 Ho 0.57 0.88 0.39 0.85 0.59 0.78 0.48 0.63 0.69 He 0.85 0.87 0.51 0.86 0.50 0.82 0.46 0.85 0.79 FIS 0.33 -0.01 0.24 0.01 -0.18 0.05 -0.04 0.26 0.13 TX A 12 19 5 13 5 9 5 11 9 Ho 0.62 0.89 0.35 0.90 0.53 0.73 0.47 0.72 0.60 He 0.87 0.87 0.50 0.87 0.54 0.82 0.45 0.85 0.78 FIS 0.29 -0.02 0.30 -0.03 0.02 0.11 -0.04 0.15 0.23
71
Table 4.8. Partition of the total genetic variance of mottled duck populations. Three groups are
Texas-Louisiana, Georgia-South Carolina, and Florida.
Source of variation df Sum of squares
Mean square
Variance components
Percentage of variation
Among groups 2 58.826 29.413 0.062 1.87 Within groups 1611 5261.618 3.266 3.266 98.13 Total 1613 5320.444 32.679 3.328
72
Table 4.9. Results of tests of bottleneck events in mottled duck populations. The
Wilcoxon sign-rank test shows p-value for each population. The k-test shows
the number of positive k-values out of nine loci.
Population Wilcoxon sign-rank test k-test g-test Beta-value M-value
SCR 0.213 6 2.01 5.47 0.42
Rhetts 0.0
0.6
0.6
0.2
0.0
0.5
0.0
19* 5 3.36 10.13 0.41
Bear 0.248 7 1.70 4.69 0.42
Guana 33 8 1.52 5.40 0.40
Brevard 33 5 3.88 7.30 0.40
Duda 48 6 1.00 6.99 0.37
IMC 0.010* 4 3.55 8.98 0.47
Orange 05* 5 1.74 8.26 0.43
LA 90 6 2.19 6.96 0.39
TX 82 6 2.03 5.42 0.41 * significant at alpha = 0.05.
73
Table 4.10. Estimated number of migrants per generation between each pair of mottled duck
populations. Above diagonal, FST-based estimates; below diagonal, private-allele method
estimates.
SCR Bear Rhetts Guana Brevard Duda IMC Orange LA TX
SCR 102.3 22.8 9.1 8.2 7.1 11.1 7.1 249.8 192.4
Bear 5.7 13.4 7.9 5.8 6.5 9.6 4.9 42.7 26.4
Rhetts 2.5 3.9 12.9 6.6 8.1 7.4 6.3 12.9 14.9
Guana 4.3 6.8 5.5 5.5 8.1 6.3 4.5 7.3 7.5
Brevard 9.2 10.4 7.3 15.9 186.3 14.4 26.6 6.8 6.7
Duda 2.5 3.6 1.6 3.8 12.8 52.9 17.5 6.7 6.3
IMC 2.1 2.5 1.4 2.0 7.4 1.0 7.3 8.8 7.5
Orange 2.0 2.5 1.4 3.2 7.7 1.5 1.0 5.6 5.6
LA 33.5 64.4 19.9 17.8 28.2 9.3 6.3 8.2 110.4
TX 12.5 15.6 5.5 8.0 13.0 4.2 2.7 3.0 247.5
74
Figure 4.1. Locations from which samples of mottled ducks were obtained, 2001-2005, for
genetic analysis. 1: Santee Coastal Reserve; 2: Bear Island Wildlife Management Area; 3: Rhetts
Island, Altamaha WMA; 4: Guana River WMA; 5: Merritt Island National Wildlife Refuge
(NWR); 6: T. M. Goodwin WMA; 7: Duda vegetable farm; 8: IMC pit mine; 9: Orange Creek
Small-game Hunting Area; 10: Rockefeller State Wildlife Refuge; 11: Miller estate (private); 12:
Sabine NWR; 13: McFaddin NWR; 14: Anahuac NWR. The 10 newly defined populations are
SCR (1), Bear (2), Rhetts (3), Guana (4), Brevard (5 and 6, both in Brevard Co.), Duda (7), IMC
(8), Orange (9), LA (10, 11, and 12), and TX (13 and 14).
75
Figure 4.2. Population structure of the 10 newly defined mottled duck populations. The
structure was established using Reynold’s (1983) genetic distance and UPGMA algorithm.
Significant FST values (p<0.05) were indicated by an asterisk. P-values were from the G-based
tests. Length of branches does not reflect any relative relationship between populations.
76
Figure 4.3. Population structure of the 10 newly defined mottled duck populations established
by using Reynold’s (1983) genetic distance and Neighbor-Joining algorithm.
77
y = -0.6251x + 2.5232R2 = 0.1256
0
0.5
1
1.5
2
2.5
1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9
Log10(geographic distance)
Log 1
0(nu
mbe
r of m
igra
nts)
Figure 4.4. Log10(number of migrants) plotted against log10(geographic distance) for
the five mottled duck populations (SCR, Bear, Rhetts, Orange, and Guana) along
South Atlantic Coastal Zone.
78
0
2
4
6
8
10
12
14
SCR Bear Rhetts Guana Brevard Duda IMC Orange LA TX
Population
Aver
age
num
ber o
f alle
les,
priv
ate
alle
les,
or a
llelic
ric
hnes
s pe
r loc
us
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Het
eroz
ygos
ity
Figure 4.5. Allelic pattern across 10 newly defined mottled duck populations in South Carolina,
Georgia, Florida, Louisiana, and Texas. Solid line: expected heterozygosity; broken line:
observed heterozygosity; open bar: average observed number of alleles per locus, black bar:
average number of private alleles per locus, slash bar: average allelic richness per locus. SCR:
Santee Coastal Reserve, SC; Bear: Bear Island Wildlife Management Area (WMA); Rhetts:
Rhetts Island, Altamaha WMA, GA; Guana: Guana River WMA, FL; Brevard: Brevard County,
FL; Duda: Duda vegetable farm, FL; IMC: IMC pit mine, FL; Orange: Orange Creek Small-
game Hunting Area, FL; LA: Louisiana, TX: Texas.
79
(A)
-0.5-0.4
-0.3-0.2
-0.10.0
0.10.2
0.30.4
AIc
Male
Female
(B)
-0.6-0.5-0.4-0.3-0.2-0.10.00.10.20.30.4
AIc
AHY
HY
Figure 4.6. Average assignment index correction (AIc) for sex and age categories of mottled
ducks in Florida, Louisiana, and Texas. (A) sex-biased disperal; (B) age-biased dispersal. AHY,
after hatch year; HY, hatch year. Florida sample was all from Brevard population. Sample sizes
are shown in parentheses.
80
CHAPTER 5
CONCLUSIONS
The translocation of mottled ducks from their native habitats to South Carolina has been
successful according to the definition by Griffith et al. (1989). Index of harvest per unit effort
showed an apparent increase in abundance of mottled ducks at the two Wildlife Management
Areas (Santee Coastal Reserve and Bear Island) where mottled ducks were released during 1975-
1982. The translocation is successful because not only the introduced birds established self-
sustainable populations but also the genetic variability has been maintained for 30 years. The
success provided a safe estimate of minimum population size to establish a viable and genetically
stable waterfowl population to survive 30 years. In Florida, shallow wetlands preferred by
mottled ducks have been lost due to agriculture and urban development and there is risk of
continued loss (Florida Fish and Wildlife Conservation Commission 2006a). If Florida mottled
ducks were to be maintained in fragmented or isolated habitats, 1,200 birds could serve as a
reference to estimate a reasonable population size for a particular conservation plan.
However, consequences of the introduction of mottled ducks are beyond expectations.
Two new breeding populations were established at Savannah Confined Disposal Facilities in
South Carolina and Rhetts Island in Georgia. Genetic data suggested that these two populations
were established by mottled ducks from South Carolina instead of Florida. This southward
expansion was unexpected because of mottled ducks’ non-migratory nature and fidelity to natal
areas. The expansion also caused gene flow from the subspecies Anas fulvigula maculosa in
Georgia and South Carolina to the subspecies A. f. fulvigula in Florida. This directional gene
81
flow was revealed by the population structure, smaller genetic distance between Georgia and
Florida populations than that among native populations, and negative correlation between genetic
and geographic distances. Gene flow has changed the genetic composition of mottled ducks at
the Guana River Wildlife Management Area (WMA) because this population is genetically
closer to mottled ducks in Georgia and South Carolina than to those in Florida, but private alleles
of Guana population indicated that this population is a mixture of two subspecies. This
unexpected gene flow should concern biologists who have attempted to keep Florida mottled
ducks as a unique subspecies.
Habitat management could be a way to control the gene flow from mottled ducks in
Georgia to Florida. In this research, water depth was found to be the only factor that associated
with habitat use by mottled ducks at the Bear Island WMA in South Carolina. Mottled ducks
preferred water shallower than 15 cm and seldom used water deeper than 20 cm. Management
practices may deepen water level at some impoundments close to the border of Georgia and
Florida to discourage use by mottled ducks. However, this operation may also affect habitat use
by other water birds. Trapping and removing mottled ducks is another possibility to control the
population. Georgia Department of Natural Resources has successfully conducted the first
trapping and banding on mottled ducks at the Rhetts Island in summer 2006 (G. Balcom, pers.
comm.). This experience may enhance further studies on mottled ducks such as radio telemetry
to confirm their dispersal pattern, and the experience can also be used to remove a mottled duck
population in this area if the rate of southward dispersal is a concern.
The translocation of this non-migratory waterfowl species has caused unexpected
expansion and breakdown of geographic and genetic isolation between two subspecies. If the
introduced mottled ducks were from Florida, gene flow would not be a concern after these 30
82
years. The introduced mottled duck population demonstrated that the consequences of a
translocation are unpredictable and may be unfavorable. Future translocation of any species
should be limited to conservation purposes only. If translocation is necessary, source
populations should be chosen from close proximity to the release sites and genetic compositions
of both source and recipient populations should be evaluated to prevent breakdown of isolation
between species or populations.
83
LITERATURE CITED
Avise, J. 1996. Toward a regional conservation genetics perspective: phylogeography of faunas
in the southeastern United States. In Conservation genetics: case histories from nature. J. C.
Avise and J. L. Hamrick eds. Chapman & Hall, New York, New York, USA.
Balloux, F. and N. Lugon-Moulin. 2002. The estimation of population differentiation with
microsatellite markers. Molecular Ecology 11:155-165.
Batzer, D. P., M. McGee, V. H. Resh, and R. R. Smith. 1993. Characteristics of invertebrates
consumed by mallards and prey response to wetland flooding schedules. Wetlands 13:41-
49.
Batzer, D. P. and S. Wissinger. 1996. Ecology of insect communities in nontidal wetlands.
Annual Review of Entomology 41:75-100.
Beckett, D. C., T. P. Aartila, and A. C. Miller. 1992. Invertebrate abundance on Potamogeton
nodus: effects of plant surface area and condition. Canadian Journal of Zoology 70:300-
306.
Bellrose, F. C. 1980. Ducks, geese and swans of North America. Stackpole Books, Harrisburg,
Pennsylvania, USA.
Bergey, E. A., S. F. Balling, J. N. Collins, G. A. Lamberti, and C. H. Resh. 1992. Bionomics of
invertebrates within an extensive Potamogeton pectinatus bed of a California marsh.
Hydrobiologia 234:15-24.
84
Birkey, C. W., P. Fuerst, and T. Maruyama. 1989. Organelle diversity under migration,
mutation and drift: equilibrium expectations, approach to equilibrium, effects of
heteroplasmic cells, and comparisons to nuclear genes. Genetics 121:613-627.
Boutin-Ganache, I., M.Raposo, M. Raymond, and C. F. Deschepper. 2001. M13-tailed primers
improve the readability and usability of microsatellite analyses performed with two different
allele-sizing methods. BioTechniques 31: 24-28.
Breininger, D. R. and R. B. Smith. 1990. Waterbird use of coastal impoundments and
management implications in east-central Florida. Wetlands 10:223-241.
Brigham, A. R., W. U. Brigham and A. Gnilka (eds.). 1982. Aquatic insects and oligochaetes of
North and South Carolina. Midwest Aquatic Enterprises, Mahomet, IL.
Brownstein, M. J., J. D. Carpenter, and J. R. Smith. 1996. Modulation of non-templated
nucleotide addition by Taq DNA polymerase: primer modifications that facilitate
genotyping. BioTechniques 20:1004-1010.
Buchholz, W. G., J. M. Pearce, B. J. Pierson, and K. T. Scribner. 1998. Dinucleotide repeat
polymorphisms in waterfowl (family Anatidae): characterization of a sex-linked (Z-specific)
and 14 autosomal loci. Animal Genetics 29: 323-325.
Charlesworth, B. 1998. Measures of divergence between populations and the effect of forces
that reduce variability. Molecular Biology and Evolution 15:538-543.
Cooper, C. B. and S. H. Anderson. 1996. Significance of invertebrate abundance to dabbling
duck brood use of created wetlands. Wetlands 16:557-563.
Cornuet, J. M. and G. Luikart. 1996. Description and power analysis of two tests for detecting
recent bottlenecks from allele frequency data. Genetics 144:2001-2014.
85
Cox, Jr., R. R., M. A. Hanson, C. C. Roy, N. H. Euliss, Jr., D. H. Johnson, and M. G. Butler.
1998. Mallard growth rates and survival in relation to aquatic invertebrates. Journal of
Wildlife Management 62:124-133.
Cox, Jr., R. R. and J. A. Kadlec. 1995. Dynamics of potential waterfowl foods in Great Salt
Lake marshes during summer. Wetlands 15:1-8.
Cyr, H. and J. A. Downing. 1988. The abundance of phytophilous invertebrates on different
species of submerged macrophytes. Freshwater Biology 20:365-374.
Danell, K. 1979. Reduction of aquatic vegetation following the colonization of a Northern
Swedish Lake by the muskrat, Ondatra zibethica. Oecologia 38:101-106.
D’Antonio, C., L. A. Meyerson, and J. Denslow. 2001. Exotic species and conservation,
research needs. In Conservation Biology, research priorities for the next decade, ed. M. E.
Soule and G. H. Orians, pp. 59-80. Island Press, Washington D.C., USA.
Dobson, A. P. and R. M. May. 1986. Disease and conservation. In Conservation Biology: The
Science of Scarcity and Diversity, ed. M. E. Soule, pp. 345-365. Sinauer, Sunderland,
Massachusetts, USA.
Downing, J. A. 1986. A regression technique for the estimation of epiphytic invertebrate
populations. Freshwater Biology 16:161-173.
El Mousadik, A. and R. J. Petit. 1996. High level of genetic differentiation for allelic richness
among populations of the argan tree [Argania spinosa (L.) Skeels] endemic to Morocco.
Theoretical and Applied Genetics 92:832-839.
Elsey, R. M., P. L. Trosclair, III, and J. T. Linscombe. 2004. The American alligator as a
predator of mottled ducks. Southeastern Naturalist 3:381-390.
86
Euliss, Jr., N. H., R. L. Jarvis, and D. S. Gilmer. 1991. Feeding ecology of waterfowl wintering
on evaporation ponds in California. Condor 93:582-590.
Excoffier, L., P. Smouse, and J. Quattro. 1992. Analysis of molecular variance inferred from
metric distances among DNA haplotypes: Application to human mitochondrial DNA
restriction data. Genetics 131:479-491.
Favre, L. F. Balloux, J. Goudet, and N. Perrin. 1997. Female-biased dispersal in the
monogamous mammal Crocidura russula: evidence from field data and microsatellite
patterns. Proceedings of the Royal Society of London Series B 264:127-132.
Fields, R. L. and K. T. Scribner. 1997. Isolation and characterization of novel waterfowl
microsatellite loci: cross-species comparisons and research applications. Molecular Ecology
6:199-202.
Fitch, H. S. and H. W. Shirer. 1971. A radiotelemetric study of spatial relationships in some
common snakes. Copeia 1971:118-128.
Florida Fish and Wildlife Conservation Commission. 2006a. A Conservation Plan for the
Florida Mottled Duck 2004-2009. Florida Fish and Wildlife Conservation Commission.
Tallahassee, Florida. http://myfwc.com/duck/Mottled_Ducks/mottled_duck.htm.
_____. 2006b. Florida’s Mottled Duck Population Monitoring. Florida Fish and Wildlife
Conservation Commission. Tallahassee, Florida.
http://myfwc.com/duck/Mottled_Ducks/modu_survey%202000.htm.
Fogarty, M. J. and D. E. LaHart. 1971. Florida Duck movements. Proceedings of Annual
Conference of Southeast Association of Fish and Wildlife Agencies 25:191-201.
Foose, T. J. 1991. Viable population strategies for re-introduction programmes. Symposia of
the Zoological Society of London 62:165-172.
87
Frankham, R., J. D. Ballou, and D. A. Briscoe. 2002. Introduction to conservation genetics.
Cambridge University Press. Cambridge, UK.
Garza, J. C. and E. G. Williamson. 2001. Detection of reduction in population size using data
from microsatellite loci. Molecular Ecology 10:305-318.
Gibbs, H. L., R. J. G. Dawson, and K. A. Hobson. 2000. Limited differentiation in
microsatellite DNA variation among northern populations of the yellow warbler: evidence
for male-biased gene flow? Molecular Ecology 9:2137-2147.
Goodman, D. 1987. How do any species persist? Lessons for conservation biology.
Conservation Biology 1: 59-62.
Gordon, D. H., B. T. Gray, R. D. Perry, M. B. Prevost, T. H. Strange, and R. K. Williams. 1989.
South Atlantic Coastal Wetlands. Pp. 57-92 in L. M. Smith, R. L. Pederson, and R. M.
Kaminski, eds. Habitat management for migrating and wintering waterfowl in North
America. Texas Tech University Press, Lubbock, Texas, USA.
Goudet, J., M. Raymond, T. De Meeus, and F. Rousset. 1996. Testing differentiation in diploid
populations. Genetics 144:1933-1940.
Goudet, J. 1995. FSTAT (Version 1.2): A computer program to calculate F-statistics. Journal of
Heredity 86: 485-486. http://www.unil.ch/izea/softwares/fstat.html.
Gray, P. N. 1993. The biology of a southern mallard: Florida’s mottled duck. Ph.D. Diss.,
University of Florida, Gainesville, Florida, USA.
Greig, J. C. 1979. Principles of genetic conservation in relation to wildlife management in
southern Africa. South African Journal of Wildlife Researches 9:57-78.
Griffith, B., J. M. Scott, J. W. Carpenter, and C. Read. 1989. Translocation as a species
conservation tool. Science 245:477-480.
88
Heard, R.W. 1982. Guide to common tidal marsh invertebrates of the northeastern Gulf of
Mexico. Mississippi Alabama Sea Grant Consortium MASGP-79-004.
Hedrick, P. W. 1999. Highly variable loci and their interpretation in evolution and conservation.
Evolution 53:313-318.
Hedrick, P. W., P. R. Brussard, F. W. Allendorf, J. A. Beardmore, and S. Orzack. 1986. Protein
variation, fitness, and captive propagation. Zoo Biology 5:91-99.
Holsinger, K. E. and R. J. Mason-Gamer. 1996. Hierarchical analysis of nucleotide diversity in
geographically structured populations. Genetics 142:629-639.
Hughes, J., K. Goudkamp, D. Hurwood, M. Hancock, and S. Bunn. 2003. Translocation causes
extinction of a local population of the freshwater shrimp Paratya australiensis.
Conservation Biology 17:1007-1012.
Hurlbert, S. H. 1971. The nonconcept of species diversity: a critique and alternative parameters.
Ecology 52:577-586.
_____. 1984. Pseudoreplication and the design of ecological field experiments. Ecological
Monograph 54:187-211.
IUCN. 2006. IUCN position statement on translocation of living organisms. Species Survival
Commission. http://www.iucn.org/themes/ssc/publications/policy/transe.htm.
Jackson, J. E. 1988. Terrestrial mammalian pests in Argentina – an overview. Proceedings of
the Vertebrate Pests Conference:196-198. http://digitalcommons.unl.edu/vpcthirteen/41
Jin, L. and R. Chakraborty. 1995. Population structure, stepwise mutations, heterozygote
deficiency and their implications in DNA forensics. Heredity 74:274-285.
Johnsgard, P. A. 1961. Evolutionary relationships among the North American mallards. Auk
78:3-43.
89
Johnson, F. A., F. Montalbano III, J. D. Truitt, and D. R. Eggeman. 1991. Distribution,
abundance, and habitat use by mottled ducks in Florida. Journal of Wildlife Management
55:476-482.
Johnson, T. W. 1973. The wing molt of the Florida Duck. Condor 85:77-78.
Joyner, D. E. 1980. Influence of invertebrates on pond selection by ducks in Ontario. Journal
of Wildlife Management 44:700-705.
Joyner, D. E., R. D. Arthur, and B. N. Jacobson. 1984. Winter weight dynamics, grain
consumption and reproductive potential in Canada Geese. Condor 86:275-280.
Kaminski, R. M. and H. H. Prince. 1981. Dabbling duck activity and foraging responses to
aquatic macroinvertebrates. The Auk 98:115-126.
Keller, L. F., K. J. Jeffery, P. Arcese, M. A. Beaumont, W. M. Hochachka, J. N. M. Smith, and
M. W. Bruford. 2001. Immigration and the ephemerality of a natural population bottleneck:
evidence from molecular markers. Proceedings of the Royal Society of London Series B
268:1387-1394.
Kimmel, M., R. Chakraborty, J. P. King, M. Bamshad, W. S. Watkins, and L. B. Jorde. 1998.
Signatures of population expansion in microsatellite repeat data. Genetics 148:1921-1930.
Kimura, M. and T. Ohta. 1978. Stepwise mutation model and distribution of allele frequencies
in a finite population. Proceedings of the National Academy of Sciences USA 75:2868-72.
King, J. R. 1980. Energetics of avian moult. International Ornithological Congress 17:312-317.
Kleiman, D. G., B. B. Beck, J. M. Dietz, and L. A. Dietz. 1991. Cost of a re-introduction and
criteria for success: accounting and accountability in the golden lion tamarin conservation
program. Pp. 125-142 in J. H. W. Gipps, ed. Beyond captive breeding: Re-introducing
endangered mammals to the wild. Clarendon Press, Oxford, UK.
90
Kumar, S., K. Tamura, and M. Nei. 2004. MEGA3: integrated software for molecular
evolutionary genetics analysis and sequence alignment. Briefings in Bioinformatics 5:150-
163.
Lack, D. 1967. The significance of clutch-size in waterfowl. Wildfowl 18:125-128.
LaHart, D. E. and G. W. Cornwell. 1969. Habitat preference and survival of Florida duck
broods. Proceedings of Annual Conference of Southeast Association of Fish and Wildlife
Agencies 23:117-121.
Leberg, P. L. 2002. Estimating allelic richness: effects of sample size and bottlenecks.
Molecular Ecology 11:2445-2449.
Lewis, P. O. and D. Zaykin. 2001. Genetic Data Analysis: computer program for the analysis of
allelic data. Version 1.0. http://lewis.eeb.uconn.edu/lewishome/software.html
Lotter, C. F. 1969. Habitat requirements and procedures for measuring various population
parameters of the Florida duck, Anas platyrhynchos fulvigula. Ridgeway, M.S. Thesis,
University of Florida, Gainesville, Florida, USA.
Maak, S., K. Wimmers, S. Weigend, and K. Neumann. 2003. Isolation and characterization of
18 microsatellites in the Peking duck (Anas platyrhynchos) and their application in other
waterfowl species. Molecular Ecology Notes 3: 224-227
Mantel, N. 1967. The detection of disease clustering and a generalized regression approach.
Cancer Research 27:209-220.
Marklund, O., I. Blindow, and A. Hargeby. 2001. Distribution and diel migration of
macroinvertebrates within dense submerged vegetation. Freshwater Biology 46:913-924.
Martin, P. and P. Bateson. 1986. Measuring behaviour. Cambridge University Press.
Cambridge, UK.
91
McCommas, S. A. and E. H. Bryant. 1990. Loss of electrophoretic variation in serially
bottlenecked populations. Heredity 64:315-321.
McCracken, K. G., W. P. Johnson, and F. H. Sheldon. 2001. Molecular population genetics,
phylogeography, and conservation biology of the mottled duck (Anas fulvigula).
Conservation Genetics 2:87-102.
McKinstry, M. C. and S. H. Anderson. 2002. Creating wetlands for waterfowl in Wyoming.
Ecological Engineering 18:293-304.
Merritt, R. W. & K. W. Cummins (eds.). 1996. An introduction to the aquatic insects of North
America. 3rd ed. Kendall/Hunt Publishing Co., Dubuque, Iowa, USA.
Moore, H. H., W. A. Niering, L. J. Marsicano, and M. Dowdell. 1999. Vegetation change in
created emergent wetlands (1988–1996) in Connecticut (USA). Wetlands Ecology and
Management 7:177-191.
Moorman, T. E., and P. N. Gray. 1994. Mottled duck (Anas fulvigula). 20pp. In A. Poole and
F. Gill, eds. The birds of North America, No. 81. The Academy of Natural Sciences,
Philadelphia; The American Ornithologists’ Union, Washington, D.C., USA.
Moritz, C. 1994. Applications of mitochondrial DNA analysis in conservation: a critical review.
Molecular Ecology 3:401-411.
Moyle, P. B. 1973. Effects of introduced bullfrogs, Rana catesbeiana, on the native frogs of the
San Joaquin Valley, California. Copeia 1973:18-22.
Murkin, E. J., H. R. Murkin, and R. D. Titman. 1992. Nektonic invertebrate abundance and
distribution at the emergent vegetation-open water interface in the Delta Marsh, Manitoba,
Canada. Wetlands 12:45-52.
92
Murkin, H. R. and J. A. Kadlec. 1986. Relationships between waterfowl and macroinvertebrate
densities in a northern prairie marsh. Journal of Wildlife Management 50:212-217.
Murkin, H. R., R. M. Kaminski, and R. D. Titman. 1982. Responses by dabbling ducks and
aquatic invertebrates to an experimentally manipulated cattail marsh. Canadian Journal of
Zoology 60:2324-2332.
Nagylaki, T. 1998. Fixation indices in subdivided populations. Genetics 148:1325-1332.
Nei, M. 1987. Molecular evolutionary genetics. Columbia University Press, New York, New
York, USA.
Nei, M., T. Maruyama, and R. Chakraborty. 1975. The bottleneck effect and genetic variability
in populations. Evolution 29:1-10.
Neigel, J. E. 1997. A comparison of alternative strategies for estimating gene flow from genetic
markers. Annual Review of Ecology and Systematics 28:105-128.
Newman, D., and D. A. Tallmon. 2001. Experimental evidence for beneficial fitness effects of
gene flow in recently isolated populations. Conservation Biology 15:1054-1063.
Nolet, B. A., S. Broekhuizen, G. M. Dorrestein, and K. M. Rienks. 1997. Infectious diseases as
main causes of mortality to beavers Castor fiber after translocation to the Netherlands.
Journal of Zoology 241: 35-42
Palmer, R. S. 1976. Handbook of North American birds. Vol. 2, Waterfowl (first part). Yale
University Press, New Haven, Connecticut, USA.
Paulus, S. L. 1984. Behavioral ecology of mottled ducks in Louisiana. Ph. D. dissertation,
Auburn Univiersity, Auburn, Alabama, USA.
93
_____. 1988. Social behavior and pairing chronology of Mottled Ducks during autumn and
winter in Louisiana. Pp. 59-70 in Waterfowl in winter, M. W. Weller, ed. University of
Minnesota Press, Minneapolis, Minnesota, USA.
Perry, M. C. and F. M. Uhler. 1988. Food habits and distribution of canvasback, Aythya
valisineria, on Chesapeake Bay. Estuaries 11:57-67.
Peakall, R. and P. E. Smouse. 2006. GENALEX 6: genetic analysis in Excel. Population
genetic software for teaching and research. Molecular Ecology Notes 6:288-295.
Petit, R. J., A. El Mousadik, and O. Pons. 1998. Identifying populations for conservation on the
basis of genetic markers. Conservation Biology 12:844-855.
Raymond, M. and F. Rousset. 1995. GENEPOP (version 1.2): population genetic software for
exact tests and ecumenicism. Journal of Heredity 86:248-249.
Reich, D. E., M. W. Feldman, and D. B. Goldstein. 1999. Statistical properties of two tests that
use multilocus data sets to detect population expansion. Molecular Biology and Evolution
16:453-466.
Reich, D. E. and D. B. Goldstein. 1998. Genetic evidence for a Paleolithic human population
expansion in Africa. Proceedings of the National Academy of Sciences USA 95:8119-8123.
Reinert, H. K. 1991. Translocation as a conservation strategy for amphibians and reptiles: some
comments, concerns, and observations. Herpetologica 47:357-363.
Reynolds, J., B. S. Weir, and C. C. Cockerham. 1983. Estimation of the coancestry coefficient:
Basis for a short-term genetic distance. Genetics 105:767-779.
Rice, W. R. 1989. Analyzing tables of statistical tests. Evolution 43:223-225.
Ridgway, R. 1874. Notes upon American water birds. American Naturalist 8:108-111.
94
Ryder, J. P. 1970. A possible factor in the evolution of clutch size of Ross’ Goose. Wilson
Bulletin 82:5-13.
Ryman, N., S. Palm, C. Andre, G. A. Carvalho, T. G. Dahlgren, P. E. Jorde, L. Laikre, L. C.
Larsson, A. Palme, and D. E. Ruzzante. 2006. Power for detecting genetic divergence:
differences between statistical methods and marker loci. Molecular Ecology 15:2031-2045.
Saitou, N. and M. Nei. 1987. The neighbor-joining method: a new method for reconstructing
phylogenetic tree. Molecular Biology and Evolution 4:406-425.
Schable, N. A., R. U. Fischer, T. C. Glenn. 2002. Tetranucleotide microsatellite DNA loci from
the dollar sunfish (Lepomis marginatus). Molecular Ecology Notes 2:509-511.
Scott, P. 1972. Key to the wildfowl of the world. W. P. Royale and Son, Ltd. London, UK.
Sedinger, J. S. 1992. Ecology of prefledging waterfowl. Pp. 109-127 in B. D. J. Batt, A. S.
Afton, M. G. Anderson, C. D. Ankney, D. H. Johnson, J. A. Kadlec, and G. L. Krapu, eds.
Ecology and management of breeding waterfowl. University of Minnesota Press,
Minneapolis, Minnesota, USA.
Sennett, G. B. 1889. A new species of duck from Texas. Auk 6:263-265.
Slatkin, M. 1985. Rare alleles as indicators of gene flow. Evolution 39:53-65.
_____. 1993. Isolation by distance in equilibrium and non-equilibrium populations. Evolution
47:264-279.
Slatkin, M. and N. H. Barton. 1989. A comparison of three indirect methods for estimating
average levels of gene flow. Evolution 43:1349-1368.
Sneath, P. H. A. and R. R. Sokal. 1973. Numerical taxonomy – The principles and practice of
numerical classification. W. H. Freeman, San Francisco, California, USA.
95
Sokal, R. R. and F. J. Rohlf. 1995. Biometry: the principles and practice of statistics in
biological research. 3rd ed. W. H. Freeman and Company, New York, New York, USA.
Spencer, C. C., J. E. Neigel, and P. L. Leberg. 2000. Experimental evaluation of the usefulness
of microsatellite DNA for detecting demographic bottlenecks. Molecular Ecology 9:1517-
1528.
Spong, G. and L. Hellborg. 2002. A near-extinction event in Lynx: do microsatellite data tell
the tale? Conservation Ecology 6:15. http://www.consecol.org/vol6/iss1/art15.
Stieglitz, W. O. and C. T. Wilson. 1968. Breeding biology of the Florida Duck. Journal of
Wildlife Management 32:921-934.
Strange, T. 1979. Waterfowl Status Report 1978-1979. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1980. Waterfowl Status Report 1979-1980. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1981. Waterfowl Status Report 1980-1981. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1982. Waterfowl Status Report 1981-1982. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
96
_____. 1983. Waterfowl Status Report 1982-1983. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1984. Waterfowl Status Report 1983-1984. South Carolina Wildlife & Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1985. Waterfowl Status Report 1984-1985. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1986. Waterfowl Status Report 1985-1986. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1987. Waterfowl Status Report 1986-1987. South Carolina Wildlife amd Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1988. Waterfowl Status Report 1987-1988. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1989. Waterfowl Status Report 1988-1989. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
97
_____. 1990. Waterfowl Status Report 1989-1990. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1991. Waterfowl Status Report 1990-1991. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1992. Waterfowl Status Report 1991-1992. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1993. Waterfowl Status Report 1992-1993. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1994. Waterfowl Status Report 1993-1994. South Carolina Wildlife and Marine
Resources Department, Division of Wildlife and Freshwater Fisheries, Columbia, South
Carolina, USA.
_____. 1995. Waterfowl Status Report 1994-1995. South Carolina Department of Natural
Resources, Division of Wildlife and Freshwater Fisheries, Columbia, South Carolina, USA.
_____. 1996. Waterfowl Status Report 1995-1996. South Carolina Department of Natural
Resources, Division of Wildlife and Freshwater Fisheries, Columbia, South Carolina, USA.
_____. 1997. Waterfowl Status Report 1996-1997. South Carolina Department of Natural
Resources, Division of Wildlife and Freshwater Fisheries, Columbia, South Carolina, USA.
_____. 1998. Waterfowl Status Report 1997-1998. South Carolina Department of Natural
Resources, Division of Wildlife and Freshwater Fisheries, Columbia, South Carolina, USA.
98
_____. 1999. Waterfowl Status Report 1998-1999. South Carolina Department of Natural
Resources, Division of Wildlife and Freshwater Fisheries, Columbia, South Carolina, USA.
_____. 2000. Waterfowl Status Report 1999-2000. South Carolina Department of Natural
Resources, Division of Wildlife and Freshwater Fisheries, Columbia, South Carolina, USA.
_____. 2001. Waterfowl Status Report 2000-2001. South Carolina Department of Natural
Resources, Division of Wildlife and Freshwater Fisheries, Columbia, South Carolina, USA.
_____. 2002. Waterfowl Status Report 2001-2002. South Carolina Department of Natural
Resources, Division of Wildlife and Freshwater Fisheries, Columbia, South Carolina, USA.
_____. 2003. Waterfowl Status Report 2002-2003. South Carolina Department of Natural
Resources, Division of Wildlife and Freshwater Fisheries, Columbia, South Carolina, USA.
Stutzenbaker, C. H. 1988. The mottled duck: Its life history, ecology and management. Texas
Parks and Wildlife Department, Austin, Texas, USA.
Szabo, M. P. J., M. B. Labruna, M. C. Pereira, and J. M. B. Duarte. 2003. Ticks (Acari:
Ixodidae) on Wild Marsh-Deer (Blastocerus dichotomus) from Southeast Brazil: Infestations
before and after habitat loss. Journal of Medical Entomology 40:268-274.
Thompson, J. D. and G. A. Baldassarre. 1990. Carcass composition of nonbreeding blue-
winged teal and northern pintail in Yucatan, Mexico. Condor 92:1057-1065.
Thorp, J. H. and A. P. Covich (eds.). 1991. Ecology and classification of North American
freshwater invertebrates. Academic Press, Inc. San Diego, California, USA.
Traxler, B., G. Brem, M. Müller, and R. Achmann. 2000. Polymorphic DNA microsatellites in
the domestic pigeon, Columba liviavar domestica. Molecular Ecology 9:366-368.
Voigts, D. K. 1976. Aquatic invertebrate production in relation to changing marsh vegetation.
American Midland Naturalist 93:313-322.
99
Weir, B. S. and C. C. Cockerham. 1984. Estimating F-statistics for the analysis of population
structure. Evolution 38:1358-1370.
Weir, B. S. 1996. Genetic Data Analysis II. Sinauer Associates, Inc. Sunderland,
Massachusetts, USA.
White, D. H. and D. James. 1978. Differential use of freshwater environments by wintering
waterfowl of coastal Texas. Wilson Bulletin 90:99-111.
Whitlock, M. C. and D. E. McCauley. 1999. Indirect measures of gene flow and migration:
FST≠1/(4Nm + 1). Heredity 82:117-125.
Williams, C. L., R. C. Brust, and O. E. Rhodes, Jr. 2002. Microsatellite polymorphism and
genetic structure of Florida mottled duck populations. The Condor 104:424-431.
Williams, C. L., A. M. Fedynich, D. B. Pence, and O. E. Rhodes, Jr. 2005. Evaluation of
allozyme and microsatellite variation in Texas and Florida mottled ducks. The Condor
107:155-161.
Williams, C. L., R. C. Brust, T. T. Fendley, G. R. Tiller, Jr., and O. E. Rhodes, Jr. 2005. A
comparison of hybridization between mottled ducks (Anas fulvigula) and mallards (A.
platyrhynchos) in Florida and South Carolina using microsatellite DNA analysis.
Conservation Genetics 6:445-453.
Wright, S. 1978. Evolution and the genetics of population, variability within and among natural
populations. The University of Chicago Press, Chicago, Illinois, USA.
Zwank, P. J., P. M. McKenzie, and E. B. Moser. 1989. Mottled duck habitat use and density
indices in agricultural lands. Journal of Wildlife Management 53:110-114.
100
