Distribution, relative abundance, and habitat requirements of Cerulean
Warblers (Dendroica cerulea) in northern Alabama
by
John Peter Carpenter
A THESIS
Submitted in partial fulfillment of the requirements
for the degree of Master of Science
in the Department of Plant and Soil Science
in the School of Graduate Studies
Alabama A&M University
Normal, Alabama 35762
May 2007
Submitted by JOHN P. CARPENTER in partial fulfillment of the requirements for
the degree of MASTER OF SCIENCE specializing in PLANT AND SOIL SCIENCE.
Accepted on behalf of the Faculty of the Graduate School by the Thesis Committee:
___________________________Dr. Yong Wang, Major Advisor
___________________________Dr. Paul Hamel
___________________________Dr. Callie Schwetizer
___________________________Dr. Wubishet Tadesse
___________________________Dr. Ken Ward
_______________________________ Dean of the Graduate School
_______________________________ Date
ii
Copyright by
John P. Carpenter
2007
iii
This thesis is dedicated to the memories of:
John and Patricia Carpenter,
John and Jane Kinn,
and
Joan Carpenter
iv
Distribution, relative abundance, and habitat requirements of Cerulean Warblers (Dendroica
cerulea) in northern Alabama
Carpenter, John P., M.Sc., Alabama A&M University, 2007. 122 pp.
Thesis Advisor: Dr. Yong Wang
Northern Alabama represents a portion of the Cerulean Warbler’s southern-most breeding
range where they were once considered common and even numerous in several counties.
Today, Cerulean Warblers are rarely encountered in Alabama and are classified as a Priority
One species (highest conservation concern). The objectives of this study were to: 1)
determine distribution and relative abundance, 2) examine habitat use and avian associations,
3) quantify microhabitat characteristics, 4) investigate landscape associations, 5) locate
potential breeding habitat using Geographic Information Systems (GIS), 6) measure home
ranges and core use areas using radio-telemetry, and 7) estimate breeding success. Point
counts and habitat assessments were conducted in areas of Cerulean Warbler
absence/presence, and a subsample of D. cerulea males were captured and fitted with
transmitters for radio-telemetry analysis. Cerulean Warblers occurred in three disjunct
populations: one in Bankhead National Forest, Lawrence County, and two in Jackson County
along Larkin Fork and in Walls of Jericho along Hurricane Creek. In northern Alabama, the
species selected habitats containing a variety of tall, large diameter deciduous tree species
with a high percent canopy cover, sparse understory, and a moderately complex canopy
structure. At the landscape level, this species bred in contiguous tracts of deciduous forest
close to streams but far from areas experiencing rapid human development. They associated
most often with sympatric, deciduous forest-dwelling Neotropical migrants, and two radiotracked males had an average home range greater than five hectares. The estimated
reproductive success for all three populations was extremely low and future management and
protection is recommended.
KEY WORDS: Cerulean Warbler, Dendroica cerulea, microhabitat, avian associations,
radio-telemetry, landscape characteristics, Geographic Information Systems (GIS), habitat
modeling, Hurricane Creek, Walls of Jericho, Larkin Fork, Bankhead National Forest, Sipsey
Wilderness
v
TABLE OF CONTENTS
CERTIFICATE OF APPROVAL…………………………………………………………….ii
ABSTRACT AND KEY WORDS……………………………………………………………..v
LIST OF FIGURES…………………………………………………………………………..ix
LIST OF TABLES…………………………………………………………………………...xii
ACKNOWLEDGMENTS…………………………………………………………………..xiii
CHAPTERS
1- INTRODUCTION…………………………………………………………………….1
Cerulean Warbler Natural History…………………………………………………….2
Range-wide Distribution and Population Trends……………………………………..4
Cerulean Warbler Occurrence in Alabama……………………………………………7
Objectives……………………………………………………………………………..9
2- MATERIALS AND METHODS……………………………………………………..10
Study Areas………………………………………………………………………….10
Bird Surveys…………………………………………………………………………12
Mist-netting and Radio-telemetry……………………………………………………16
Microhabitat Characteristics…………………………………………………………18
Landscape Associations……………………………………………………………...21
Habitat Modeling…………………………………………………………………….22
Statistical Analysis…………………………………………………………………...23
3- RESULTS……………………………………………………………………………30
Distribution and Relative Abundance………………………………………………..30
vi
TABLE OF CONTENTS CONTINUED
CHAPTERS
3- RESULTS……………………………………………………………………………30
Bird Surveys………………………………………………………………………….31
Nesting and Reproductive Success…………………………………………………..32
Mist-netting and Radio-telemetry……………………………………………………34
Microhabitat Characteristics…………………………………………………………36
Landscape Associations……………………………………………………………...38
Habitat Modeling…………………………………………………………………….40
4- DISCUSSION………………………………………………………………………..42
Distribution and Relative Abundance………………………………………………..42
Bird Surveys………………………………………………………………………….43
Nesting and Reproductive Success…………………………………………………..47
Mist-netting and Radio-telemetry……………………………………………………48
Microhabitat Characteristics…………………………………………………………51
Landscape Associations……………………………………………………………...53
Habitat Modeling…………………………………………………………………….56
5- CONCLUSIONS…………………………………………………………………….58
6- RECOMMENDATIONS……………………………………………………………62
LITERATURE CITED…………………………………………………………………..64
APPENDICES………………………………………………………………………….109
A. Sample letter used to request permission to access private property in
Jackson County, Alabama...………………………………………………..114
B. Microhabitat variable codes and explanations …………………………......115
C. Original and reduced variables for National Land Cover Data used in
landscape analyses………………………………………………………….116
D. Variable codes and explanations of landscape metrics……………………..117
vii
TABLE OF CONTENTS CONTINUED
APPENDICES………………………………………………………………………….109
E. Additional searches for Cerulean Warblers in northern Alabama, 20042006.………………………………………………………………………..118
F. Abundance and total percent of breeding birds species detected at “used”
point counts in northern Alabama, 2005-2006.……….………..…………..119
G. Abundance and total percent of breeding bird species detected at “random”
point counts in northern Alabama, 2005-2006.……..………. ……..……...121
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LIST OF FIGURES
Figure
Page
1.
Locations of historic and recent Cerulean Warbler encounters in Alabama…….78
2.
Locations of Cerulean Warbler study sites in northern Alabama, 2005-2006…...79
3.
Distribution of habitat plots, nest sites, and points counts at Walls of Jericho,
Jackson County, 2005-2006...................................................................................80
4.
Distribution of habitat plots, nest sites, and points counts at Larkin Fork,
Jackson County, 2005-2006…………...................................................................81
5.
Distribution of habitat plots, nest sites, and points counts at Bankhead National
Forest, Lawrence County, 2005-2006.…………………………………………...82
6.
Locations of “random” points sampled for habitat, landscape, and avian
associations in northeast Alabama, 2005-2006…….…………………………….83
7.
Locations of “random” points sampled for habitat, landscape, and avian
associations in northwest Alabama, 2005-2006…….……………………………84
8.
Mist-net designs………………………………………………………………….85
9.
Territory centroids of Cerulean Warbler territories used for nearest neighbor
analysis……………………………………………………………….…………..86
10.
Means (± SE) of bird species abundance and richness detected at “used” and
“random” point count stations in northern Alabama, 2005-2006………………..87
11.
Scatter biplot (Axes 1 & 2) of canonical correspondence analysis for “used”
and “random” point counts conducted during the 2005-2006 breeding seasons
throughout northern Alabama……………………………………………………88
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LIST OF FIGURES CONTINUED
Figure
Page
12.
Scatter biplot (Axes 1& 3) of canonical correspondence analysis for “used”
and “random” point counts conducted during the 2005-2006 breeding seasons
throughout northern Alabama……………………………………………………89
13.
Scatter biplot (Axes 2 & 3) of canonical correspondence analysis for “used”
and “random” point counts conducted during the 2005-2006 breeding seasons
throughout northern Alabama……………………………………………………90
14.
Proportion of stems selected by Cerulean Warblers versus their availability for
the ten most used species in Jackson and Lawrence Counties, Alabama, 20052006………………………………………………………………………...........91
15.
Means (± SE) of tree diameters and tree heights used by Cerulean Warblers
versus those available in 0.04 ha “used” and nest site habitat plots sampled in
Jackson and Lawrence Counties, Alabama, 2005-2006………………………....92
16.
Reproductive success of Cerulean Warblers in Jackson and Lawrence Counties,
Alabama, 2005-2006…………………………………………………..................93
17.
Mean (± SE) number of food deliveries per 30 minutes recorded during two
surveys of a Cerulean Warbler nest in Bankhead NF, 2006……………………..94
18.
Radio-telemetry results for two Cerulean Warbler males tracked at Walls of
Jericho, Jackson County, Alabama, 2006………………………………………..95
19.
Means (± SE) of observed territory sizes from Cerulean Warbler populations in
2006 and of home range core use areas delineated using radio-telemetry at Walls
of Jericho, Jackson County, Alabama, 2006.…………………………..………...96
20.
Transformed aspect scores for habitat plots in northern Alabama, 2005-2006….97
21.
Potential Cerulean Warbler habitat in Jackson County, Alabama identified using
binary logistic regression…………………………………………………...........98
22.
Potential Cerulean Warbler habitat in Jackson County, Alabama identified using
Mahalanobis distance (D2)……………………………………………….............99
x
LIST OF FIGURES CONTINUED
Figure
Page
23.
Potential Cerulean Warbler habitat in Lawrence and Winston Counties, Alabama
identified using binary logistic regression……………………………...............100
24.
Potential Cerulean Warbler habitat in Lawrence and Winston Counties, Alabama
identified using Mahalanobis distance (D2)………………………….................101
25.
Means (± SD) of Mahalanobis distances obtained from habitat plots sampled in
Jackson and Lawrence Counties, Alabama, 2005-2006………………………..102
26.
Means (± SD) of probability of use obtained through binary logistic regression
using habitat plots sampled in Jackson and Lawrence Counties, Alabama, 20052006…………………………………………………………………………….103
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LIST OF TABLES
Table
Page
1. Abundance of Cerulean Warblers and maximum index of reproductive activity
(IRA) ranks for territories detected in Jackson and Lawrence Counties, Alabama,
2005-2006..................................................................................................................104
2. Summary of all mist-net attempts and captured males at Walls of Jericho and Larkin
Fork, Jackson County, Alabama, 2005-2006.............................................................105
3. Comparisons (mean ± SE) of microhabitat characteristics for Cerulean Warbler study
plots sampled in northern Alabama, 2005-2006........................................................106
4. Comparisons (mean ± SE) of microhabitat characteristics sampled from 0.04 ha
“used” habitat plots at three Cerulean Warbler study sites in northern Alabama, 20052006...........................................................................................................................108
5. Summary of Cerulean Warbler nests from northern Alabama, 2004-2006...............110
6. Comparisons (mean ± SE) of landscape associations for Cerulean Warbler study plots
sampled in northern Alabama, 2005-2006.................................................................111
7. Comparisons (mean ± SE) of landscape associations among three Cerulean Warbler
populations in northern Alabama, 2005-2006...........................................................112
8. Top ten competing AIC models used for development of Cerulean Warbler habitat
models........................................................................................................................113
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ACKNOWLEDGMENTS
The completion of this thesis would not have been possible without the help of many
individuals and organizations. I have tried to include everyone I can think of at this moment
and apologize for any that have been accidentally left out.
My major advisor, Dr. Yong Wang, has sacrificed a good deal of his time on this
project. He is a great teacher and friend, and his generosity and patience have been an
inspiration.
The expertise provided by my advisory committee: Dr. Paul Hamel, Dr. Callie
Schweitzer, Dr. Wubishet Tadesse, and Dr. Ken Ward, improved this work tremendously.
The faculty, staff, and students of Alabama A&M University, especially many of
those in the Department of Plant and Soil Science, have kindly contributed their equipment,
assistance, advice, and personal time to my research. Special thanks to Kimi Sangalang, Dr.
Wes Stone, Dr. Luben Dimov, Dr. Kozma Naka, Dawn Lemke, Tom Smith, Courtney
Kilgore, Jeff Crocker and all of Dr. Wang’s graduate students: Florence Chan, Zach Felix,
Lisa Gardner, Adrian Lesak, Shanta Parajuli, Bill Sutton, and Jill Wick.
I am indebted to Joe Gardinski and the Alabama Natural Resources Conservation
Service, Allison Cochran, Tom Counts and Bankhead National Forest, Dr. Stacy Clark, Ryan
Sisk and the US Forest Service, Eric Soehren and the Alabama Department of Conservation
xiii
and Natural Resources, the Ohio State Borror Laboratory of Bioacoustics, Harold and Betty
Huey, and Phillip Blackburn.
Many private landowners granted me access to their property throughout the course
of this study. I thank these families and businesses for their hospitality: Mr. and Mrs. Bill
Cagle, Greg Janzen and Stevenson Land Company, Miller Family Trust, the Layky family,
the Emmans family, the Goennier family, the Green family, the Carr family, the Dean family,
the Douglas family, the Dyer family, the Grant family, the Gurley family, the Hodges family,
the Duffy family, the Johnson family, the Kinnebrew family, the McCrary family, the
Roberson family, the Shankles family, the Sledge family, the Sisk family, the Youngblood
family, the Reynolds family, Dese Research, Summit Structures, and Trees, Inc.
Funding for this project was provided by the Alabama Department of Conservation
and Natural Resources, USDA Forest Service, USDI Fish and Wildlife Service, and Alabama
A&M University.
Finally, my most sincere thanks and gratitude is for my parents, Peter and Nancy, my
sisters, Coleen and Kerry, and their families, and all the Kinns and Carpenters. None of this
would not have been possible without all of your love, encouragement, and support.
xiv
CHAPTER 1
INTRODUCTION
Nearctic-Neotropical migratory birds, those that breed in the New World Temperate
Zone and winter in the Tropics, comprise up to two-thirds of species breeding in eastern
North American forests (Terborgh 1980). Because these species are widely distributed and
easily detected, they are considered ideal bio-indicators of environmental health and diversity
(Heagy and McCraken 2004). Furthermore, migratory birds promote critical ecological
processes through the suppression of forest insects, seed dispersion, and pollination (Holmes
1990, Rotenberry et al. 1995), provide cultural and aesthetic value through song and
appearance (Bolen and Robinson 1999), and contribute to the $32 billion in U.S. revenue
generated from wildlife watching (La Rouche 2001). Beginning in the late 1980s, concern
for these migrants escalated after reports suggested several species were suffering from
significant population declines throughout their summer and winter ranges (Terborgh 1989,
Askins 1990, Finch 1991).
At the turn of the 20th century, the Cerulean Warbler (Dendroica cerulea Wilson)
was recognized as one of the most abundant warblers in the Ohio and Mississippi Alluvial
Valleys (Hamel 2000a, 2000b).
Today it is experiencing one of the most precipitous
population declines of any Nearctic-Neotropical species in the United States (Robbins et al.
1
1992, James et al. 1996, Villard and Maurer 1996, Hamel 2000a, 2000b, Sauer et al. 2002)
and has become the focus of several research and conservation initiatives in North America
(Robbins et al. 1992, Oliarnyk and Robertson 1996, Rosenberg et al. 2000, Ruley 2000,
Burhans et al. 2002, Link and Sauer 2002, Hamel et al. 2004, Jones et al. 2004, Thogmartin
et al. 2004, Hamel 2005) and in South America (Jones et al. 2000, Bakermans and Rodewald
2006, Colorado et al. 2006, Hamel et al. 2006, Moreno et al. 2006).
Cerulean Warbler Natural History
Cerulean Warblers belong to the family Parulidae, which consists of 16 genera with
53 species breeding in North America (Sibley 2000). They are short-tailed but long-winged,
weigh approximately 8-10 g, and are the smallest of the 29 species in the genus Dendroica
(Dunn and Garrett 1997). Their diet consists mostly of insects and their larvae, which they
capture from leaf bases and foliage by sallying, gleaning, and hover-gleaning (Hamel 2000a,
2000b).
Cerulean Warblers are sexually dimorphic and were originally described as two
separate species (Hamel 2000a). Breeding and winter plumages display white wing bars and
white tail spots. The upper parts of males are sky blue with a streaked back and flanks and a
dark breast band. Females and juveniles are blue-green above, yellowish below, lack any
streaking, and exhibit a broad supercilium; second-year males may also retain a partial
eyebrow (Dunn and Garret 1994, Hamel 2000a, 2000b).
Cerulean Warblers are classified as upper canopy specialists who breed in mature
forests with large diameter deciduous trees, complex canopy structure, and sparse understory
(Hamel 2000a, 2000b). They occur most often in sycamore-dominated riparian bottomland
2
forests, mixed-mesophytic cove forests, and oak-hickory mesic upland forests (Hamel 2000a,
2000b, Barker Swarthout et al. 2006), but have also been documented successfully exploiting
mid-succession, abandoned farmland (Oliarnyk and Robertson 1996). Males are often found
singing near forest edges created by natural canopy openings, power line right-of-ways,
roads, and fields (Hamel et al. 2005a, Carpenter pers. obs.) Minimum area requirements
range from ten forested ha in Ontario (Hamel 2000a) to >8000 ha in the Mississippi Alluvial
Valley (Hamel 2000b, Hunter et al. 2001).
Robbins et al. (1989) found Ceruleans only in
forests >700 ha in the Mid-Atlantic States, while over 80% of occupied sites in the
southeastern United States (US Fish and Wildlife Service Region 4) occurred in forests
>2000 ha (Rosenberg et al. 2000).
Nests are typically constructed on a forked, horizontal limb at an average height
greater than 11.5 m in the mid to upper canopy and are often concealed from above by the
vegetation of an adjacent branch (Hamel 2000a, 2000b, Rogers 2006). Clutch size ranges
from three to five eggs that are creamy white and blotched around the large end with bay,
chestnut, or auburn (Bent 1953, Griscom 1979, Hamel 2000b). Typically one brood is raised
per season (Hamel 2000b) with only a single documented instance of double brooding (Barg
et al. 2006b). Pairs frequently re-nest after a failed attempt (Oliarnyk and Robertson 1996,
Hamel 2000b, Barg et al. 2006b, Rogers 2006), and in southern Ontario, the first case of
brood adoption was witnessed (Barg et al. 2006b). Females construct their nests in a wide
variety of deciduous tree species (Oliarnyk and Robertson 1996, Hamel 2000b, Rogers 2006,
Barg et al. 2006b) with the exception of one nest found in a shortleaf pine (Pinus echinata
Mill.) in southern Illinois (Hamel 2000a).
3
Although much debate still exists regarding the migratory ecology of Cerulean
Warblers, it is widely accepted that they are a nocturnal, trans-gulf migrant (Hamel 2000a,
2000b).
During their spring route, Ceruleans are believed to make stopovers in northern
Latin America, most notably in Belize (Parker 1994), and again along the Gulf Coast of the
United States (Mehlman et al. 2006). Their northeast expansion into the breeding grounds
occurs primarily through the Mississippi and Ohio River Valleys (Hamel 2000b). Their fall
migration is hypothesized to be a mirror of the spring and is characterized by two main
passages with birds arriving in South America as early as August (Mehlman et al. 2006).
During the winter months, Cerulean Warblers return to the cooler subtropical clines
and moderate rainfall of South America where they inhabit primary deciduous forests and
agroecosystems characterized by mature shade trees (Jones et al. 2000, Bakermans et al.
2006, Colorado et al. 2006, Hamel et al. 2006, Moreno et al. 2006). Greater than fifty
percent of all winter observations come from coffee plantations located in the intermontane
valleys of Colombia; however, Cerulean Warblers that associate with dense forests may be
underrepresented because of the difficulties associated in detecting individuals silently
foraging in the thick vegetation (Moreno et al. 2006). The species has been observed in
mixed species flocks (Jones et al. 2000, Colorado et al. 2006), but this behavior may be
dictated by rainfall and resource availability (Moreno et al. 2006).
Range-wide Distribution and Population Trends
At present, the Cerulean Warbler’s breeding range encompasses 32 U.S. states and
two Canadian provinces with 70% of the population concentrated in the Ohio Hills and
4
northern Cumberland Plateau (Dunn and Garret 1994, Hamel 2000a, 2000b, Rosenberg et al.
2000, Barker Swarthout et al. 2006). In Canada, the Committee on the Status of Endangered
Wildlife in Canada (COSEWIC) lists Cerulean Warblers as “Endangered or Threatened” and
of “Special Concern”, while in the United States they are currently classified as “Endangered
or Threatened” in three states and a “Species of Concern” in 14 additional states (Hamel
2000a, 2000b, Rosenberg et al. 2000, Mirachi et al. 2004). In 2000, a petition was submitted
to the US Fish and Wildlife Service (USFWS) requesting that the Cerulean Warbler be listed
as “Threatened” under the Endangered Species Act (Ruley 2000, Hamel et al. 2004). In
December 2006, the USFWS announced that the current status of the Cerulean Warbler did
not warrant its classification for federal protection (USFWS 2006).
In South America, Cerulean Warblers are an uncommon, non-breeding resident
throughout the northern Andean forests (Pearson 1980, Hamel 2000a, 2000b, Moreno et al.
2006). They have been observed as far north as the tepui regions of Venezuela and south to
northern Bolivia, but recent surveys have suggested that they are unevenly distributed
throughout their range (Moreno et al. 2006). The increasing popularity of higher-yielding
sun-coffee varieties has resulted in a loss of over 80% of mature shade-grown coffee habitat
at one key Cerulean stronghold in Colombia (Moreno et al. 2006). Only an estimated 1040% of Cerulean Warbler habitat may remain throughout its winter range with no stateowned areas currently designated for protection (Moreno et al. 2006).
Declines in Cerulean Warbler populations are attributed to the loss and fragmentation
of breeding, migratory, and wintering habitats, stream and air pollution, nest parasitism by
the Brown-headed Cowbird (Molothrus ater Boddaert), loss of important tree species through
5
the introduction of exotic diseases, and shortened rotation periods in managed forests (Lynch
1981, Robbins et al. 1992, James et al. 1996, Hamel 2000a, 2000b). Furthermore, Cerulean
Warblers must also endure the risks associated with a long migration route, which may total
over 4,000 km (kilometer) round trip each year (USFWS 2006).
Roughly 70% of the Cerulean Warbler breeding population has been lost since 1966,
and recent estimates suggest as few as 280,000 pairs may remain (Rich et al. 2004, Barker
Swarthout et al. 2006). Breeding Bird Surveys (BBS) data for the eastern United States from
1966-2005 revealed a 4.5% decline in the Cerulean Warbler population (Sauer et al. 2005).
Additional analysis of BBS data from 1967-1989 and 1966-1992 indicated the greatest
subsidence was occurring in areas with the highest breeding potential (James et al. 1996,
Villard and Maurer 1996, Hamel 2000b). While an expansion into Ontario had been reported
for several years (Robbins et al. 1992, Oliarnyk and Robertson 1996, Jones and Robertson
2001), a decline in this part of its range is now becoming apparent (Heagy and McCraken
2004, Barker Swarthout et al. 2006).
While BBS data still provides the best large-scale population estimates available for
several species of Neotropical migrants, reliability of these roadside surveys has been
questioned in regard to D. cerulea because of their propensity to use large forest tracts, the
largest of which are often situated far from these types of corridors (Hamel 2000b).
Since
1966, only two BBS routes in Alabama have detected Cerulean Warblers during the breeding
season (Sauer et al. 2005). In response to these negative population trends, the Cerulean
Warbler Atlas Project (CEWAP), in conjunction with Partners in Flight (PIF), USFWS, and
the Cornell Lab of Ornithology, examined regional population status, habitat, and area
6
requirements, and potential breeding areas not accessible by BBS protocol. The results,
based on searches from 1997 to 2000, were assumed to be most accurate in the periphery of
the Cerulean’s breeding range due to lower abundances and consequently a higher
probability of detecting breeding populations. Regardless, several areas in Alabama were not
surveyed and further investigation was recommended (Rosenberg et al. 2000).
Cerulean Warbler Occurrence in Alabama
The northern half of Alabama historically represented a portion of the southern-most
extension of the Cerulean Warbler’s breeding range (Fig. 1). Five specimens were collected
by Avery in May 1887 near the Warrior River bottom west of Greensboro (Holt 1921), and
Saunders (1908) regarded them as common in Woodbine along Finigotchki Creek. Howell
(1928) documented several encounters between 1889 and 1914 and considered the species a
common breeder along Short Creek in Guntersville and rare at Erin, Monte Sano, Squaw
Shoals, Tuscaloosa, and Autaugaville. Imhof (1976) described Ceruleans as numerous in the
western half of Alabama and common breeders in river and creek valleys south to the “Fall
Line”, the gradual change in topography dividing the Appalachian foothills from the Coastal
Plain. Furthermore, Imhof (1976) confirmed breedings in Lauderdale, Lawrence, Winston,
and Jefferson counties, and reported June sightings in eight additional counties.
More recently, Cerulean Warblers were encountered in Bankhead National Forest
(Vaughan 1994, Rosenberg et al. 2000, Gilliland and Kittinger 2001, Soehren 2004b) and
Bucks Pocket State Park in Marshall County (Cooley 2001).
Since 2002, Alabama’s
Breeding Bird Atlas (BBA) has searched 5x5 km blocks and mapped Cerulean Warblers in
7
three additional counties during June: Colbert County (T. Haggerty and P. Kittle pers. obs.,
D. Slimbeck pers. obs., Jackson 1999), Fayette County (D. Cutten and R. Cutten pers. obs.,
Jackson 2001), and Little River National Park in De Kalb County (B. Steadman pers. obs.,
West pers. comm., Alabama Ornithological Society [AOS]). As encouraging as these recent
sightings appear, most encounters are infrequent and may represent migrant or transient,
unpaired males. Consequently, during the Second Alabama Nongame Wildlife Symposium
in 2002, D. cerulea was designated as a Priority One species (highest conservation concern)
in Alabama based on its population trends, low relative abundance, patchy distribution,
dependence on mature, contiguous forests and continual threats of habitat disturbance and
destruction (Mirachi et al. 2004, Soehren 2004a, Carpenter et al. 2005).
In addition to a previously documented yet poorly monitored population in Bankhead
National Forest, the recent discoveries of two small breeding Cerulean Warbler populations
in Jackson County have prompted further investigation of its current status in northern
Alabama (Carpenter et al. 2005). An agreement between the USDA Forest Service (USFS)
and Alabama’s Department of Conservation and Natural Resources (ADCNR) was
established in 1999 to perform bird surveys in Bankhead National Forest (BNF) with an
emphasis in locating Cerulean Warblers (Soehren 2004b). These surveys were conducted for
approximately one week in late May from 1999 to 2004 and revealed 32 Cerulean Warblers
and one nest in Lawrence County. In 2002, researchers from Alabama A&M University
(AAMU) and USFS located a breeding population and two fledglings along Larkin Fork
while performing an unrelated avian study in Jackson County. The third breeding population
8
of Cerulean Warblers was discovered in 2004 along Hurricane Creek in Walls of Jericho/
Skyline Wildlife Management Area (WMA), Jackson County.
Objectives
The status of the three aforementioned Cerulean Warbler populations in Alabama is
poorly understood; however, their presence suggests that suitable habitat may still be
available in northern Alabama to support small breeding populations.
This study was
designed to help provide the information required for effectively managing Cerulean
Warblers in northern Alabama. Specifically, the goals of this study were to:
1. Determine distribution and relative abundance,
2. Examine habitat use and avian associations,
3. Quantify microhabitat characteristics,
4. Investigate landscape associations,
5. Locate potential breeding habitat using Geographic Information Systems (GIS),
6. Measure sizes of home ranges and core use areas, and
7. Estimate breeding success.
9
CHAPTER 2
MATERIALS AND METHODS
Study Areas
Cerulean Warblers were monitored at three study sites in Lawrence, Winston, and
Jackson Counties, Alabama (Fig. 2). These counties were selected based on historic breeding
records from Imhof (1976) and recent sightings (Soehren 2004a, 2000b, Carpenter et al.
2005, West pers. comm. [AOS]). Bird surveys and habitat assessments were also performed
at random locations in northern Alabama for comparisons with breeding populations.
Walls of Jericho (Fig. 3) - Located along the mid-Cumberland Plateau in northwest
Jackson County, Walls of Jericho is a 5,060 ha multiuse tract acquired by Alabama’s Forever
Wild program in 2004. Braun (1950) categorized vegetation of the plateau in northern
Alabama as oak and oak-hickory forests with mixed mesophytic communities restricted to
valleys and coves. Nearly 80% of forests in Jackson County are composed of oak-hickory
species (Hartsell and Brown 2002). Hurricane Creek, a tributary of the Paint Rock River,
extends north through the preserve for approximately four km before reaching the Tennessee
state line and is bordered by Little Cumberland Mountain to the west and Skyline Wildlife
Management Area (WMA) to the east. The surrounding topography is highly dissected with
10
elevations ranging from roughly 500 m along ridge tops to 200 m in the floodplains. Several
hunting fields are situated throughout the floodplain of Hurricane Creek and are mowed by
the Alabama Department of Conservation and Natural Resources each fall. In addition, an
approximately 3 ha seasonally inundated wetland is located in the northern half of the
preserve.
Larkin Fork (Fig. 4) - Situated approximately ten km to the west of Walls of Jericho,
Larkin Fork runs parallel with AL State Highway 65 near the Tennessee state border. The
floodplain of Larkin Fork is bounded to the east by Miller Mountain and to the west by King
Cove. Vegetation and elevations are similar to those found at Walls of Jericho. All property
along Larkin Fork is privately owned, and contact information of these landowners was
obtained from the Jackson County Municipal Courthouse’s property tax records. Permission
was granted by property owners prior to surveying (see Appendix A).
Recent human
disturbances, including agricultural practices and private timber harvesting, are more
prevalent here than at the other two study sites.
Bankhead National Forest (Fig. 5) - Located in Franklin, Winston, and Lawrence
Counties along the southern Cumberland Plateau in northwest Alabama, Bankhead NF is
characterized by dissected sloping ridges and rock bluffs dominated by loblolly pine and
upland hardwood and hardwood pine (Gaines and Creed 2003). Elevations reach 275 m and
roughly 48% of the 71,600 forested ha in BNF are classified as late succession (Gaines and
Creed 2003).
The 10,400 ha Sipsey Wilderness Area is the second largest designated
wilderness east of the Mississippi (Chipley et al. 2003) and is situated in the northwest
portion of the forest.
11
Random points - A total of 51 “random” points were sampled for comparison with
occupied Cerulean Warbler habitat and to increase the chances of discovering new breeding
populations. The only requirement for “random” locations was that each point must fall
within deciduous-mixed forest. ArcGIS v.9.1 (Environmental Systems Research Institute
[ESRI] 2005) was used to randomly generate a total of 24 points in the Skyline WMA and in
Jackson, Madison, Cherokee, and DeKalb Counties (Fig. 6). For Lawrence and Winston
Counties, 25 points were selected from 122 pre-existing point count stations located in
Bankhead National Forest (Fig. 7). Locations of the remaining two points were based on
Cerulean Warbler sightings in Colbert and Fayette Counties in 1999 and 2001, respectively.
Bird Surveys
Distribution and relative abundance of Cerulean Warblers was examined by
conducting weekly systematic searches of all three populations during the 2005 and 2006
breeding seasons (roughly mid/late April to early July). Surveys were focused along the
floodplains and adjacent slopes of Hurricane Creek and Larkin Fork, and in the Sipsey
Wilderness Area of Bankhead NF, primarily along Flannigan and Borden Creeks. Playback
of a conspecific D. cerulea song was also broadcasted at “random” points to increase the
likelihood of detecting at-rest or “floater” males outside of the three known populations. In
addition, target searches and playback were performed where Cerulean Warblers had been
detected on recent Breeding Bird Atlas surveys and in areas displaying similar landscape
characteristics of Alabama’s remaining breeding populations using US Geological Survey
(USGS) topographic quadrangle maps.
12
Locations of all Cerulean Warblers were recorded with an eTrex Legend Global
Positioning System (GPS), which has a reported ± 15 m accuracy (Garmin©). Direction and
estimated distance of counter-singing males was noted, as well as any diagnostic song or
plumage qualities that would aid in distinguishing Cerulean neighbors. All surveys were
performed on foot throughout the day, and the duration of each visit ranged from a few
minutes to several hours. Survey length was usually dictated by several factors, including:
weather conditions, time of day, amount of area covered by the observer, and the quality of
information being collected.
Point Counts – Fixed radius point counts were performed during encounters with
Cerulean Warblers and at “random” points to assess avian community composition and
associations. All counts were conducted prior to 10:30 a.m. from May to July 2005 and 2006
following modified protocol of Hamel et al. (1996). During encounters, “used” counts were
centered under singing males. If a Cerulean Warbler was detected at a “random” point,
counts were performed at both the pre-determined location and under the individual. Before
beginning, GPS coordinates were recorded while allowing all birds to settle. Every bird
observed during three time intervals (0-3 min., 4-5 min., and 6-10 min.) were mapped in their
estimated direction and distance interval (<25 m, 25-50 m, 50-100 m, >100 m, and flyover).
All point counts were performed by the author to eliminate multiple surveyor bias (Sauer et
al. 1994, Rosenstock et al. 2002).
Tree Use - Cerulean Warbler’s tree selection and use was documented to confirm its
dependency on the upper canopy of tall, deciduous trees. Instantaneous sampling (Hejl et al.
1990) was employed to assign relative vertical (upper, middle, or lower) and horizontal
13
(inside, middle, or outside) positions within the crown (Hamel 1981). Once a Cerulean
Warbler was detected, the observer recorded the bird’s relative location at the completion of
a five second count. Stem use versus availability was examined by graphing the proportions
and averages of tree species selected by Cerulean Warblers in relation to those same species
present in all “used” and nest habitat plots (See Microhabitat Characteristics below).
Additional measurements included: tree species, tree height (m), tree diameter at breast
height (cm), and tree crown class (dominant, co-dominant, intermediate, or suppressed).
Heights were estimated using a clinometer and readings were taken at a fixed distance
of 20 m from the tree bole, which was determined with a rangefinder or mason’s line.
Diameter at breast height (DBH) was measured at approximately 1.3 m above ground level
and adjusted for irregularities as directed by Avery and Burkhart (1994).
Crown
classifications were derived from Avery and Burkhart (1994) and were as follows: dominant
crowns extended above the general height of the canopy and received complete sunlight from
above and slightly from the sides, co-dominant crowns formed the average canopy height and
were exposed to full sunlight from above but relatively little from the sides, intermediate
crowns were found within the surrounding middle canopy and received little direct sunlight,
and suppressed crowns grew entirely below the average canopy and received no direct
sunlight.
Nest Searching – Systematic nest searches were based on male/female vocalizations
(Barg et al. 2006b, Rogers 2006) and other behavioral observations, such as food deliveries
and gathering of nesting materials (Jones and Robertson 2001). Nests were monitored at
least every two to three days, and food provisioning was quantified by recording time of
14
delivery and identity of the provider. Additional measurements at nest sites included: nest
tree species, nest tree DBH (cm), nest tree height (m), nest height (m), ratio of nest height to
nest tree height, straight-line distance from nest to tree bole (m), straight-line distance from
nest to end of branch (m), distance from nest to nearest above branch (m), distance from nest
to nearest canopy gap (m), distance from nest tree bole to nearest canopy gap (m) and
absence/presence of Brown-headed Cowbirds. A nest that produced at least one fledgling
was considered successful (Jones and Robertson 2001).
Reproductive Success - Because of their concealment in the upper canopy, Cerulean
Warbler nests can be both difficult and time consuming to locate. In such instances, using
behavioral clues or observations are the most efficient way to estimate breeding success
(Vickery et al. 1992). Such observations may include an adult carrying nesting material or
food, or in the case of the Cerulean Warbler, a male’s use of the “whisper song” (a quieter,
softer version of the typical song) is a reliable indication of a nearby potential female mate
(Weakland and Wood 2002, Barg et al. 2006b, Rogers 2006). For this study, an index of
reproductive activity (IRA) modified from Vickery et al. (1992) and Bonifait et al. (2006)
was used to approximate breeding productivity. The highest IRA score recorded for each
territory during the entire breeding season was used as an estimate of breeding success and
based on observations ranked into eight classes: (1) presence of singing male, (2) presence of
singing male displaying aggressive territorial behavior, (3) presence of singing male using
“whisper song”, (4) presence of singing male and female, (5) female observed carrying
nesting material, (6) nest located, (7) presence of nestlings or adult carrying food, and (8)
presence of fledglings. Breeding success was considered low for territories with a maximum
15
IRA score of one or two, medium for scores three through five, and high for scores six
through eight.
Mist-netting and Radio-telemetry
The evaluation of an animal’s use of space is essential for identifying specific habitat
requirements, movement patterns, and selection of natural resources. A home range is the
entire area, minus any exploratory “sallies”, that an animal uses to fulfill its life history
requirements (Burt 1943, Powell 2000). More specifically, it has also been referred to as a
utilization distribution (UD): the two-dimensional representation of the relative amount of
time an animal spends in an area over a certain period of time (Van Winkle 1975, Seaman
and Powell 1996). A territory or core area, on the other hand, is a defended area usually
located within a home range of which an animal has exclusive use (Powell 2000). Male
Cerulean Warblers were captured and radio-tracked for estimation of home range size and
core use areas. Males were also color banded to assist in determining site-fidelity and
distinguishing neighboring individuals.
Mist-netting was limited in 2005 due to a lack of USGS banding permits; however,
weekly efforts resumed at Walls of Jericho and periodically at Larkin Fork in 2006. A
wooden decoy and conspecific D. cerulea song were used to lure males into mist-nets erected
in either a triangular or stacked fashion (Fig. 8). Every bird captured was banded with a
single aluminum USFWS band and a unique combination of colored plastic leg bands.
Captured birds were aged as hatch-year, second-year, or after-second-year according to Pyle
(1997). Hatch-year birds (HY) were born during the current breeding season, second-year
16
birds (SY) were born the previous summer, and after-second-year birds (ASY) were at least
two breeding seasons old. Additional measurements included: relaxed wing length (mm), tail
length (mm) from vent, bill length (mm) from nostril, bill width (mm) at nostril, and bill
depth (mm) at nostril.
Transmitters were attached to males using a harness made of biodegradable
cornstarch. A single two mm wide strip piece was cut from a Dispoz-A-Scoop© pet waste
bag and glued to the top of each transmitter in a figure-eight loop (Rappole and Tipton 1991).
Harnesses were initially made in the field post-capture; however, once the appropriate size
was determined (~18 to 19 mm, extended length of each loop), they were made beforehand
to reduce handling time.
Each leg was placed into its corresponding loop resting the
transmitter above the synsacrum.
Cerulean Warbler males were tracked during three hour sessions in the morning
and/or mid to late afternoon. Locations were recorded every 10 to 15 minutes; however, this
interval was not always achievable during periods of erratic and silent movement. Therefore,
positions were marked as often as possible under singing males, in areas of equal signal
strength from at least three separate directions (indicating the male was overhead), or at the
site of a recovered transmitter.
Radio-telemetry data was analyzed using Home Range Tools for ArcGIS (Rogers et
al. 2005). Outliers, or occasional “sallies”, were removed before analysis by excluding the
5% of locations that deviated furthest from all other observations (Powell 2000). Home
ranges were then created using fixed kernel density estimators with a smoothing parameter
(h) selected through least squares cross validation (Seaman and Powell 1996, Barg et al.
17
2005). The resulting home range kernel was divided into probability contours in increments
of 10 (10% to 90%), where the smaller of two consecutive isopleths whose area doubled in
size was considered an area of core use (Barg et al. 2005).
In addition, an attempt was made in 2006 to record at least three locations
representing the furthest points an individual had traversed during an encounter without the
aid of radio-telemetry.
These coordinates were used to create 100% minimum convex
polygons (Mohr 1947, Robertson et al. 1998) as an estimate of daily, observed territory size.
Microhabitat Characteristics
Habitat structure and composition play a vital role in a land bird’s selection of
breeding territory and nest site (James and Shugart 1970, Cody 1981, Block and Brennan
1993). Vegetation measurements were taken within 0.04 ha (11.3 m radius) circular plots
from “used” habitat, “random” habitat, “available” habitat, and nest sites (Jones 2001). For
this study, “used” habitat was centered at Cerulean Warbler perch/foraging trees, whereas
“random” habitat was generated points where Ceruleans were not detected. “Available”
habitat plots were centered within a 100% minimum convex polygon (MCP) constructed
from an individual’s home range radio-telemetry data when a sufficient number of locations
were available to delineate its boundary. Selection of sampled “used” habitat plots was
dictated by point count locations followed by a stratified random process to account for the
remaining territories. On most occasions, all measurements were taken by the author to
eliminate any biases.
18
Microhabitat variable codes and descriptions are presented in Appendix B.
An
ultrasonic transponder (Haglof©) was used to mark the extent of plot boundaries. Habitat
variables measured within the entire plot included tree species and number of trees ≥3 cm
DBH. Basal area (BA) was derived from:
BA(m2) = 0.00007854DBH2
and was also used to calculate the ratio of number of trees/basal area per ha.
Seedlings/shrubs and canopy cover were measured along two right-angle transects set
in the cardinal directions. Total number of woody stems <3 cm DBH and at least 1.3 m tall
intercepted by out-stretched arms were used to estimate understory density per ha (James and
Shugart 1970). Percent canopy cover was determined using 40 +/- densitometer readings
(twenty along each transect) of vertical, green vegetation. A densitometer contains an angled
mirror and offset leveling vials housed inside of two joined, perpendicular tubes that allows
for exact vertical line-of-sight measurements (Geographic Resource Solutions©).
In
addition, canopy structure was quantified by assigning each reading to a height interval (no
cover, <2 m, ≥2 <5 m, ≥5 <15 m, ≥15 <25 m, ≥25 m). Upper, middle, and lower canopy
heights (m) were measured from trees classified as dominant and co-dominant, intermediate,
and suppressed, respectively.
Log and tree dispersion were estimated in the four quarters of each plot by measuring
distance to and DBH of the nearest tree, and distance to, DBH (taken ~1.3 m from the largest
end), and length of the nearest fallen log ≥1.5 m in length and ≥8 cm DBH (Noon 1981).
19
Canopy gaps are often created from a fallen tree or large branch; therefore, logs (downed
woody debris) were used as an measure of localized disturbance.
Slope of each plot was estimated using a clinometer. Aspects were transformed and
assigned values ranging from 0.0 to 2.0 using the equation:
1 + cos (45 – aspect)
This distinguishes less productive, southwest facing slopes (value = 2.0) from more
productive, mesic northeast slopes (value = 0.0) (Beers et al. 1966, van Manen et al. 2005,
Wood et al. 2005a). A plot with a slope = 0.0 was considered flat and received an aspect
value = -1.0.
Distance to and size of the nearest and largest canopy gaps <50 m from plot center
were measured using the modified protocol of Runkle (1992).
Gaps were defined as
openings ≥10 m2 and could be either natural or man-made. Vertical regeneration within the
gap along two perpendicular axes, representing the longest and widest points of its boundary,
could not exceed 15 m when the average surrounding canopy height was ≥25 m. If the
surrounding canopy was <25 m, regeneration height within the gap could be no more than
half the average canopy height (Jones et al. 2001). Area of each gap was calculated by
summing the lengths of the two axes, which were measured using a transponder, tape
measurer, and/or by pacing, but gaps were eventually categorized into relative sizes: ≥10 m2
<20 m2, ≥20 m2 <30 m2, ≥30 m2 <40 m2, and ≥40 m2. Bearing to (from plot center) and
orientation of each gap was also recorded.
20
Landscape Associations
Geographic Information Systems (GIS) significantly increase productivity by
allowing researchers to efficiently survey and analyze many aspects of wildlife ecology
without the spatial and temporal limitations of traditional methods (Shaw and Atkinson
1990). ArcView v.3.2a (ESRI 2000) and ArcGIS v.9.1 (ESRI 2005) were used to examine
associations of all habitat plots with surrounding landscape features and land use practices.
All data were projected using North American Datum (NAD) 83 Universal Transverse
Mercator (UTM) Zone 16.
The basis for land cover analyses was the 2001 National Land Cover Data (NLCD)
raster dataset (30 m2 resolution). Mapping was derived from 2000 Landsat-7s Enhanced
Thematic Mapper (ETM) images and developed by the US Environmental Protection
Agency’s (EPA) Multi-Resolution Land Characteristics (MRLC) consortium. The original
classification scheme was reduced from 15 to nine classes because of high similarities in
several variable descriptions (Appendix C).
Two types of metrics were analyzed to help define Cerulean Warbler habitat:
landscape composition and landscape configuration (McGarigal and Banks 1995).
Composition refers to the abundance of a land cover type or attribute, whereas configuration
describes the spatial arrangement of patches or features. Variable codes and descriptions of
all landscape metrics are presented in Appendix D.
Each habitat plot was assigned a unique identification number and buffered with a 1km polygon. Patch Analyst Grid v.3.0 (Rempel 1997) calculated fragmentation statistics
through “Region Analysis”, whereby each buffer was examined as an independent region.
21
For calculation of edge statistics, the “Boundary influence” was set to zero so that grid cells
located along the perimeter of the 1-km buffer would not be affected by this artificial
boundary/edge. Percent land cover for each class was determined using “Thematic Raster
Summary” available in Hawth’s Analysis Tools v.3.27 (Beyer 2006).
Habitat plot GPS locations were spatially joined with US Census Bureau 1999 Tiger
road shapefiles and US EPA 1994 Reach Files v.3 (RF3) stream shapefiles to measure
distances (m) to nearest road and nearest stream, respectively. Total length (m) of roads and
streams within each buffer was calculated using the “Sum Line Length” tool (Beyer 2006),
and elevations (m) were obtained using zonal statistics derived from a USGS digital
elevation model (30 m2 resolution). Furthermore, all fields nearest to “used” habitat plots at
Walls of Jericho and Larkin Fork were delineated by digitizing 1999 and 2005 aerial
orthophotographs using ArcGIS.
Habitat Modeling
Potential Cerulean Warbler habitat in Jackson, Lawrence, and Winston Counties was
identified using ArcView v.3.2a and ArcGIS v.9.1. All models were created by combining
several grid layers (30 m2 cell resolution), which individually represented a landscape
variable selected through Akaike’s information criterion (see Statistical Analysis below) as a
reliable predictor of Cerulean Warbler occurrence.
The Spatial Analyst extension for ArcGIS v.9.1 was used to calculate a densitybased, distance-based, or percent-based value for every cell in each layer. Any layers
composed of continuous data (i.e. digital elevation model) were used as is. “Line Density”
22
was used to measure the total length of all roads and streams within 1-km of every cell, and
“Straight Line Distance” was used to measure the distance from each cell to the nearest road
and stream.
Land classes were independently converted to a binary system (0 = absent, 1 =
present) to obtain land cover percentages within 1-km of each cell.
“Neighborhood
Statistics” summed present cells within the search radius, and the resulting grid was
transformed to a floating point pixel type, which was required to produce decimal values in
subsequent mathematical computations. Using the raster calculator in ArcGIS, each grid
layer was divided by the total number of cells (3,491) within the 1-km radius and multiplied
by 100 to achieve the total percentage of that land cover surrounding each grid cell. The
final habitat models were then created using two multivariate statistical methods:
Mahalanobis distance (D2) and binary logistic regression (see Statistical Analysis below).
Statistical Analysis
Distribution – A single centroid for each Cerulean territory mapped in 2006 was used
in a nearest neighbor (NN) analysis to determine the amount of aggregation present among
the three populations. The average nearest neighbor tool in Spatial Analyst (ESRI 2005)
measured and compared Euclidean distances between bird locations and a hypothetical,
computer generated random distribution.
An index was calculated for each study site by
dividing the observed mean distance by the expected mean distance. Values ≥1.0 suggested
a random distribution, whereas ratios <1.0 exhibited clumping (Clark and Evans 1954).
23
Point counts – Mean species richness (S’) was calculated as the total number of
species detected during each count, and mean bird abundance was considered the total
number of individuals counted at each location. Independent sample t-tests were used to test
for differences in bird species richness and abundance between “used” and “random” plots.
Avian Associations - Canonical correspondence analysis (CCA) was performed to
detect patterns of variation in avian community composition and species abundance as they
related to microhabitat characteristics. Ordination employs multiple regression to obtain an
average weight for all species and vegetation traits present at each sampling unit. These
weighted values are plotted along a gradient and represent the “center” of the animal’s and
habitat variable’s distribution in relation to that particular location, which can then be used to
highlight environmental characteristics that best explain species occurrence (ter Braak 1986,
1995). Lines are used to represent habitat features and illustrate their relationships with the
avian community. The longer a line is and the closer a species lays to its tip, the stronger
their correlation (ter Braak 1986). Furthermore, a weaker affiliation exists when a species is
plotted at the opposite end or side of a line’s origin. Species and habitat variable scores were
standardized by centering and normalizing, and avian species’ ordination scores were
optimized for scaling using PC-ORD v.4.01 (McCune and Medford 1999). Only species
with ten or more detections were included in the CCA.
Tree Use – Chi-square statistics (x2) were performed to detect preferences for tree
species, crown class, and relative locations within the tree using the equation:
k
ˆ 2
x2 = ∑ (ƒi -ˆ ƒi)
i=1
ƒi
24
where ƒi is the frequency (i.e. number of counts observed in class i), ƒˆi is the expected
frequency, and k the number of categories (Zar 1999).
Microhabitat and Landscape Characteristics – Standardized residuals of each
variable were examined to test the assumptions of normality, and an attempt was made to
correct any non-normal distributions and/or heteroscedasticity using log10 or square-root
transformations. Due to the conservation status of the Cerulean Warbler, an alpha level of
0.1 was selected for all tests of significance (Askins 1990, Bosworth 2002).
Independent sample t-tests were employed to compare means of “used” habitat plots
with all “random” plots, and two-sample Mann-Whitney U-tests were used for mean
comparisons of those variables unable to meet normality requirements.
Due to such small
sample sizes of nest (n = 4) and “available” habitat (n = 2), these factors were not included in
any of the analyses.
Analysis of variance (ANOVA) and post-hoc Tukey tests were used to determine if
and where differences existed among microhabitat and landscape measurements sampled
from the three Cerulean Warbler populations. Non-parametric Kruskal-Wallis tests (H)
followed by repeated Mann-Whitney U-tests using an adjusted alpha level were performed
for mean comparisons of those variables unable to meet the assumptions of normality. The
adjusted significance level was obtained through a Bonferroni correction, which was
calculated by dividing the original alpha level by the number of comparisons.
Canopy structure and complexity were assessed using the Shannon-Wiener diversity
index (H’):
25
H’ =
nlogn - ∑ƒilogƒi
n
where n is the sample size and ƒi the number of observations for each canopy height category
(Zar 1999). To obtain the proportion of maximum possible diversity, evenness (J’) was
calculated as:
J’ =
H’
H’max
where H’max is logk with k equal to the number of parameters. The closer J’ is to 1.0, the
more evenly distributed and diverse the category is (Zar 1999).
Habitat Modeling – Pearson’s correlation matrices were used to examine collinearity
among landscape characteristics; only one variable from each relationship with r ≥0.9 was
retained for modeling.
An information-theoretic approach (Burnham and Anderson 2004) was used to select
the best-fit model for construction of the Cerulean Warbler habitat models.
Akaike’s
information criterion (AIC) has become a popular choice for habitat model selection due to
its ease of interpretation in comparison of competing hypotheses and because it allows the
researcher to select habitat characteristics they deem most ecologically important to the
species under investigation (Burnham and Anderson 2004). For this study, a series of
landscape variable combinations were selected a priori for inclusion into the models based
on Cerulean Warbler literature (Robbins et al. 1992, Hamel 2000a, 2000b, Wood et al.
2005a), results of “used” vs. “random” landscape comparisons, and personal observations.
A second-order bias correction (AICc) was chosen as n/K was <40:
26
(AICc) = -2loge(L) + 2K + 2K(K +1)
(n + K + 1)
where -2loge(L) is the log-likelihood function derived from binary logistic regression and K
is equal to the number of parameters in the model + 1 (Burnham and Anderson 2004). AIC
scores were then rescaled to remove constants following:
∆i = AIC – AICmin
This transforms the ∆i of the best model to 0.0; generally models with ∆i ≤2.0 demonstrate
substantial support.
Evidence ratios, or the likelihood that model i is better than model j,
were adjusted to Akaike weights (wi) by:
c/2)
wi = exp(-∆
R
∑exp(-∆c/2)
r=1
This “weight of evidence” displays a model’s strength as a probability with the highest ratio
equating to the best-fit model (Burnham and Anderson 2004). The relative importance of
each variable, w+(j), was determined by summing the Akaike weights for all models that
contained the variable under inspection (Burnham and Anderson 2004, Welsh and
MacMahon 2005). All variables included in the model with the lowest ∆i and wi were used to
construct the final habitat maps.
Mahalanobis distance (D2) is preferred for wildlife and plant species modeling
because it requires only presence data and thus eliminates the possibility of misclassifying
“available” habitat as “unused” (Clark et al. 1993, Dettmers and Bart 1999, Browning et al.
27
2005, Van Manen 2005, Buehler et al. 2006a, Thatcher et al. 2006). The Mahalanobis
statistic is the squared, standardized distance between occupied locations and the mean center
of all observations (grid cells) in the study area (Clark et al. 1993, Rotenberry et al. 2006).
Smaller D2 values indicate areas or cells “closer” to the environmental characteristics found
at occupied locations and are therefore considered more similar to the focal species’
preferred habitat (Van Manen et al. 2005). “Used” and nest site habitat plots were selected
as presence data and D2 values were calculated by importing all GIS grid layers into the
ArcView v.3.2a Mahalanobis distances extension (Jenness 2003).
Binary logistic regression has been used to predict species occurrence or density for a
number of wildlife, GIS-based models (Fleishman et al. 2001, Osborne et al. 2001, Apps et
al. 2004, Gibson et al. 2004, Buehler et al. 2005). This method is advantageous because
models are scaled from 0.0 to 1.0 according to probability of use and are thus easy to
interpret. Furthermore, the independent variables are not required to meet the assumptions of
multivariate normality (Gray et al. 1996). The dichotomous dependent variable indicating
presence or absence was derived from “used” and nest sites and “random” habitat plots,
respectively. The logistic regression coefficient (β0, β1, …, βp) for each landscape variable
included in the best AIC model was multiplied by its corresponding GIS layer (x1, …, xp) and
summed so that β´x = β0 + β1x1 + … βpxp. Probability of Cerulean Warbler occurrence (P)
was calculated as:
P=
(exp, β´x)
1 + (exp, β´x)
28
with exp equal to 2.71828. This result was then used to derive the probability of occurrence
(P) in ArcGIS and entered into the raster calculator as:
P=
Pow(exp, β´x)
1 + Pow(exp, β´x)
where Pow raises 2.71828 to the power of β´x.
All statistical analyses were performed using SPSS v.10.0 (SPSS, Inc.©), except for
AIC and J’ values, which were calculated in Microsoft Office Excel 2003 (Microsoft, Inc.©).
Unless otherwise noted, all means are ± the standard error (SE).
29
CHAPTER 3
RESULTS
Distribution and Relative Abundance
During the 2005 and 2006 breeding seasons, Cerulean Warblers were only detected in
Jackson County at Walls of Jericho and Larkin Fork, and in Lawrence County at Bankhead
National Forest. No Cerulean Warblers were encountered at “random” points or during
additional target searches throughout northern Alabama (Appendix E).
Walls of Jericho (Fig. 3) – Cerulean Warblers were detected as early as April 16th in
both 2005 and 2006. The majority of this population occurred within the boundaries of the
preserve along the floodplain of Hurricane Creek; males were periodically observed south of
the property line and north into Tennessee. In both 2005 and 2006, 18 males and three
females were observed at Walls of Jericho (Table 1). The number of fledglings detected
increased from two individuals from two territories in 2005 to four individuals from three
territories in 2006. The nearest neighbor index for this population was 0.67 (272.1 m
observed/408.7 m expected) and exhibited significant clumping, P (Z = -2.79) < 0.001 (Fig.
9).
Larkin Fork (Fig. 4) – Ceruleans were detected as early as April 10th and April 21st in
2005 and 2006, respectively. In 2005, 15 males, two females and one fledgling were present;
30
in 2006, 15 males, five females and one fledgling were found at Larkin Fork (Table 1). This
population spans approximately 3.5 km along the floodplain of Larkin Fork and had a
nearest neighbor index of 0.78 (165.8 m observed/212.8 m expected). Even though this
population was significantly aggregated, P (Z = -1.69) < 0.05, Cerulean Warblers were more
randomly distributed here than at Walls of Jericho (Fig. 9).
Bankhead National Forest (Fig. 5) – Cerulean Warblers were detected as early as
May 19th and April 28th in 2005 and 2006, respectively. In 2005, 13 males were encountered,
and in 2006, 17 males, three females, and three juveniles were observed (Table 1). Ceruleans
were only found in the northwestern portion of BNF in Lawrence County, and the majority of
this population occurred within and just outside of the Sipsey Wilderness Area,
predominately along Flannigan and Borden Creeks. Cerulean Warblers here were not as
clumped as those at Walls of Jericho but exhibited a distribution more similar to the Larkin
Fork population. The average nearest neighbor ratio was 0.78 (454.9 m observed/581.0 m
expected) with P (Z = -1.66) < 0.04 (Fig. 9).
Bird Surveys
Point Counts - A total of 53 “used” and 51 “random” point counts were conducted in
2005 and 2006. See Appendices F and G for a list of all species detected. Species richness
(S’) was significantly higher (t = 4.79, P < 0.001) at “used” locations (mean = 9.2 ± 0.3,
Range = 5-15) than “random” (mean = 7.2 ± 0.3, Range = 2-14), and birds were also
significantly more abundant (t = 3.52, P < 0.001) at “used” counts (mean = 11.7 ± 0.5, Range
= 6-27) than at “random” (mean = 9.5 ± 0.4, Range = 5-16) (Fig. 10). Brown-headed
31
Cowbirds were encountered on three separate occasions in “used” habitat: two individuals
roughly 600 m apart at Walls of Jericho in 2005, and a flock of four individuals at Larkin
Fork in 2006.
Avian Associations – Scatter biplots (Figs. 11-13) separated most sympatric warbler
and deciduous forest-dwelling bird species from an inhabitant of pine forests, the Pine
Warbler (Dendroica pinus Wilson). The species plotted nearest to Cerulean Warbler were
Kentucky Warbler (Oporornis formosus Wilson), Louisiana Waterthrush (Seiurus motacilla
Vieillot), Acadian Flycatcher (Empidonax virescens Vieillot), and Indigo Bunting (Passerina
cyanea L.).
Tree Use - Cerulean Warblers used an average tree height of 25.7 m (± 0.4, Range =
5.25-49.0, n = 363) and average DBH of 37.9 cm (± 0.8, Range = 2.2-120.5, n = 392). They
preferred the outside (x2 = 59.0, df = 2, P < 0.001), upper canopy (x2 = 62.0, df = 2, P <
0.001) of co-dominant trees (x2 = 204.7, df = 3, P < 0.001). Black Walnut (Juglans nigra L.)
was the most preferred tree species (x2 = 151.6, df = 9, P < 0.001) and accounted for 20.8%
of all observations. The proportion of used stems relative to their availability was greater for
eight out of the ten most popular tree species selected by Cerulean Warblers (Fig. 14), and
mean heights and diameters of trees used were larger than the means of all available stems of
those same species sampled from “used” and nest site habitat plots (Fig. 15).
Nesting and Reproductive Success
Walls of Jericho – No nests were found at Walls of Jericho in 2005 and 2006. In
2004, two nests were discovered along Hurricane Creek by E. Soehren (ADCNR) and A.
32
Lesak (AAMU); both attempts were unsuccessful due to abandonment or depredation. Of all
three populations, the number of encounters with fledglings was highest at Walls of Jericho
during both seasons, which doubled from two (each belonging to a different territory) in
2005 to four (from three territories) in 2006.
According to the IRA index (Table 1),
estimated reproductive success was low for greater than 70% of territories in both years (Fig.
16).
Larkin Fork – No nests were found at Larkin Fork, and only one fledgling was
encountered during each breeding season. Several more behavioral observations indicative
of nesting success were witnessed in 2006, including the presence of more than twice as
many females as compared to the previous summer (Table 1). On one occasion, a male was
observed rubbing his cloaca in the fork of a branch as if signifying the potential of the
location as a nest site. The female then replaced the male and repeated the action in the same
spot; however, no nest was found in the vicinity. Estimated reproductive success was low in
2005 and moderate in 2006 (Fig. 16).
Bankhead National Forest - One nest was discovered in 2006 just outside of the
Sipsey Wilderness near the confluence of Horse and Borden Creeks. Only two feeding
surveys were performed before both juveniles fledged (Fig. 17). At least two nestlings were
observed during the first survey, which was conducted in late afternoon for roughly 120
minutes immediately after the discovery. The second survey was performed for
approximately four hours the following morning. By this time, one nestling had already
fledged and was seen just below the nest before moving to a nearby oak tree. The remaining
nestling prematurely left the nest after a Black-throated Green Warbler (Dendroica virens
33
Gmelin) approached and peered into the cup, which was quickly chased off by the adult male
Cerulean. This fledgling stayed close to the nest during the remainder of the survey. The
male parent accounted for greater than 75% of deliveries to the nestlings per 30 minutes
(mean = 3.9 ± 0.5, Range = 0-8), whereas the female averaged only 0.4 ± 0.6 (Range = 0-3).
An additional nest was found along Horse Creek in 2004 by E. Soehren; the fate of this nest
was unknown.
No fledglings were detected at BNF in 2005; however, three males were observed
carrying Lepidoptera spp. late in the breeding season suggesting the presence of young. In
2006, a male, female, and juvenile Cerulean Warbler were found foraging near Borden Creek
on July 31, 2006. This encounter was not included in the IRA scores because of their close
proximity (~500 m) from the nest site mentioned previously. Estimated reproductive success
was low in both years, and the lowest IRA rankings recorded for all three populations were
from Bankhead NF in 2006 (Table 1, Fig. 16).
Mist-netting and Radio-telemetry
Mist-netting - In 2005, ten attempts on ten different Cerulean Warbler males resulted
in three captures (Table 2). Only one attempt was performed at Larkin Fork, which failed
when two agitated neighboring Cerulean males became preoccupied with chasing one
another. A triangular net design was used during every attempt.
In 2006, a total of 25 attempts were made on 18 males resulting in eleven captures
(Table 2). At Larkin Fork, six attempts on six individuals yielded three captures, while 19
attempts on 12 individuals produced seven captures at Walls of Jericho. A triangular net
34
design was used during six attempts and resulted in two captures, whereas a stacked design
was used on the remaining 19 attempts and yielded eight males. The eleventh male was
captured passively at Walls of Jericho during an unrelated study using a single, standard size
mist-net.
Age Demographics – In 2005, two males were aged as after-second-year (ASY) and
the other as a second-year (SY). In 2006, seven males were aged as SY and the remaining
four as ASY (Table 2).
Site Fidelity - Two of three males banded in 2005 returned to Walls of Jericho the
following season. One male exhibited high site tenacity while the other defended a territory
roughly 300 m from where he was banded the previous year.
Radio-telemetry - Transmitters were attached to eight Cerulean Warblers in 2006;
however, only three males retained them long enough for telemetry analysis. The mean
weight of transmitters, including harness and glue, was 0.39 g (± 0.03, Range = 0.36-0.44, n
= 7) and accounted for an average 4% (± 0.3, Range = 3.5-4.7, n = 7) of the bird’s body
weight. The longevity of each harness varied from as little as a few hours up to 29 days.
Of those tracked, two birds had enough locations to produce kernel density estimators
(Fig. 18). Cerulean #1 had a total of 35 locations recorded every 32.2 minutes (± 6.1) with a
kernel home range of 4.15 ha (h = 0.435439), core use area of 0.15 ha, and a 95% MCP of
4.02 ha. Cerulean #2 had a total of 97 locations recorded every 17.3 minutes (± 1.2) with a
kernel home range of 7.09 ha (h = 0.225958), core use area of 0.20 ha, and a 95% MCP of
8.03 ha. Cerulean #3 had a total of eight locations recorded every 21.6 minutes (± 5.4) and a
95% MCP of 1.23 ha. In summary, the average kernel home range was 5.62 ha (± 1.48) with
35
a mean core use area of 0.18 ha (± 0.02). The average 95% minimum convex polygon for all
three males was 4.43 ha (± 1.97).
The average observed, daily territory size for 35 Cerulean Warbler males in 2006 was
0.15 ha (± 0.02, Range = 0.0001-0.6669, n = 54). Surveys lasted an average 83.3 minutes (±
6.2, Range = 10.0-200.0, n = 40), and 100% minimum convex polygons were created with an
average 3.8 locations (± 0.16, Range = 3.0-9.0, n = 54). There was no difference (H2 = 1.8, P
< 0.398) in observed territory size based on study site (Fig. 19).
Microhabitat Characteristics
In total, 83 “used”, 51 “random”, four nest, and two “available” habitat plots were
sampled in 2005 and 2006 (Table 3). When compared to “random” habitat, “used” plots had
significantly fewer live trees ≥3 cm DBH (NTREE, Z = -3.757, df = 133, P < 0.001), higher
basal area to tree stem ratio (RBATR, Z = -3.819, df = 133, P < 0.001), greater percentage of
deciduous basal area (DECBA, Z = -5.025, df = 133, P < 0.001), taller middle and upper
canopy heights (MIDHT, t = -3.056, df = 129, P < 0.003; UPHT, t = -2.586, df = 133, P <
0.011), greater canopy cover (CNPYCVR, Z = -4.327, df = 133, P < 0.001), larger diameter
trees near plot center (TRDBH, Z = -6.017, df = 133, P < 0.001), and downed logs further
from plot center (LOGDIS, t = -1.834, df = 129, P < 0.069). They also occurred in areas
with shorter lower canopy height (LOWHT, t = -1.968, df = 133, P < 0.051), less complex
canopy structure (CNPYSTR, t = 1.728, df = 133, P < 0.086), and fewer seedlings/shrubs
(UNDRSTRY, Z = -2.358, df = 133, P < 0.018).
36
Cerulean Warblers at Walls of Jericho were encountered in areas with fewer total tree
stems (NTREE, F2,82 = 3.51, P < 0.035), taller middle canopy height (MIDHT, F2,80 = 3.74, P
< 0.028) and lower average aspect score (ASPCT, H2 = 8.40, P < 0.015) (Fig. 20) than at
Bankhead NF (Table 4). Habitat plots at Walls of Jericho and Larkin Fork had shorter upper
canopy heights (UPHT, F2,82 = 8.04, P < 0.001), larger canopy gaps within 50 m of plot
center (LGAPSZ, H2 = 7.55, P < 0.023), fewer seedlings/shrubs (UNDRSTRY, F2,82 = 4.53,
P < 0.014), larger diameter downed logs (LOGDBH, F2,82 = 4.88, P < 0.010), and downed
logs of greater length (LOGLNG, F2,82 = 5.28, P < 0.007) as compared to Bankhead NF.
Furthermore, the average distance to the nearest tree in each quarter from plot center was
greater at Walls of Jericho than Larkin Fork (TRDIS, F2,82 = 3.80, P < 0.027), and the nearest
canopy gap within 50 m of Larkin Fork samples was larger than those measured at Bankhead
NF (NGAPSZ, H2= 4.84, P < 0.089).
Canonical Correspondence Analysis – CCA related Cerulean Warbler abundance to
large diameter, deciduous trees (Fig. 11). Positive yet weaker associations existed with upper
canopy height and size of the nearest canopy gap ≥10 m2 (Fig. 11). A negative correlation
between Cerulean Warblers and tree density was also evident in Axes 1 and 3 (Fig. 12).
Eigenvalues were 0.219 for axis 1, 0.128 for axis 2, and 0.095 for axis 3. The total inertia
(i.e., variance) for all three axes was 3.9245, and 11.3% of the species data was explained by
the ordination (equal to the sum of the eigenvalues divided by the total inertia). Speciesenvironment correlations were high for axis 1 (0.818) but decreased with axis 2 and 3 (0.768
and 0.583, respectively).
37
Nest Site Characteristics - Cerulean Warblers chose a different tree species for each
of the four nests discovered during the course of the study (Table 5). All nests were built in
the upper half of its tree, which averaged 20.9 m (± 1.6, Range = 17.0-23.5).
Distance to
bole (mean = 5.2 m ± 3.8, Range = 1.1-12.8, n = 3) and nest tree diameter (mean = 38.0 cm ±
14.3, Range = 13.2-76.1, n = 4) were both highly variable. Canopy gaps were present at only
two locations. The first was a natural opening ≥10 <20 m2 along a creek and situated 1.5 m
from the nest and 13.5 m from the tree bole; this nest was successful and produced at least
two fledglings. The second gap was a large (≥40 m2) opening near a riparian corridor
bordered by a succession change in forest structure and was located 30 m from both the nest
and tree bole; this nest site was abandoned.
Landscape Associations
Barren rock accounted for a negligible amount (0.001%) of the total land cover in
Jackson, Lawrence and Winston Counties and was excluded from analyses due to its trivial
contribution to the overall composition of each landscape.
Refer to Appendix D for
landscape variable descriptions.
As compared to “random” habitat plots, Cerulean Warblers were found at lower
elevations (ELEV, t = 6.788, df = 133, P < 0.001), farther from roads (ROAD, Z = -2.454, df
= 133, P < 0.014), closer to streams (STRM, Z = -6.326, df = 133, P < 0.001), and were
surrounded by a greater density of streams (TSL, t = 5.936, df = 133, P < 0.001) (Table 6).
Ceruleans also chose territories in areas with fewer open bodies of water (WATER, Z =
-4.394, df = 133, P < 0.001), surrounded by less impervious surfaces (DVLPD, Z = -4.809, df
38
= 133, P < 0.001), less evergreen forest (EVER, Z = -3.347, df = 133, P < 0.001), fewer
grasslands (GRASS, Z = -3.035, df = 133, P < 0.002) and less edge (ED, t = 6.829, df = 133,
P < 0.001). Moreover, they occupied sites dominated by deciduous-mixed forest (DECMX,
Z = -5.717, df = 133, P < 0.001) with a greater abundance of core area (TCAI, Z = -4.929, df
= 133, P < 0.001) that was composed of larger, more complex-shaped patches (MCA, Z =
-5.703, df = 133, P < 0.001; MPFD, Z = -2.568, df =133, P < 0.001).
Differences among the three populations became exacerbated at the landscape level
(Table 7). Ceruleans at Bankhead NF were found breeding at lower elevations (ELEV, H2 =
36.31, P < 0.001) in areas surrounded by denser evergreen cover (EVER, F2,82 = 292.16, P <
0.001) and a more extensive stream network (TSL, F2,82 = 16.63, P < 0.001). Walls of
Jericho had a greater abundance of larger core areas (TCAI, F2,82 = 75.26, P < 0.001; MCA,
F2,82 = 79.83, P < 0.001) and the lowest percentage of developed area (DVLPD, F2,82 = 243.1,
P < 0.001). Larkin Fork Ceruleans chose to breed in an area bounded by more shrubland
(SHRUB, H2 = 70.46, P < 0.001), grassland (GRASS, F2,82 = 39.61, P < 0.001), and
agriculture (AGRI, H2 = 54.41, P < 0.001).
Furthermore, each population significantly differed from each other in distance to
nearest road (ROAD, H2 = 62.06, P < 0.001) and road density (TRL, F2,82 = 294.05, P <
0.001) with Larkin Fork containing more than three times as much road length as Bankhead
NF and over 500 times the amount surrounding Walls of Jericho plots. Edge density was
significantly more prevalent at Bankhead NF (ED, F2,82 = 79.75, P < 0.001), which was one
and a half and three times greater than at Larkin Fork and Walls of Jericho, respectively.
39
All three populations occurred close to streams (STRM, F2,82 = 0.97, P < 0.381), far
from open bodies of water (WATER, H2 = 0.00, p < 1.00), and had similar mean patch fractal
dimension indices (MPFD, F2,82 = 2.29, P < 0.108).
Habitat Modeling
Edge density (ED), total core area index (TCAI) and percent deciduous-mixed forest
cover (DECMX) were highly correlated (r ≥0.9) and as a result, only DECMX was kept for
habitat modeling because its implementation in GIS was less complicated. In addition, mean
core area (MCA) was also removed from habitat modeling because creation of core areas for
use in the models required the user to set a minimum buffer distance, which defined how
isolated the inner cells of a patch must be for inclusion as core area. In many instances
during this study, Cerulean Warblers were encountered near dissimilar patches of land cover
types. Therefore, selecting a buffer distance would have been arbitrary and may have even
excluded potential habitat.
The best AIC model included seven landscape variables that best explained
Cerulean Warbler presence (Table 8). A landscape characterized by lower elevations, a high
percentage of deciduous-mixed forest cover and in close proximity to streams was most
indicative of D. cerulea occurrence in northern Alabama.
Habitat far removed from
development was also more favorable with the nearest impervious surface an average 3.7 ha
(± 0.6) and 1.2 km (± 88.7 m) from “used” habitat plots. Positive relationships also existed
with stream and road densities and distance to nearest road. The most to least important
variables included in the top model were as follows: elevation and percent deciduous-mixed
40
forest (w+(j) = 0.9973), total road and total stream length (w+(j) = 0.9964), distance to nearest
stream (w+(j) = 0.9893), percent developed land (w+(j) = 0.9843), and distance to nearest road
(w+(j) = 0.9788).
Logistic regression and Mahalanobis distance models are displayed in figures 20-24.
“Used” and nest sites (n = 86) had a combined average Mahalanobis distance of 7.0 (± 0.5,
Range = 1.2-22.9) (Fig. 25) and probability of use equal to 86.1% (± 3.0, Range = 0.0-100.0)
(Fig. 26). The average “random” plot (n = 45) had a Mahalanobis distance of 326.4 (± 67.9,
Range = 12.5-2496.1) (Fig. 25) and a probability of use of only 4.0% (± 2.4, Range = 0.080.0) (Fig. 26).
41
CHAPTER 4
DISCUSSION
Distribution and relative abundance
Assuming that each male encountered was mated, there were approximately 45-50
pairs of Cerulean Warblers breeding in northern Alabama in 2005 and 2006. Because not all
birds were banded, estimates may fluctuate plus or minus a few pairs.
Walls of Jericho – The distribution and relative number of Cerulean Warblers
remained stable at Walls of Jericho from 2005 to 2006. The bulk of this population in both
years lay in the northern half of the preserve, which may also spillover into southeastern
Tennessee. This population appears to be limited in growth to the south as the floodplain
widens and a transition from forest to alternate land cover types begins.
Larkin Fork – The abundance and distribution along Larkin Fork also remained
consistent over the two year study. During both seasons, a few territories to the south were
separated from the rest of the population by roughly 800 m. This isolation may indicate the
end of Cerulean Warbler expansion farther south as the forested floodplain habitat along
Larkin Fork becomes scarcer.
Bankhead National Forest - The surplus in detections at Bankhead NF in 2006 was
likely the result of an increase in search effort and not reproductive output or immigration.
42
In 2006, Ceruleans were found farther north along the upper portions of Flannigan and
Borden Creeks than in previous surveys; however, the heart of this population appears to be
concentrated near the Sipsey Wilderness Area. Because of its size, surveys were more
limited at Bankhead NF than the other two study sites, and Ceruleans may be breeding in
additional areas that were not visited.
Aggregation - Cerulean Warblers have often been noted as colonial-like breeders
(Griscom 1979, Hamel et al. 1994, Oliarnyk and Robertson 1996), but most of the evidence
is purely anecdotal.
In the Mississippi Alluvial Valley, Hamel (1995) found that one
Tennessee population was clumped and another uniformly distributed, whereas a high degree
of aggregation among three populations was reported in southern Indiana (Basile 2002, Islam
and Roth 2004).
Campbell (1996) argued that fine-scale patterns are often over-shadowed by large
scale aggregation, and also warned that sample variance may be compromised by edgeeffects and the presence of reciprocal pairs.
For this study, an extent boundary was
calculated for each population [area = (xmax – xmin) x (ymax – ymin)] to reduce the influence of
edge-effects and account for the linear distribution of territories. This analysis included
practically every individual present at each site and was therefore not weakened by the
limitations of testing only a sub-sample from the entire population.
Bird Surveys
Point counts – Cerulean Warblers have been cited as associates of several bird
species, including Kentucky Warbler (O. formosus), American Redstart (Setophaga ruticilla
43
L.), Northern Parula (Parula americana L.), and Blue-gray Gnatcatcher (Polioptila caerulea
L.) (Lynch 1981, Hamel 2000a). All of these species were detected on counts at “used”
locations, and interactions between Cerulean Warblers and several of these species escalated
to physical contact on several occasions. Red-eyed Vireos (Vireo olivaceus L.) and Northern
Parulas appeared to be particularly sensitive to the use of D. cerulea playback and both were
often observed competing with Cerulean Warblers for upper canopy resources.
Avian Associations – The Cerulean’s closest allies were those species that breed near
streams (S. motacilla), in moist woodlands (O. formosus), and in deciduous bottomland
forests (E. virescens) (Ehrlich et al. 1988). Indigo Buntings are an abundant species and
were often detected in and around small fields scattered throughout the Jackson County
populations. A Great-blue Heron (Ardea herodias L.) rookery was present along Larkin Fork
during both field seasons and the reason for its placement near Ceruleans in the biplots.
The middle of the biplot represents the grand mean and origin of each environmental
trait, and species considered as habitat generalists are most likely to be found near the plot
center (Allen et al. 2006). Eastern Tufted Titmouse (Parus bicolor L.), Carolina Wren
(Thryothorus ludovicianus Latham) and Carolina Chickadee (Parus carolinensis Audubon)
are all common year-round residents found in a wide variety of habitats (Ehrlich 1988). All
three of these species received some of the lowest correlations (r <0.03), thus explaining their
placement within the center of the biplot for Axes 1 and 2.
Because species richness and abundance were significantly higher in “used” areas,
managing forests for Cerulean Warbler habitat may be beneficial for a wide range of avian
species.
The recognition of these avian relationships, especially the corresponding
44
similarities and dissimilarities in habitat characteristics, should help identify areas worthy of
investigating for new Cerulean Warbler populations.
While abundances did not differ at “used” and “random” plots among any nest
predators, Red-bellied Woodpecker (Melanerpes carolinus L.), a commonly overlooked
threat to songbird nests (Hazler et al. 2004), had the strongest correlation with Cerulean
Warbler of any other predatory species in the CCA biplot. Brown-headed Cowbirds have
shown varying effects on Cerulean Warbler nesting success with very little impact in Ontario
(Oliarnyk and Robertson 1996, Barg et al. 2006b) but are a more common parasite in the
Mississippi Alluvial Valley and perhaps Michigan (Hamel 2000a, Rogers 2006). The low
number of Brown-headed Cowbirds encountered during this study suggests that they were
not a threat to the breeding success of these D. cerulea populations from 2005-2006. The
role these potentially threatening species play as limiting factors in the reproductive potential
of Cerulean Warblers in northern Alabama requires further investigation.
Tree Use – Most encounters during this study were with male Cerulean Warblers, and
the confirmation of its reliance on the upper canopy of co-dominant trees was not unexpected
based on previous research (Robbins et al. 1992). However, both males and females were
observed, albeit infrequently, visiting lower heights while foraging for young, bathing along
stream banks, gathering nesting materials or during courtship sequences.
The result that requires further investigation was the Cerulean Warbler’s strong
preference for Black Walnut (J. nigra), followed by hickory (Carya spp.), Box Elder (Acer
negundo L.), Eastern Sycamore (Platanus occidentalis L.), and Tulip Poplar (Liriodendron
tulipifera L.). Recent examinations of tree selection by D. cerulea throughout its range have
45
found similar tendencies.
Cerulean Warblers residing in Ontario, Illinois, and Indiana
gravitated towards hickories and walnuts, but avoided American Beech (Fagus grandifolia
Ehrhart) and Red Maple (Acer rubrum L.) (Gabbe et al. 2002, Barg et al. 2006a, Jones and
Islam 2006). In Arkansas, Hamel et al. (2005b) provided evidence for the importance of
American Elm (Ulmus Americana L.) to Cerulean Warblers through stand manipulation. In
the Mississippi Alluvial Valley, Hamel (2005) also observed that while Ceruleans did not
prefer J. nigra, they were attracted to shade intolerant species, especially Box Elder,
Hackberry (Celtis laevigata Wild.) and Eastern Sycamore.
Several hypotheses can be postulated for why Cerulean Warblers were observed most
often in J. nigra during this study.
Firstly, Black Walnut is characteristically akin to
hickories in that it has delayed bud break and a reduced crown density in comparison to other
hardwood species. A decrease in foliage also reduces acoustical interference, which allows
Cerulean Warbler males to broadcast their song and detect territorial neighbors more
efficiently (Barg et al. 2006a).
Secondly, Cerulean Warblers have been described as
selecting habitats with little or no understory (Hamel 2000a, 2000b). Black Walnuts have
been described as allelopathic (Walker 1990, Petrides 1998), which may create a more
desirable, less crowded understory. Thirdly, a Cerulean’s motivation for tree selection may
not be one of species but of size. This however contradicts the findings of this study, as five
species (L. tulipifera, P. occidentalis, C.ovata, Carya spp., and Q. alba) were on average
larger than J. nigra. Conversely, these species were also some of the most commonly
chosen, which supports the theory that Cerulean Warblers consistently use the largest trees of
many species (Oliarnyk and Robertson 1996, Jones and Robertson 2001, Hamel 2005b).
46
Lastly, the birds were easier to locate in the open canopy of Black Walnuts that were on
average shorter than the other tree species used.
Nesting and Reproductive Success
As mentioned previously, behavioral clues were used to estimate breeding success
due to the difficulty of locating nests that are often hidden in dense foliage at extreme
heights. The “whisper song” auditory clue was used to confirm the presence of a female on
seven occasions. All instances of adult males carrying food were late enough in the breeding
season to avoid confusion with courtship feedings or deliveries to incubating females (Barg
et al. 2006b). Even though nests are difficult to find, young fledglings will often become
excited and loud when food is being delivered (Oliarnyk and Robertson 1996, Rogers 2006,
J. Carpenter pers. obs.).
The total number of rankings equating to fledgling presence
accounted for only a small percentage (10.4%) of all behavioral observations over the course
of the study. This causes concern because if fledglings are present, encountering their
obnoxious begging calls should have been frequent enough to locate them as evidence of
reproductive success.
On the other hand, Oliarnyk and Robertson (1996) described a
situation whereby an adult male used an alarm call to quiet his fledglings, which did not
move again until the parent resumed singing. This may help explain why some juveniles
went unnoticed.
Reproductive success for all three Cerulean Warbler populations was estimated to be
low from 2005-2006, suggesting that these may be population sinks, whereby annual
mortality exceeds natality (Pulliam 1988). Population sinks can be advantageous by serving
47
as distinct subpopulations, increasing genetic diversity and providing a reserve for the larger,
source metapopulation (Howe et al. 1991).
Sinks can also mislead natural resources
managers into protecting sink habitat, which may be inferior to the true requirements of a
species (Howe et al. 1991, Van Horne 1983). At the current estimated rate, the three
Cerulean Warbler populations of northern Alabama will be unable to sustain themselves over
a long period of time without constant recruitment from a nearby source (Donovan et al.
1995).
Food Provisioning - The number of deliveries made by the male parent at the
Bankhead NF nest were well above the average of 1.1 (± 0.1, Range = 0-4) per 30-minutes
reported by Barg et al. (2006b). Alternatively, nests monitored by Allen and Islam (2004)
had females making more trips every hour (mean = 4.0 ± 2.0). Food provisioning often
increases near the end of a nesting cycle (Allen and Islam 2004). Both juveniles fledged over
the course of the two survey periods, which may explain why the male became increasingly
indefatigable. It is also plausible that a third juvenile fledged before the nest was discovered
and was being cared for by the mother, thus explaining her lack of attention to the nestlings.
Mist-netting and Radio-telemetry
The increase in captures over the course of this study was due to amplified netting
efforts in 2006. The use of a stacked net design also appeared to improve capture success,
especially for those males who were more apprehensive about moving down to the lower
canopy to confront the spurious intruder. More important was the presence of a single
suppressed tree near the net, which was often used as a perch by the male to inspect and
48
strike at the decoy. During the second field season, the decoy was mounted on a spring with
a long black cord attached to its tail to simulate movement when pulled. On two occasions,
males were captured 25 and 30 minutes after they initially arrived. The “attentiveness” of the
spring loaded model may have enticed these males to strike, whereas a stationary model
would appear less threatening in a similar situation.
Harness Design - The harness design used to attach radio transmitters failed for a
number of reasons. Firstly, the loops of at least two broke because they had been cut too thin
(<0.5 mm), which was done to ensure that they would eventually fall off. Secondly, it took
an average 60 minutes to build the initial harnesses that were made in the field post-capture,
and several individuals appearing stressed were released before the glue had completely set.
Lastly, the loop sizes were too big for birds that were slightly smaller than the average size
estimated using the first captured male.
This design did not hamper the movement of any birds during preliminary tests, and
reproductive success was evident in at least one of two Cerulean territories whose males were
tracked. Furthermore, the harness will eventually expand from degradation and fall off;
recovered harnesses with the greatest longevity (14-21 days and 29 days) were both larger
than when originally built. This design may be more practical for tracking larger passerines
that can be handled for longer periods of time and are not of conservation concern.
Age Demographics - In Jackson County, second-year old males (SY) outnumbered
older males eight to six. This supports the hypothesis that northern Cerulean populations are
comprised of more ASY than southern their southern counterparts (Jones et al. 2006).
Second-year males of similar warbler species are often forced into less desirable habitat by
49
older, socially dominant males (Sherry and Holmes 1995, Rogers 2006).
Based on a
hypothetical population model, yearlings (SY) should only account for 30-50% of all
breeding males (Sherry and Holmes 1992). This bias in age may create another situation of
misidentifying less favorable habitat as “ideal”.
Site Fidelity - Cerulean Warblers at Walls of Jericho demonstrated site fidelity, which
has been reported elsewhere (Hamel 2000a). The third male captured in 2005 at Walls of
Jericho was never encountered in 2006. Future surveys and mist-netting will help confirm
site faithfulness and recruitment rates of D. cerulea in northern Alabama.
Home Ranges and Core Use Areas – No literature is currently available for
comparison of the radio-telemetry analysis conducted during this study. There was very little
difference between mean sizes of daily, observed territory size (0.15 ha ± 0.02) and home
range core use areas delineated using radio-telemetry (0.18 ha ± 0.02). The average observed
territory size from this study was much smaller than that of 0.7 ha (± 0.16) reported in
Ontario by Barg et al. (2005), where observed Cerulean locations were marked once every
minute during a 30-minute “burst” sampling session.
The sampling protocol used here was
much less intense than that implemented by Barg et al. (2005) and is the most probable cause
for the difference. The average home range core use area in this study was at least twice as
large as the territory core use areas of 0.07 ha (± 0.16) and 0.05 ha cited by Barg et al. (2005)
and Perkins (2006), respectively. This was expected due to the advantages of radio tracking
individuals, which allows a researcher to cover a larger area and locate a bird regardless of its
singing frequency or visibility.
50
The second male tracked had almost three times as many locations and twice the
home range area as that of the first male. An appropriate alternative for the latter male would
have been using a kernel density estimator with a smoothing parameter selected through
likelihood cross-validation. This method has been proven to be more robust than least
squares cross validation for sample sizes ≤50 (Horne and Garton 2006).
The results of the radio-telemetry analysis presented here provide insight into the
spatial requisites of individual Cerulean Warblers. These estimates, when used collectively
and in conjunction with microhabitat and landscape analyses, will further clarify the habitat
and resource requirements of Cerulean Warbler populations.
Morphological Measurements - All body measurements of captured Cerulean
Warblers, including bill depth (3.34 mm ± 0.07, n = 14) and bill width (3.63 mm ± 0.06, n =
14), were within the ranges reported by Hamel (2000b). Tail length was the only exception
and was 1.8 mm shorter than the average 42.4 mm (Hamel 2000b); different methodology
may be the source of this deviation. Jones et al. (2005) examined the Cerulean Warbler’s
adherence to Bergmann’s rule, which states that animals at higher latitudes tend to be larger
than their southern counterparts, and found that differences in thermodynamics and resource
seasonality account for variation in body size of D. cerulea throughout its range.
Measurements from their study were not presented for comparisons.
Microhabitat Characteristics
Many of the results presented here agree with the general assumptions regarding a
Cerulean Warbler’s selection of microhabitat characteristics (Lynch 1981, Robbins et al.
51
1992, Jones and Robertson 2001, Hamel 2005b). The most obvious was the selection of
habitats containing fewer but larger diameter deciduous trees with tall middle to upper
canopy heights and a sparse understory.
Canopy cover was higher in “used” sites in this study and others (Jones and
Robertson 2001), whereas “random” sites in a Tennessee experiment had consistently denser
cover (Nicholson 2003). A multi-layered canopy has been cited as an important component
in Cerulean Warbler habitat (Oliarnyk and Robertson 1996, Jones and Robertson 2001,
Wood et al. 2005a, Buehler et al. 2006b). Canopy structure was significantly more diverse in
“random” plots, but the average evenness (J’) at occupied sites was still moderately high
(0.71 ± 0.01) indicating that some complexity is present.
Understory abundance per hectare significantly differed between “used” and
“random” locations and is consistent with the belief that less cover is more preferred
(Oliarnyk and Robertson 1996, Jones and Robertson 2001, Bosworth 2003, Wood et al.
2000a). Among the Cerulean populations, the bottomland forest along Hurricane Creek was
historically used for cattle grazing, and Larkin Fork appears much more susceptible to
flooding than at Bankhead NF, where long stretches of Borden and Flannigan Creeks are
defined by sharp, steep banks. Prolonged exposure to heavy trampling and flood waters may
restrain seedling and shrub growth long enough to create a more uniform and open
understory at the Jackson County sites.
In West Virginia, snag and Cerulean Warbler abundance were positively related
(Weakland and Wood 2002, Wood et al. 2005a). For this study, no significant differences
52
were found among snag variables between plot types, but there were on average fewer but
larger snags present in occupied sites than at “random” locations.
The average size of the largest canopy gap within 50 m of plot center was
significantly greater among the Jackson County populations than at Bankhead NF. In many
instances, Ceruleans at Larkin Fork were found in close proximity to the broken canopy
created by AL State Highway 65.
Furthermore, many of the gaps documented were
maintained hunting meadows at Walls of Jericho and fields near Larkin Fork. In Jackson
County, the mean distance of 473 Cerulean Warbler GPS locations to these larger types of
openings was 151.3 m (± 6.2, Range = 0.0-646.2) that were an average 1.9 ha (± 0.1, Range
= 0.1-9.9).
Landscape Associations
Cerulean Warblers occupied areas dominated by deciduous-mixed forest close to
streams and far from developed areas, evergreen forests, grasslands, and open bodies of
water. As compared to areas where they were not found, Cerulean Warbler habitat was also
characterized by larger total core area index (TCAI) and edge density (ED) values. Total
core area index represents the amount of core area within a region, and its interpretation can
be difficult without considering the presence of other variables.
For instance, a TCAI
approaching 100 indicates that a landscape contains a greater density of similar patches
farther away from other land cover types. Depending on the dominant land cover, this value
will assume different meanings.
Because occupied habitat was surrounded by a high
percentage of deciduous-mixed forest with a low density of edge and high TCAI, these
53
measures are evidence that a degree of contiguity in deciduous-mixed forest cover is required
by the Cerulean Warbler in Alabama.
“Used” plots also had similar mean patch fractal dimension scores, which when
above one (all three populations were ≥1.09), suggests an increase in patch shape complexity.
According to McGarigal and Banks (1995), forest interior species may be sensitive to patch
shape because the more complex a shape is, the larger the edge-to-interior ratio.
No Cerulean Warblers were ever encountered above 300 m, and differences in
elevation were detected among plot types and Cerulean populations. Though most birds
encountered were using floodplain habitat and lower portions of adjacent slopes, the presence
of upland deciduous forests and the surrounding topography may still be influential as all
three populations were found in highly dissected areas. Historically, both bottomland and
upland forests have been cited as Cerulean Warbler habitat, and today the species still occurs
in both situations throughout its range (Hamel 2000a).
The population at Walls of Jericho occurred in less fragmented stands based on its
low edge density, total core area index, and mean core area values; however, this site does
contain features that disrupt the continuity in deciduous forest cover, i.e. the hunting fields
and wetland along the floodplain of Hurricane Creek. Bankhead NF Ceruleans were found in
areas with a greater density of streams and a higher percentage of evergreen forest, the later
of which was most likely the reason for its higher edge density and smaller mean core area.
In 2006, the Larkin Fork population had some of the highest IRA scores even though they
bred in an area composed of more agriculture, shrubland, and grassland and were also found
closer to and surrounded by the greatest density of roads. Although much of Highway 65
54
near the Larkin Fork population is subjected to only light traffic and contains a fully closed to
partially open canopy, its presence is still an indication of Cerulean Warblers’ tolerance to
some human activity and suggests that they may even benefit from canopy gaps created by
such disturbances.
The role these associations play with distribution, abundance, and
reproductive success of this species should be considered when addressing forest
management strategies in Alabama.
Cerulean Warblers have responded unpredictably to both natural and intentional
large-scale alterations of its breeding habitat. Jones et al. (2001) witnessed an increase in
reproductive output two years following a devastating ice storm that significantly reduced the
canopy structure at their Ontario study site. In Pennsylvania, Rodewald (2004) found that
Ceruleans were more likely to use areas in close proximity to non-targeted harvesting
practices, and males in Arkansas responded positively to a prescription specifically designed
for D. cerulea (Hamel et al. 2005).
Around 1999, two clearcuts approximately 4.5 ha each were established in the
floodplain of Larkin Fork. It is unclear what effect this action initially had on the Cerulean
population, but today they are consistently using areas immediately next to the regenerating
forest. According to a study in West Virginia (Wood et al. 2005b), abundance of Cerulean
Warblers in unharvested control stands was not affected by neighboring small, forest-interior
clearcuts. Beginning in 1999, a series of Southern pine beetle (Dendroctonus frontalis
Zimm.) outbreaks swept through Bankhead NF and over a four year period altered much of
its landscape, including a large portion of the Sipsey Wilderness Area. Some areas near
55
Cerulean Warbler territories were heavily damaged, but again, the effects of this event on
habitat use and nesting success were not documented.
Habitat Modeling
Both modeling approaches produced similar results, but direct comparisons were
limited by differences in scale units. Surprisingly, even though there was no significant
difference of road density between “used” and “random” plots, the best AIC model indicated
that Cerulean Warbler occurrence was positively related to this feature. Collinearity was
evident with total road length and distance to nearest road (r = -0.8) and percent developed
land (r = 0.7), which may have been considerable enough to affect the interpretation of the
regression coefficients (Hair et al. 1998).
A drawback to the Mahalanobis statistic is that an infinite number of distances are
possible, thus requiring the designation of a cutoff value to separate “ideal” habitat from less
favorable ones (Browning et al. 2005, Buehler et al. 2006a). However, the goal of this study
was to not only identify areas where immediate research and conservation efforts should be
focused, but to also provide future researchers with an opportunity to investigate additional,
potential sites. For those reasons, values were classified in increments of ten up to 100, and
all values greater than 100 were considered too “far” from habitat currently occupied by
Cerulean Warblers in Jackson and Lawrence Counties.
Weins et al. (1985) stated that most landscape processes are influenced heavily by
edaphic factors, and the inclusion of a soil type layer in the model may prove to be
beneficial. Additionally, stand width has been shown to affect breeding bird communities in
56
bottomland forests (Kilgo et al. 1998) and should be addressed for the floodplain habitat of
Cerulean Warblers in northern Alabama.
Ultimately, there may be more suitable habitat available, at least at the landscape
level, than there are Cerulean Warblers to colonize the surplus of areas predicted by the
models. Nonetheless, both maps will be useful for management strategies and may assist
future studies that wish to document changes in landscape composition and configuration.
57
CHAPTER 5
CONCLUSIONS
The following is a brief summary of the results from this study and is intended to
highlight the most pertinent findings. For more detailed information regarding each topic,
refer to the “Table of Contents” for page numbers of chapters and their corresponding
sections.
Distribution and Relative Abundance:

There are currently three breeding Cerulean Warbler populations in Alabama: one
in Bankhead National Forest in Lawrence County, and two in northwest Jackson
County along Larkin Fork on private property and along Hurricane Creek in Walls
of Jericho/Skyline Wildlife Management Area.

Nearest neighbor (NN) analysis indicated that all three populations demonstrated
colonial distributions with concentrations occurring near the Sipsey Wilderness
Area along Borden and Flannigan Creeks in Bankhead National Forest, and along
the floodplains of Larkin Fork and Hurricane Creek near the Tennessee state border.
58

Assuming each male was mated, the estimated annual total population during in
Alabama in 2005 and 2006 was approximately 45-50 pairs.
Avian Associations and Habitat Use:

Cerulean Warblers bred in areas characterized by a higher abundance and diversity
of avian species than in areas where they did not occur.

They associated most often with sympatric inhabitants of deciduous bottomland
forests.

Brown-head Cowbirds (M. alter) were rarely detected in areas occupied by
Cerulean Warblers suggesting that nest parasitism was of little concern for these
populations in 2005-2006.

Cerulean Warblers used an average tree height of 25.7 m with a mean DBH of 37.9
cm.

They preferred the outside, upper canopy of co-dominant trees and were observed
most often in Black Walnut (J. nigra).
Nesting and Reproductive Success

Nesting success was low for all three populations based on an index of reproductive
activity (IRA) developed from behavioral observations.

Based on the estimates of this study, all three populations may be population sinks.

A total of four nests were discovered from 2004-2006: two at Bankhead NF and
two at Walls of Jericho.
59

For a single nest monitored at Bankhead NF, the male parent provided food almost
four times every 30 minutes and accounted for greater than 75% of deliveries.
Mist-netting and Radio-telemetry

Fourteen males were captured and banded during the study: eleven at Walls of
Jericho and three at Larkin Fork.

The Jackson County populations were composed of younger males, which
outnumbered older males eight to six.

At Walls of Jericho, two of three males banded in 2005 returned to the same
breeding site in 2006.

The average kernel home range for two males radio-tracked at Walls of Jericho was
5.62 ha with mean core use area of 0.18 ha. The average observed territory size for
Cerulean Warbler males was 0.15 ha.
Microhabitat Characteristics

As compared to areas where they were not detected, Cerulean Warblers occurred in
habitat characterized by:
- Fewer but larger diameter trees,
- Higher percentage of deciduous basal area,
- Taller middle and upper canopy heights,
- Greater percentage of canopy cover,
- Downed logs further from plot center,
60
- Shorter lower canopy height,
- Less dense understory,
- Less, but still moderately complex canopy structure.
Landscape Associations and Habitat Modeling

As compared to areas where they were not detected, Cerulean Warblers occurred in
a landscape characterized by:
- Lower elevations,
- Further from roads but closer to streams,
- Higher density of streams,
- Lower percentages of open bodies of water, developed/impervious surfaces,
grassland, shrubland, and evergreen forest,
- Greater percentage of deciduous-mixed forest,
- Less edge,
- Greater abundance of core area with larger patches of core area,
- More complex-shaped patches.

Binary logistic regression and Mahalanobis distance (D2) models produced similar
results, although direct comparisons are limited because of differences in scale.

Ultimately, there may be more habitat available in northern Alabama at the
landscape level than there are Cerulean Warblers to occupy it.
61
CHAPTER 6
RECOMMENDATIONS
These recommendations are provided to assist in the design and implementation of
future research projects and conservation efforts targeted at the Cerulean Warbler (Dendroica
cerulea) in northern Alabama. In addition to the information presented throughout this
document, all available research related to this species should be thoroughly reviewed and
discussed before initiating any large-scale, long-term management plans.
1) Continue monitoring of all three populations with increased searches in and
surrounding the Sipsey Wilderness of Bankhead National Forest and into
southeastern Tennessee, north of Walls of Jericho and Larkin Fork.
2) Concentrate field research efforts on nest searching and radio-telemetry.
Effective management and conservation strategies will be limited until the status
of the reproductive potential of these populations becomes more apparent.
3) Focus additional searches in areas identified by habitat models while eliminating
searches in “random” habitat.
4) Incorporate distance sampling techniques with increased point count effort for
further assessment of the avian community in occupied Cerulean habitat.
62
5) Perform microhabitat assessments in areas with the highest probability of
use/lowest Mahalanobis distances identified by the habitat models. Combine
landscape and microhabitat data into future predictive models using extrapolation
methods such as kriging or inverse distance weighting.
6) Landscape analyses should only be carried out using an updated land use/land
cover dataset, i.e. supervised classification of current, remotely sensed data.
7) Substitute nearest neighbor (NN) analysis with Ripley’s K or neighborhood
density function (NDF) for tests of spatial patterns among territories.
8) Initiate and maintain contact with the Cerulean Warbler Technical Group,
Alabama Department of Conservation and Natural Resources, and Bankhead
National Forest.
63
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FIG. 1. Locations of historic and recent Cerulean Warbler encounters in Alabama. Recent
sightings (1977-2006) represent where at least one male was observed during the breeding
season. All sightings prior to 1977 were taken from Imhof (1976); refer to this text for
explanation of survey methods and densities.
Lauderdale
X!
X
Madison
#
Limestone
XX Colbert
"
Lawrence
Franklin
"
Cherokee
Cullman
#
Etowah
Blount
X
Walker
Calhoun
Fayette
XXXX
Jefferson
!XXXX
X
X
TuscaloosaX
Shelby
Pickens
De Kalb
#
X
"
Lamar
"
Marshall
Winston
Marion
Jackson
X
Morgan
!
X^X
!
¹
^^"
St. Clair
Cleburne
Talladega
#
#"Clay
Randolph
Bibb
Coosa
Greene
Tallapoosa
Chilton
Chambers
Hale
#
Sumter
Perry
Lee
Elmore
Autauga
#
Macon
Dallas
Russell
Marengo
Montgomery
Lowndes
Choctaw
Bullock
Wilcox
Barbour
Pike
Butler
Clarke
Crenshaw
Monroe
Henry
Conecuh
Washington
Coffee
Dale
Covington
Houston
Escambia
0
15
Geneva
30
60
90
120
Kilometers
Mobile
Baldwin
Alabama Fall Line
#
Sightings prior to 1930
X
June sightings (1930-1976)
!
Confirmed breedings (1930-1976)
" June sightings (1977-2006)
^
Confirmed breedings (1977-2006)
78
FIG. 2. Locations of Cerulean Warbler study sites in northern Alabama, 2005-2006.
!
O
Lauderdale
Limestone
Jackson
Madison
Colbert
Lawrence
Morgan
Franklin
De Kalb
Marshall
Marion
Cherokee
Winston
Cullman
Etowah
Blount
0
40
80
160
240
!
O
320
Kilometers
Larkin Fork
Walls of Jericho
Sipsey Wilderness
Bankhead National Forest
Alabama Fall Line
¹
79
FIG. 3. Distribution of “used” habitat plots, nest sites, and points counts from Walls of
Jericho, Jackson County, Alabama, 2005-2006
#
!
(
#
!
(
#
!
(
ica
Hu
rr
#
ne
Cr
eek
#
!
(#
#
!
(
(
#!
# !
(
#
!
( #
#
!
(!
(
## #
!
(
#
#
!
(
!
(
(#
!
#
!
(
#
!
(
#
!
( !
#
(
(
#
#
(
!
( !
(
#
!!
!
(
(!
#
!
(
#
#
#
#
!
(
##
!
(
#
_
^
_
^
#
#
!
(
#
0
350
700
1,400
2,100
2,800
Meters
_ Nest site (2)
^
#
¹
"Used" habitat (36)
( "Available" habitat (2)
!
!
( Point Counts (26)
Paint Rock River
80
Hurricane Creek
WJ/Skyline WMA
Open Water
Developed
Barren Rock
Evergreen Forest
Deciduous/Mixed
Shrubland
Grassland
Agriculture
Wetland
FIG. 4. Distribution of “used” habitat plots and point counts along Larkin Fork, Jackson
County, Alabama, 2005-2006
#
*
!
(!
(
#
*
!
(
#
*
!
(
#
*
*
!
( #
!
(#
*#
*
*
* #
!
(#
!
(
(#
*
#
*!
!
(
#
*
!
(
rk
La
For k
in
#
*
#
*
!
(
!
(
#
*
!
(
#
#
*
*
!
(
#
*
!
(*
(
#
*
!
(!
!
(#
*#
*
!
(
#
* #
#
*
(#
#
*
!
(!
#
*
!
(
*
#
*
!
(!
#
*
(
0
275
550
1,100
1,650
2,200
Meters
#
* "Used" habitat (30)
! Point Counts (26)
(
¹
Larkin Fork
Open Water
Paint Rock River
Developed
Barren Rock
Evergreen Forest
Deciduous/Mixed
Shrubland
Grassland
Agriculture
Wetland
81
FIG. 5. Distribution of “used” habitat plots and point counts in Bankhead National Forest,
Lawrence County, Alabama, 2005-2006.
!
(
Bor
den
#!
(
!
( #
!
(
#
!
(
n
Fla
in
nag
#
#
!
(
_
^
##
#^
_
!
(
#
!
(
#
#
!
(
#
!
(
!
(#!
(
#
!
(
#
#
!
(
#
!
(
0
365
730
1,460
2,190
2,920
Meters
_ Nest (2)
^
¹
#
!
(
82
"Used" habitat (17)
Point counts (14)
Creeks
Sipsey Wilderness
Water
Developed
Bare
Evergreen
Deciduous
Shrubland
Grassland
Agriculture
Wetland
FIG. 6. Locations of “random” points sampled for habitat, landscape, and avian associations
in northeast Alabama, 2005-2006.
# #
#
####
#
###
#
Y
X
!
(!
(
!
(
Madison
"
Jackson^
_
_
^
$
+
_
^
De Kalb
G
G
G
Marshall
Cherokee
0
¹
55
110
220
330
440
Kilometers
Y Tom Smith's place (1)
X
"
Keel Mtn Preserve (1)
_
^
Guntersville State Park (3)
RB Whitaker Preserve (1)
$
+
G Little River Canyon NP (3)
!
(
Sharp-Bingham Mtn Preserve (3)
# Walls of Jericho/Skyline WMA (12)
Guntersville State Park
Little River Canyon National Park
Walls of Jericho/Skyline WMA
83
FIG. 7. Locations of “random” points sampled for habitat, landscape, and avian associations
in northwest Alabama, 2005-2006.
Colbert
"
Lawrence
Franklin
*
#
*
##
#
*
*#
##
#
* *
*#
#
*#
*
*#
**#
#
*
#
*
*
#
*
#
*#
*
#
*
#
*
#
*#
*
Winston
Marion
!
Walker
Lamar
Fayette
0
¹
5
10
20
30
40
Kilometers
"
Rock Creek (1)
!
#
*
Boxes Creek (1)
Bankhead National Forest (25)
Sipsey Wilderness
Bankead National Forest
84
FIG. 8. Triangular (A) and stacked (B) mist-net designs used to capture Cerulean Warbler
males.
(A)
12 m
6m
Decoy
&
Speakers
6m
(B)
12 m
3m
Tension
anchors
Decoy
1.5 – 3 m
Speakers
85
FIG. 9. Territory centroids used for nearest neighbor (NN) analysis at Bankhead NF (A), Larkin Fork (B), and Walls of Jericho
(C), Alabama, 2006. Nearest neighbor indices ≥1.0 suggest a random distribution, values <1.0 exhibit clumping. Note
differences in scale.
(A)
(C)
(B)
!
(
!
(
!
(
!
( !
(
!
(!
(
!
(!
(
!
(
!
(
!
(
!
(
(
!
(!
!
(
!
(
!
(!
(
(
(!
!
(!
!
(
!
(!
(
!
(
!
(!
(
!
(
!
(
!
(
!
(
(
!
(! !
(
86
!
(
!
(
!
(
!
( !
(
!
(
!
(!
(
!
(
!
(
!
(
!
(
!
(
!
(
!
(
NN index = 0.78
P (Z = -1.66) < 0.04
0
420 840
1,680
2,520
3,360
Meters
¹
0
86
195 390
!
(
NN index = 0.78
P (Z = -1.69) < 0.05
780
1,170
1,560
Meters
¹
0
340 680
NN index = 0.67
P (Z = -2.79) < 0.001
1,360
2,040
2,720
Meters
¹
FIG. 10. Means (± SE) of bird species abundance and richness detected at “used” and
“random” point count stations (n = 103) in northern Alabama, 2005-2006.
14
Number of birds detected
Used
Random
12
10
8
6
4
2
0
Abundance
Richness
87
Axis 2
FIG. 11. Scatter biplot (Axes 1 & 2) of canonical correspondence analysis for “used” and “random” point counts (n = 103)
conducted during the 2005-2006 breeding seasons throughout northern Alabama. See Appendix B for microhabitat
descriptions and Appendices F and G for bird species codes.
BGGN
YTVI UPHT
RBWO
KEWA LOWA
WEWA
ASPECT WBNU
NOPA
HOWA
DOWO
GCFL
ACFL
DECBA
88
CERW
TRDBH
ETTI
REVI
WOTH
CACH
CARW
INBU AMCR
GBHE
Axis 1
BLJA
SUTA
EAWP
NOCA
YBCU
SCTA
AMRE
NGAPSZ
COYE
PIWA
YBCH
88
DOWO
Axis 3
FIG. 12. Scatter biplot (Axes 1& 3) of canonical correspondence analysis for “used” and “random” point counts (n = 103)
conducted during the 2005-2006 breeding seasons throughout northern Alabama. See Appendix B for microhabitat
descriptions and Appendices F and G for bird species codes.
GCFL
COYE
YTVI ACFL
CARW
89
DECBA
INBU
AMRE
CERW
LOWA
RBWO
YBCH
WBNU
WOTH
EAWP
AMCR
CACH
NOCA
NOPA
BGGN
TRDBH
KEWA
SUTA
ETTI
REVI
BLJA
WEWA
SCTA
Axis 1
HOWA
YBCU
NTREE
PIWA
GBHE
89
Axis 3
FIG. 13. Scatter biplot (Axes 2 & 3) of canonical correspondence analysis for “used” and
“random” point counts (n = 103) conducted during the 2005-2006 breeding seasons
throughout northern Alabama. See Appendix G for microhabitat descriptions and
Appendices F and G for bird species codes.
DOWO
GCFL
COYE
ACFL
NGAPSZ SCTA
YBCH
AMRE
CARW
SUTA
INBU
YTVI
ASPECT
WBNU
UPHT
CERW WOTH
EAWP
AMCR CACH
HOWA
LOWA
NOPA
NOCA
BGGN
RBWO
ETTI REVI
YBCU
BLJA
PIWA
GBHE
90
KEWA
Axis 2
WEWA
FIG. 14. Proportion of stems selected by Cerulean Warblers versus their availability for the
ten most used species in Jackson and Lawrence Counties, Alabama, 2005-2006.
25
Used
Available
Proportion of Stems
20
15
10
5
0
BLWA
HICK
BOXE
SYCA
T UPO
ASH
WOAK
SHAG
ELM
HACK
Tree Species Code
BLWA: Black Walnut (J. nigra.), HICK: Hickory (Carya spp.), BOXE: Box Elder (A. negundo), SYCA: E.
Sycamore (P. occidentalis), TUPO: Tulip Poplar (L. tulipifera), ASH: Ash (Fraxinus spp.), WOAK: White
Oak (Q. alba), SHAG: Shagbark hickory (C. ovata), ELM: Elm (Ulmus spp.), HACK: Hackberry (Celtis spp.)
91
FIG. 15. Means (± SE) of tree diameters (A) and tree heights (B) used by Cerulean Warblers
versus those available in 0.04 ha “used” and nest site habitat plots sampled in Jackson and
Lawrence Counties, Alabama, 2005-2006.
(A)
60
Used
Available
Tree diameter (cm)
50
40
30
20
10
0
SYCA
WOAK
T UPO
SHAG
HICK
BLWA
HACK
ASH
BOXE
ELM
Tree species code
(B)
40
Used
Tree height (m)
35
Available
30
25
20
15
10
5
0
T UPO
SYCA
SHAG
HICK
WOAK
BLWA
ASH
HACK
ELM
BOXE
Tree species code
BLWA: Black Walnut (J. nigra.), HICK: Hickory (Carya spp.), BOXE: Box Elder (A. negundo), SYCA: E. Sycamore (P. occidentalis),
TUPO: Tulip Poplar (L. tulipifera), ASH: Ash (Fraxinus spp.), WOAK: White Oak (Q. alba), SHAG: Shagbark hickory (C. ovata), ELM:
Elm (Ulmus spp.), HACK: Hackberry (Celtis spp.)
92
FIG. 16. Reproductive success of Cerulean Warblers in Jackson and Lawrence Counties,
Alabama, 2005-2006. Breeding success was considered low for territories with maximum
index of reproductive activity (IRA) scoresa of one or two, medium for scores three through
five, and high for scores six through eight. Values above bars represent the number of
territories.
Low
Proportion of territories
0.9
0.8
Medium
14
12
14
High
13
9
0.7
0.6
7
0.5
6
0.4
0.3
0.2
3
3
3
2
2
2
0.1
1
1
1
2
2
0
2005
2006
Walls of Jericho
2005
2006
Larkin Fork
Study Site
a
Maximum IRA scores:
1= presence of singing male,
2= presence of singing male displaying aggressive territorial behavior,
3= presence of singing male using “whisper song”,
4= presence of singing male and female,
5= female observed carrying nesting material,
6= nest located,
7= presence of nestlings or adult observed carrying food,
8= presence of fledglings
93
2005
2006
Bankhead NF
FIG. 17. Mean (± SE) number of food deliveries per 30 mintues recorded during two
surveys of a Cerulean Warbler nest in Bankhead NF, 2006.
Number Deliveries/30 min.
5
n = 31
Male
Female
Unknown
4
3
2
n=3
1
0
Provider
94
n =4
FIG. 18. Radio-telemetry results for two Cerulean Warbler males tracked at Walls of Jericho,
Jackson County, Alabama, 2006.
_
^
_
^
0
55
110
220
330
440
Meters
¹
_
^
Core use area
95% MCP
Home range
"Available" plot
Hurricane Creek
Walls of Jericho
Open Water
Developed
Barren Rock
Evergreen Forest
95
Deciduous/Mixed
Shrubland
Grassland
Agriculture
Wetland
FIG. 19. Means (± SE) of observed territory sizes from Cerulean Warbler populations in
2006 and of home range core use areas delineated using radio-telemetry at Walls of Jericho,
Jackson County, Alabama, 2006.
0.3
Walls of Jericho - Observed territory
Walls of Jericho - Core use area
Bankhead NF - Observed territory
Larkin Fork - Observed territory
n = 24
0.25
Size (ha)
0.2
n =2
n = 10
n = 20
0.15
0.1
0.05
0
Study Site
96
FIG. 20. Transformed aspect scores (Beers et al. 1966) for “used” and “random” habitat plots
(A) and for “used” habitat plots sampled from Cerulean Warbler populations (B) in northern
Alabama, 2005-2006.
(A)
0.40
Used
Random
Proportion of plots
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
-1.0 (Flat)
>0.0 ≤ 0.5 (NE)
>0.5 ≤ 1.5 (SE/NW)
>1.5 ≤ 2.0 (SW)
Aspect
(B)
0.55
Walls of Jericho
0.50
Larkin Fork
Bankhead NF
Proportion of plots
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
-1.0 (Flat)
>0.0 ≤ 0.5 (NE)
>0.5 ≤ 1.5 (SE/NW)
Aspect
97
>1.5 ≤ 2.0 (SW)
FIG. 21. Potential Cerulean Warbler habitat in Jackson County, Alabama identified using binary logistic regression.
98
Probability of use
0 - 0.1
0.11 - 0.2
0.21 - 0.3
0.31 - 0.4
0.41 - 0.5
0.51 - 0.6
0.61 - 0.7
0.71 - 0.8
0.81 - 0.9
0.91 - 1
¹
0
98
3
6
12
18
24
Kilometers
FIG. 22. Potential Cerulean Warbler habitat in Jackson County, Alabama identified using Mahalanobis distance (D2). Smaller
values represent areas more similar to ideal Cerulean Warbler habitat.
99
Mahalanobis distance
0.9 - 10
10.1 - 20
20.1 - 30
30.1 - 40
¹
40.1 - 50
50.1 - 60
60.1 - 70
70.1 - 80
80.1 - 90
90.1 - 100
0
99
3
6
12
18
24
Kilometers
>100.1
FIG. 23. Potential Cerulean Warbler habitat in Lawrence and Winston Counties, Alabama
identified using binary logistic regression.
Probability of use
0 - 0.1
0.11 - 0.2
0.21 - 0.3
0.31 - 0.4
0.41 - 0.5
0.51 - 0.6
0.61 - 0.7
0.71 - 0.8
0.81 - 0.9
0.91 - 1.0
¹
0
2.5
5
10
100
15
20
Kilometers
FIG. 24. Potential Cerulean Warbler habitat in Lawrence and Winston Counties, Alabama
identified using Mahalanobis distance (D2). Smaller values represent areas more similar to
ideal Cerulean Warbler habitat.
Mahalanobis distance
0.6 - 10
10.1 - 20
20.1 - 30
30.1 - 40
40.1 - 50
50.1 - 60
60.1 - 70
70.1 - 80
80.1 - 90
90.1 - 100
>100.1
¹
0
3
6
12
101
18
24
Kilometers
FIG. 25. Means (± SD) of Mahalanobis distances from “used” and nest site (A) and
“random” (B) habitat plots sampled in northern Alabama, 2005-2006. Note differences
in scale.
(A)
30
Mahalanobis Distance
25
20
15
10
5
0
N=
67
19
Jackson
Lawrence
County
(B)
1000
Mahalanobis Distance
900
800
700
600
500
400
300
200
100
0
N=
20
25
Jackson
Lawrence
County
102
FIG. 26. Means (± SD) of probability of use obtained through binary logistic regression
from “used” and nest site (A) and “random” (B) habitat plots sampled in northern
Alabama, 2005-2006. Note differences in scale.
(A)
100
90
Probability of use
80
70
60
50
40
30
20
10
0
N=
67
19
Jackson
Lawrence
County
(B)
100
90
Probability of use
80
70
60
50
40
30
20
10
0
-10
N=
20
25
Jackson
Lawrence
County
103
TABLE 1. Abundance of Cerulean Warblers and maximum index of reproductive
activity (IRA) ranks for territories detected in Jackson and Lawrence Counties, Alabama,
2005-2006.
Total Cerulean Warblersa
Site
Year
♂
♀ Jb
1
2
IRA Rankingc
3
4
5
6
7
8
Walls of
Jericho
2005
2006
18
18
3
3
2
4
10
9
3
5
0
0
2
0
0
0
0
0
0
0
3
4
Larkin Fork
2005
2006
15
15
2
5
1
1
11
2
1
5
1
2
1
3
0
1
0
0
0
1
1
1
Bankhead
NF
2005
2006
13
17
0
3
0
3
7
13
2
1
1
1
0
1
0
0
0
0
3
0
0
1
a
Includes observed individuals only.
Juveniles.
c
Maximum IRA ranking per male/territory, where:
1= presence of singing male,
2= presence of singing male displaying aggressive territorial behavior,
3= presence of singing male using “whisper song”
4= presence of singing male and female,
5= female observed carrying nesting material,
6= nest located,
7= presence of nestlings or adult observed carrying food,
8= presence of fledglings
b
104
TABLE 2. Summary of all mist-net attempts and captured males at Walls of Jericho (WJ) and
Larkin Fork (LF), Jackson County, Alabama, 2005-2006.
Date
Wing
(mm)
Weight
(g)
Tail
(mm)
Agea
FF
Wearb
Capture
Site
Setup
Type
4/30/05
4/30/05
5/16/05
5/16/05
5/29/05
6/2/05
6/2/05
6/2/05
6/2/05
6/19/05
5/15/06
5/15/06
5/15/06
5/15/06
5/16/06
5/16/06
5/16/06
5/17/06
5/20/06
5/20/06
5/20/06
5/20/06
5/21/06
5/21/06
5/23/06
5/23/06
5/24/06
5/24/06
5/29/06
5/29/06
5/29/06
5/29/06
6/6/06
6/6/06
6/6/06
6/13/06
66
65
69
67
66
64
65
66
65
64
64
64
67
61
9.9
10
9.07
9.7
10.15
9.12
9.32
9.22
8.56
9.8
9.37
9.12
44
37
41
36
41
41
43
43
41
40
40
42
42
38
SY
ASY
ASY
ASY
ASY
ASY
SY
SY
SY
ASY
SY
SY
SY
SY
2
2
1
2
1
2
1
0
0
3
4
3
3
WJ
WJ
WJ
WJ
LF
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
LF
LF
LF
LF
LF
LF
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
WJ
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Triangle
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Stacked
Single
65.2
± 0.5
9.4
± 0.1
40.6
± 0.6
.
Mean
± SE
a
SY = Second-year, ASY = After-second-year
Flight feather wear: 0 = none, 1 = slight, 2 = light, 3 = moderate, 4 = heavy, 5 = excessive
b
105
TABLE 3. Comparisons of microhabitat characteristics for Cerulean Warbler study plots sampled in northern Alabama, 20052006. Values are means (± SE) when t-tests were performed and median (interquartile range) for Mann-Whitney U-tests.
Values for “available” habitat and nest sites are provided but were not included in the analysis. Refer to Appendix B for
variable descriptions.
Microhabitat
variable
Plot Type
t-test
Available
(n = 2)
Nest
(n = 4)
BA
NTREE
Used
(n = 83)
Random
(n = 51)
106
18.4 ± 6.6
29.4 ± 4.7
28.3 ± 1.1
25.8 ± 1.1
837.5 (650.0850.0 (606.3825.0 (650.0- 1150.0 (800.01025.0)
1075.0)
1050.0)
1550.0)
RBATR
0.02 (0.01-0.04) 0.03 (0.03-0.04) 0.03 (0.02-0.05) 0.02 (0.01-0.03)
DECBA
100.0 (100.0100.0 (100.0100.0 (100.099.7 (63.5100.0)
100.0)
100.0)
100.0)
SNGBA
0.3 (0.0-0.5)
0.0 (0.0-0.9)
0.8 (0.3-2.0)
1.0 (0.3-2.5)
NSNAG
25.0 (0.00.0 (0.025.0 (25.050.0 (25.050.0)
75.0)
50.0)
100.0)
RBASNG
0.005 (0.000.000 (0.0000.015 (0.0070.018 (0.0100.010)
0.009)
0.035)
0.035)
LOWHT
4.4 ± 0.7
5.8 ± 0.7
5.2 ± 0.2
5.9 ± 0.2
MIDHT
17.1 ± 1.1
17.3 ± 0.3
17.1 ± 0.3
15.5 ± 0.5
UPHT
29.9 ± 4.9
30.6 ± 4.7
29.8 ± 0.7
27.0 ± 0.9
CNPYCVR
90.0 (85.095.0 (87.592.5 (85.085.0 (77.595.0)
98.8)
95.0)
90.0)
CNPYSTR
0.69 ± 0.07
0.65 ± 0.05
0.72 ± 0.01
0.75 ± 0.01
NGAPDIS
20.1 ± 2.6
20.9 ± 9.1
17.0 ± 1.4
16.2 ± 2.0
NGAPSZ
4.0 ± 0.0
1.3 ± 1.0
2.0 ± 0.2
2.1 ± 0.2
LGAPDIS
20.1 ± 2.6
20.9 ± 9.1
20.8 ± 1.6
17.3 ± 2.2
LGAPSZ
4.0 ± 0.0
1.3 ± 1.0
2.4 ± 0.2
2.1 ± 0.2
UNDRSTRY
3125.0
2875.0
3750.0
4875.0
(1000.0(1531.3(2000.0(2625.05250.0)
4593.8)
5625.0)
7500.0)
106
U-test
df
t
P
Z
P
133
133
-1.582
-
0.116
-
-3.757
0.001
133
133
-
-
-3.819
-5.025
0.001
0.001
133
133
-
-
-1.087
-1.592
0.277
0.111
133
-
-
-0.397
0.691
133
129
133
133
-1.968
-3.056
-2.586
-
0.051
0.003
0.011
-
-4.327
0.001
133
107
133
106
133
133
1.728
-0.359
-0.497
-1.319
-1.167
-
0.086
0.720
0.620
0.190
0.245
-
-2.358
0.018
TABLE 3. Continued.
Microhabitat
variable
SLOPE
ASPECT
TRDIS
TRDBH
LOGDIS
LOGDBH
LOGLNG
Plot Type
t-test
Available
(n = 2)
Nest
(n = 4)
Used
(n = 83)
Random
(n = 51)
5.5 ± 5.5
0.4 (-1.0-1.7)
1.7 ± 0.05
19.0 (12.925.2)
8.5 ± 1.1
10.7 ± 6.4
2.9 (0.7-5.1)
10.4 ± 4.8
0.6 (-0.8-1.7)
2.5 ± 0.4
14.9 (10.929.7)
5.0 ± 1.3
26.8 ± 9.7
10.2 (5.3-14.7)
11.2 ± 1.1
0.9 (-1.0-1.7)
3.0 ± 0.1
21.2 (15.927.5)
6.8 ± 0.2
13.3 ± 0.9
5.2 (2.7-7.6)
9.4 ± 1.0
0.8 (-1.0-1.5)
2.7 ± 0.1
10.8 (8.616.6)
6.2 ± 0.2
13.8 ± 1.1
6.4 (4.0-9.3)
107
107
U-test
df
t
P
Z
P
133
133
132
133
-1.065
-1.302
-
0.289
0.195
-
-0.049
-6.017
0.961
0.001
129
133
133
-1.834
0.324
-
0.069
0.746
-
-1.540
0.124
TABLE 4. Comparisons (mean ± SE) of microhabitat characteristics sampled from 0.04 ha “used” habitat plots at
three Cerulean Warbler study sites in northern Alabama, 2005-2006. Uppercase letters indicate where differences
exist using Tukey tests; lowercase letters indicate where differences exist using an adjusted Bonferroni correction.
Refer to Appendix B for variable descriptions.
Microhabitat
Variable
108
BA
NTREE§
RBATR§
DECBA
SNGBA
NSNAG
RBASNG
LOWHT
MIDHT
UPHT
CNPYCVR
CNPYSTR
NGAPDIS§
NGAPSZ
LGAPDIS§
LGAPSZ
UNDRSTRY§
SLOPE
ASPCT
Study Site
ANOVA
Kruskal-Wallis
Walls of Jericho
(n = 36)
Larkin Fork
(n = 30)
Bankhead NF
(n = 17)
df
F
P
H
P
26.2 ± 1.8
746.8 ± 0.8A
0.034 ± 0.000
98.3 ± 1.0
2.2 ± 0.6
46.1 ± 7.3
0.04 ± 0.01
6.0 ± 0.4
18.0 ± 0.4A
29.4 ± 0.9A
88.3 ± 1.9
0.71 ± 0.02
14.0 ± 0.1
2.3 ± 0.3ab
17.4 ± 0.1
2.6 ± 0.3a
3019.3 ± 20.8A
9.6 ± 1.7
0.3 ± 0.2a
29.1 ± 1.6
855.0 ± 0.9AB
0.034 ± 0.000
99.5 ± 0.4
1.0 ± 0.2
42.5 ± 5.6
0.01 ± 0.00
5.9 ± 0.3
16.8 ± 0.5AB
27.7 ± 0.8A
91.0 ± 1.4
0.73 ± 0.02
14.8 ± 0.1
2.4 ± 0.3a
17.8 ± 0.1
2.7 ± 0.3a
3118.9 ± 13.7A
14.7 ± 2.2
0.5 ± 0.2ab
31.3 ± 1.7
970.9 ± 1.0B
0.032 ± 0.000
96.4 ± 2.1
1.0 ± 0.3
25.0 ± 4.7
0.03 ± 0.01
5.5 ± 0.3
15.9 ± 0.6B
34.3 ± 1.7B
90.8 ± 1.3
0.72 ± 0.02
17.4 ± 0.1
1.2 ± 0.2b
22.0 ± 0.2
1.4 ± 0.2b
5532 ± 19.1B
8.8 ± 1.3
1.0 ± 0.2b
82
82
82
82
82
82
82
82
80
82
82
82
68
82
67
82
82
82
82
1.80
3.51
0.11
0.43
3.74
8.04
0.22
4.53
-
0.172
0.035
0.894
0.655
0.028
0.001
0.801
-
4.46
1.19
2.19
1.30
1.62
0.56
4.84
1.00
7.55
3.99
8.40
0.107
0.552
0.334
0.522
0.446
0.755
0.089
0.606
0.023
0.136
0.015
§
back transformed from sqrt(x)
108
0.014
-
TABLE 4. Continued.
Microhabitat
variable
TRDIS§
TRDBH†
LOGDIS
LOGDBH§
LOGLNG§
§
†
Study Site
Walls of Jericho
(n = 36)
3.268 ± 0.003A
21.1 ± 0.1
6.5 ± 0.4
9.6 ± 0.1A
3.80 ± 0.03A
Larkin Fork
(n = 30)
2.531 ± 0.003B
21.7 ± 0.1
6.9 ± 0.4
10.9 ± 0.0A
4.57 ± 0.02A
back transformed from sqrt(x)
back transformed from log10(x+1)
109
109
ANOVA
Bankhead NF
(n = 17)
2.752 ± 0.003AB
17.3 ± 0.1
7.3 ± 0.5
18.0 ± 0.1B
7.60 ± 0.03B
Kruskal-Wallis
df
F
p
H
p
82
82
78
82
82
3.80
2.26
0.82
4.88
5.28
0.027
0.111
0.442
0.010
0.007
-
-
TABLE 5. Summary of Cerulean Warbler nests discovered in northern Alabama, 2004-2006.
Location
No.
fledglings
Nest tree
species
Nest
height
(m)
Nest
height/tree
height
Nest
tree
DBH
(cm)
Dist.
to
bole
(m)
Nest
dist.
to gapa
(m)
Dist. to
branch
end (m)
?
2
Acer negundo
Fraxinus spp.
13.5
18.5
0.69
0.78
43.4
76.1
1.8
12.8
none
1.5
2.2
1.5
5/11/04 Abandoned 0
5/14/04 Depredated 0
Quercus alba
Carya spp.
13.3
12.5
0.56
0.74
19.4
13.2
1.1
30.0
none
2.1
Mean
± SE
14.5
± 1.4
0.69
± 0.04
38.0
± 14.3
5.2
± 3.8
15.8
± 14.2
1.9
± 0.2
Date
found
Nest Fate
Bankhead 5/6/04 Unknown
NF
6/15/06 Successful
Walls of
Jericho
110
110
TABLE 6. Comparisons of landscape characteristics for Cerulean Warbler study plots sampled in northern Alabama, 20052006. Values are means (± SE) when t-tests were performed and median (interquartile range) for Mann-Whitney U-tests.
Values for “available” habitat and nest sites are provided but were not included in the analysis. Refer to Appendix D for
variable descriptions.
Landscape
habitat
variable
ELEV
ROAD
STRM
TRL
111
TSL
WATER
DVLPD
DECMX
EVER
SHRB
GRASS
AGRI
ED
TCAI
MCA
MPFD
Plot Type
t-test
Available
(n = 2)
Nest
(n = 4)
219.0 ± 2.9
1396.6 (1375.41417.8)
59.8 (52.267.3)
0.0 (0.0-0.0)
199.0 ± 6.8
965.4 (873.61106.4)
39.4 (17.766.0)
73.6 (0.0763.7)
4384.1 ± 732.8
0.0 (0.0-0.0)
0.0 (0.0-0.6)
92.0 (90.693.8)
4.3 (0.7-9.0)
0.5 (0.0-1.3)
0.0 (0.0-0.0)
1.5 (0.3-3.5)
43.9 (35.7-49.6)
80.5 (78.2-83.4)
25.0 (15.3-41.0)
1.11 (1.09-1.11)
3020.9 ± 360.1
0.0 (0.0-0.0)
0.0 (0.0-0.0)
94.9 (94.895.0)
0.5 (0.5-0.5)
1.1 (1.1-1.1)
0.0 (0.0-0.0)
2.0 (1.7-2.2)
27.5 (25.3-29.7)
86.0 (85.5-86.6)
38.6 (38.4-38.9)
1.09 (1.09-1.09)
Used
(n = 83)
111
Random
(n = 51)
217.7 ± 2.2
293.05 ± 13.7
492.0 (118.0195.2 (96.91368.6)
662.6)
60.6 (31.6283.2 (109.1101.2)
422.5)
999.0 (0.02829.8 (1606.24949.3)
4272.9)
3739.5 ± 97.8
2660.2 ± 168.8
0.0 (0.0-0.0)
0.0 (0.0-0.0)
0.4 (0.0-1.2)
1.6 (0.2-3.2)
92.0 (88.676.9 (51.395.2)
89.1)
0.5 (0.4-2.0)
11.4 (0.5-26.1)
1.0 (0.8-2.4)
1.0 (0.2-2.9)
0.0 (0.0-0.3)
0.3 (0.0-1.1)
2.2 (0.7-2.8)
1.2 (0.0-6.2)
36.6 (26.0-56.0) 96.3 (47.1-143.0)
82.4 (76.8-86.5) 62.8 (46.9-79.4)
22.0 (13.4-45.5)
6.3 (2.8-19.1)
1.10 (1.09-1.10) 1.10 (1.09-1.11)
U-test
df
t
P
Z
P
133
133
6.788
-
0.001
-
-2.454
0.014
133
-
-
-6.326
0.001
133
-
-
-1.544
0.123
133
133
133
133
5.936
-
0.001
-
-4.394
-4.809
-5.717
0.001
0.001
0.001
133
133
133
133
133
133
133
133
-
-
-3.347
-0.466
-3.035
-0.310
-4.812
-4.929
-5.073
-2.568
0.001
0.641
0.002
0.757
0.001
0.001
0.001
0.010
TABLE 7. Comparisons (mean ± SE) of landscape associations among three Cerulean Warbler populations in northern
Alabama, 2005-2006. Uppercase letters indicate where differences exist using Tukey tests; lowercase letters indicate where
differences exist using an adjusted Bonferroni correction. Refer to Appendix D for variable descriptions.
Study Site
Landscape
Variable
112
ELEV
ROAD
STRM§
TRL§
TSL§
WATER
DVLPD§
DECMX
EVER†
SHRUB
GRASS§
AGRI
ED§
TCAI§
MCA†
MPFD§
ANOVA
Kruskal-Wallis
Walls of Jericho
(n = 36)
Larkin Fork
(n = 30)
Bankhead NF
(n = 17)
df
F
P
H
P
223.6 ± 2.5a
1336.6 ± 61.0a
55.2 ± 0.3
7.5 ± 2.4A
3390.8 ± 1.4A
0.0 ± 0.0
0.0 ± 0.0A
95.5 ± 0.3a
0.5 ± 0.0A
1.0 ± 0.1a
0.0 ± 0.0A
2.0 ± 0.2a
24.4 ± 0.0A
86.7 ± 0.0A
46.2 ± 0.1A
1.09 ± 0.00
224.1 ± 3.7a
89.6 ± 14.2b
72.0 ± 0.3
5104.8 ± 0.8B
3538.8 ± 0.2A
0.0 ± 0.0
1.3 ± 0.0B
89.2 ± 0.6b
0.7 ± 0.1A
3.8 ± 0.3b
0.6 ± 0.0B
3.8 ± 0.4b
46.9 ± 0.0B
78.8 ± 0.0B
16.6 ± 0.1B
1.10 ± 0.00
194.1 ± 2.7b
629.8 ± 74.7c
61.9 ± 0.7
1531.2 ± 25.1C
4657.4 ± 4.0B
0.0 ± 0.0
0.6 ± 0.0C
84.2 ± 1.8b
13.1 ± 0.1B
0.1 ± 0.0c
0.0 ± 0.0A
0.1 ± 0.0c
76.8 ± 0.1C
67.9 ± 0.0C
9.9 ± 0.2B
1.09 ± 0.00
82
82
82
82
82
82
82
82
82
82
82
82
82
82
82
82
0.97
294.05
16.63
243.10
292.16
39.61
79.75
75.26
79.83
2.29
0.381
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.108
36.31
62.06
0.00
54.75
70.46
54.41
-
0.001
0.001
1.000
0.001
0.001
0.001
-
§
back transformed from sqrt(x)
back transformed from log10(x+1)
†
112
TABLE 8. Top ten competing AIC models used for development of Cerulean Warbler habitat models. Second-order AICc
valuesa were calculated using -2log-likelihood values (L) and K (total number of parameters +1). Akaike weights (wi) were
derived from each model’s likelihood (MLb) divided by the sum of all ML values. Beta coefficients were used to indicates a
variable’s relationship (+/-) to Cerulean Warbler presence. Refer to Appendix D for descriptions of landscape variables.
113
Model
L
K
AIC
∆AICc
MLb
wi
ELEV (-), ROAD (+), STRM (-), TRL (+), TSL (+), DVLPD (-), DECMX (+)
20.562
8
36.562
0.00
1.00
0.69
ELEV (-), ROAD (+), STRM (-), TRL (+), TSL (+), DVLPD (-), DECMX
(+), AGRI (+)
20.059
9
38.059
1.79
0.41
0.28
ELEV (-), STRM (-), TRL (+), TSL (+), AGRI (-), DECMX (+)
32.301
7
46.301
9.48
0.01
0.01
ELEV (-), STRM (-), TRL (+), TSL (+), DVLPD (-), DECMX (+)
33.302
7
47.302
10.49
0.01
0.00
ELEV (-), TRL (+), TSL (+), AGRI (-), DECMX (+)
35.915
6
47.915
10.88
0.00
0.00
ELEV (-), TSL (+), TRL (+), DECMX (+)
38.470
5
48.47
11.25
0.00
0.00
ELEV (-), TRL (+), TSL (+), DECMX (+), SLOPE (+)
37.459
6
49.459
12.42
0.00
0.00
ELEV(-), TRL (±), TSL (±), DECMX (+), DVLPD (-)
37.915
6
49.915
12.88
0.00
0.00
ELEV (-), STRM (-), DECMX (+), AGRI (-), DVLP (+)
38.820
6
50.820
13.78
0.00
0.00
ELEV (-), SLOPE (+), ROAD (±), STRM (+), DVLP (+), DECMX (+)
39.106
7
53.106
16.29
0.00
0.00
a
(AICc) = -2log(likelihood) + 2K + 2K(K+1)/(n+K+1)
b
Model likelihood = exp(-∆c/2)
113
APPENDIX A. Sample letter used to request permission to access private property in
Jackson County, Alabama.
July 4, 2004
Meeghan, Kaylee and William Pollock
1234 Main St.
Hytop, AL 56789
Dear Pollocks:
My name is John Carpenter, and I am currently pursuing a Master of Science degree in wildlife ecology at Alabama A&M
University. As a requirement for this degree, I must conduct a research project and present the results to a committee of
faculty members. The topic I have chosen for my thesis research is the birds of northern Alabama. After reviewing
historical and current literature regarding this subject, I have determined that the unique landscape of Jackson County would
provide me with the most opportunity to study the diversity of bird species representative of northern Alabama.
I visited the Jackson County Courthouse to acquire the contact information for those landowners that I would need to
contact to gain permission to their property, which is how I was able to obtain your name and address. In general, my goal
is to follow individual birds on foot and record their behaviors in a notebook. Although I may not necessarily conduct a
survey on your property, I may need to pass through one of your parcels to reach a desired location. I plan to visit these
sites several times during the late spring and throughout the summer in 2005 and 2006.
Please be aware that I am fully insured by the university and that my signature below releases you from any liability while I
am on your property. Also, I will avoid surveying during designated hunting seasons and will wear protective snake-proof
apparel at all times. Furthermore, your name and address will be held under strict confidentiality, and most importantly,
your property and your privacy will be respected at all times.
Enclosed you will find an addressed and stamped postcard asking for permission to access your property in Jackson County
to survey for birds for my research. At your earliest convenience, please sign, date, and check the appropriate response and
place it in your mailbox. If you have any questions or concerns, please do not hesitate to contact me at the phone number or
email address listed below.
Thank you for your time, and I hope that we are able to reach an agreement.
Sincerely,
John Carpenter
Alabama A&M University
Center for Forestry and Ecology
P. O. Box 1927
Normal, AL 35762-0700
256.372.5991
john.carpenter@aamu.edu
114
APPENDIX B. Microhabitat variable codes and explanations measured from 0.04 ha plots.
115
Variable Code
Unit
Description
BA
NTREE
BA:TREE
DECBA
NSNAG
SNAGBA
RBASNG
LOWHT
MIDHT
UPHT
CNPYCV
CNPYSTR
NGAPDIS
NGAPSZ
per ha
per ha
0.0 to1.0
0.0 to 100.0
Per ha
Per ha
Per ha
m
m
m
0.0 to 100.0
0.0 to 1.0
m
1 to 4
Basal area of all live stems ≥3cm DBH
No. of all live stems ≥3cm DBH
Ratio of live basal area to no. of live stems ≥3cm DBH
Percent of basal area contributed by deciduous trees
No. of snags ≥7.5 cm
Basal area of all snags ≥7.5 cm
Ratio of snag basal area to no. of snags ≥7.5 cm
Lower canopy height; measured from suppressed crowns
Middle canopy height; measured from intermediate crowns
Upper canopy height; measured from dominant/co-dominant crowns
Percent canopy cover
Canopy structure. 0 = no diversity, 1 = high diversity
Distance to nearest canopy gap <50 m from plot center
Size of nearest canopy gap (1 = ≥10 m2 <20 m2, 2 = ≥20 m2 <30 m2, 3 = ≥30 m2 <40 m2,
2
4 = ≥40 m )
LGAPDIS
LGAPSZ
m
1 to 4
Distance to largest canopy gap < 50 m from plot center
Size of largest canopy gap (1 = ≥10 m2 <20 m2, 2 = ≥20 m2 <30 m2, 3 = ≥30 m2 <40 m2,
2
4 = ≥40 m )
UNDRSTRY
SLOPE
ASPCT
TRDIS
TRDBH
LOGDIS
LOGDBH
LOGLNG
per ha
0.0 to 90.0
-1.0 to 2.0
m
cm
m
cm
m
No. of seedlings and shrub stems <3 cm DBH
Degree of incline
Transformed direction of hillside
Mean distance to nearest tree in each quarter of habitat plot (NE, SE, SW, NW)
Mean DBH of nearest tree in each quarter
Mean distance to nearest log (log ≥1.5 m in length and ≥8 cm) in each quarter
Mean DBH of nearest log in each quarter
Length of nearest log in each quarter
115
APPENDIX C. Original and reduced variables for National Land Cover Data used in landscape analyses.
116
Original Classification
Descriptiona
Reduced Classification
1.) Open Water
All areas of open water with <25% vegetation
1.) Open Water
2.) Developed, Open Space
3.) Developed, Low Intensity
4.) Developed, Mid Intensity
5.) Developed, High
Intensity
<20% impervious surfaces. Constructed materials/vegetation
20-49% impervious surfaces. Constructed materials/vegetation 2.) Developed
50-79% impervious surfaces. Constructed materials/vegetation
80-100% impervious surfaces. Constructed materials/vegetation
6.) Barren Rock
Bedrock, strip mines, gravel pits, & other earthen material
3.) Barren Rock
7.) Deciduous Forest
8.) Mixed Forest
Trees >5m tall, >20% cover, >75% tree species shed foliage
Trees >5m tall, >20% cover, no dominant tree species
4.) Deciduous-Mixed
Forest
9.) Evergreen Forest
Trees >5m tall, >20% cover, >75% species maintain leaves
5.) Evergreen Forest
10.) Shrub/Scrub
Dominated by shrubs/trees <5m tall, >20% cover.
6.) Shrubland
11.) Grassland/Herbaceous
>80% herbaceous vegetation. Includes areas used for grazing
7.) Grassland
12.) Pasture/Hay
13.) Cultivated Crops
>20% vegetation intended for production of perennial crops
>20% vegetation intended for production of annual crops
8.) Agriculture
14.) Woody Wetlands
15.) Emergent Herbaceous
Wetlands
Substrate periodically saturated, >20% forest or shrubland
Substrate periodically saturated, >80% herbaceous vegetation
9.) Wetlands
a
From http://www.mrlc.gov/nlcd_definitions.asp
116
APPENDIX D. Variable codes and explanations for landscape metrics used for analyses.
Variable
Name
Unit
Descriptiona
Data Source
ED
MPFD
m/ha
1.0-2.0
Amount of edge relative to landscape area
Shape complexity. 1 = simple perimeters,
2 = complex perimeters
Mean size of disjunct patches
Percent of landscape containing core area
Percent of open water in the landscape
Percent of developed area in the landscape
Percent of deciduous-mixed forest in the
landscape
Percent of evergreen forest in the landscape
Percent of shrubland in the landscape
Percent of grassland in the landscape
Percent of agriculture (pasture/hay) in the
landscape
NLCD 2001, 30m
NLCD 2001, 30m
EVER
SHRUB
GRASS
AGRI
Edge Density
Mean Patch Fractal
Dimension
Mean Core Area
Total Core Area Index
Water
Developed
Deciduous/Mixed
Forest
Evergreen Forest
Shrub
Grassland
Agriculture
ELEV
Elevation
m
Elevation of plot center
DEM, 30m
ROAD
STRM
TRL
TSL
Distance to Road
Distance to Stream
Total Road Length
Total Stream Length
m
m
m
m
Distance to nearest road
Distance to nearest stream
Total length of all roads in the landscape
Total length of all streams in the landscape
Tiger 2000
RF3 1994
Tiger 2000
RF3 1994
MCA
TCAI
WATER
DVLPD
DECMX
117
a
ha
0.0-100.0
0.0-100.0
0.0-100.0
0.0-100.0
0.0-100.0
0.0-100.0
0.0-100.0
0.0-100.0
From McGarigal and Marks (1995) and Rempel (1997).
117
NLCD 2001, 30m
NLCD 2001, 30m
NLCD 2001, 30m
NLCD 2001, 30m
NLCD 2001, 30m
NLCD 2001, 30m
NLCD 2001, 30m
NLCD 2001, 30m
APPENDIX E. Additional searches for Cerulean Warblers in northern Alabama, 20042006.
Date
Location
County
Playback
6/8/04
6/9/04
6/10/04
6/11/04
6/12/04
6/15/04
6/16/04
6/16/04
7/5/04
Burks Creek & Estill Fork
Tate’s Cove, Skyline WMA
Fall Creek, Bankhead NF
Dry Hollow & Hagood Creek, BNF
Jones Creek
Dry Creek
Lick Fork
Guess Creek, Jacobs Mountain.
S. Saunty Creek, Bucks Pocket State Park
Jackson
Jackson
Lawrence
Lawrence
Jackson
Jackson
Jackson
Jackson
Marshall
No
No
No
No
No
No
No
No
No
5/28/05
6/8/05
6/15/05
DeKalb
Jackson
Colbert
Yes
Yes
Yes
6/16/05
6/17/05
6/20/05
6/21/05
6/23/05
-
L. River Canyon NP
Calloway Sinks, Sharp-Bingham Mtn.
Buzzard’s Roost Creek, Bear Creek, Cedar Creek
Chandelower Creek, Store Branch
S. Larkin Fork, Cnty Rd. 27
Estill Fork
L. Coon Creek, Skyline WMA
Tate’s Cove, Skyline WMA
Flint Creek, BNF
West Fork, BNF
Jackson
Jackson
Jackson
Jackson
Lawrence
Winston
Yes
Yes
Yes
Yes
Yes
Yes
6/2/06
6/4/05
6/25/06
Flint Creek, BNF
Tate’s Cove, Skyline WMA
Miller Mountain
Lawrence
Jackson
Jackson
Yes
Yes
Yes
118
APPENDIX F. Abundance (No.) and total percent (%) of breeding bird species detected at
“used” point counts in northern Alabama, 2005-2006. Species codes set in bold italics
indicate species not detected at “random” locations.
Species Code
Common Name
Scientific Name
No.
%
CERW
INBU
REVI
CARW
NOCA
GBHE
ETTI
NOPA
AMRE
CACH
WOTH
COYE
KEWA
AMCR
ACFL
RBWO
BGGN
HOWA
YBCH
YTVI
WBNU
SCTA
YBCU
UNK
WEWA
BHCO
BLJA
DOWO
YTWA
BWWA
LOWA
EAWP
RSHA
SUTA
BEKI
Cerulean Warbler
Indigo Bunting
Red-eyed Vireo
Carolina Wren
Northern Cardinal
Great Blue Heron
Eastern Tufted Titmouse
Northern Parula
American Redstart
Carolina Chickadee
Wood Thrush
Common Yellowthroat
Kentucky Warbler
American Crow
Acadian Flycatcher
Red-bellied Woodpecker
Blue-gray Gnatcatcher
Hooded Warbler
Yellow-breasted Chat
Yellow-throated Vireo
White-brested Nuthatch
Scarlet Tanager
Yellow-billed Cuckoo
Unknown
Worm-eating Warbler
Brown-headed Cowbird
Blue Jay
Downy Woodpecker
Yellow-throated Warbler
Blue-winged Warbler
Lousiana Waterthrush
Eastern Wood-Pewee
Red-shouldered Hawk
Summer Tanager
Belted Kingfisher
Dendroica cerulea
Passerina cyanea
Vireo olivaceus
Thryothorus ludovicianus
Cardinalis cardinalis
Ardea herodias
Baeolophus bicolor
Parula americana
Setophaga ruticilla
Poecile carolinensis
Hylocichla mustelina
Geothlypis trichas
Oporornis formosus
Corvus brachyrhyncos
Empidonax virescens
Melanerpes carolinus
Polioptila caerulea
Wilsonia citrina
Icteria virens
Vireo flavifrons
Sitta carolinensis
Piranga olivacea
Coccyzus americanus
Helmitheros vermivorus
Molothrus ater
Cyanocitta cristata
Picoides pubescens
Dendroica dominica
Vermivora pinus
Seiurus motacilla
Contopus virens
Buteo lineatus
Piranga ruba
Ceryle alcyon
60
49
39
36
34
33
27
26
24
24
21
20
20
17
16
15
11
11
11
11
9
8
8
7
7
6
6
6
6
5
5
4
4
4
3
9.7
7.9
6.3
5.8
5.5
5.3
4.4
4.2
3.9
3.9
3.4
3.2
3.2
2.8
2.6
2.4
1.8
1.8
1.8
1.8
1.5
1.3
1.3
1.1
1.1
1.0
1.0
1.0
1.0
0.8
0.8
0.6
0.6
0.6
0.5
119
APPENDIX F. Continued.
Species Code
Common Name
Scientific Name
No.
%
EATO
GCFL
HAWO
AMGO
WEVI
RWBB
UFLY
UWDP
Eastern Towhee
Great Crested Flycatcher
Hairy Woodpecker
American Goldfinch
White-eyed Vireo
Red-winged Blackbird
Unkown Flycatcher
Unknown woodpecker
Pipilo erythrophthalmus
Myiarchus crinitus
Picoides villosus
Carduelis tristis
Vireo griseus
Agelaius phoeniceus
-
3
3
3
2
2
1
1
1
0.5
0.5
0.5
0.3
0.3
0.2
0.2
0.2
120
APPENDIX G. Abundance (No.) and total percent (%) of breeding bird species detected at
“random” point counts in northern Alabama, 2005-2006. Species codes set in bold italics
indicate species not detected at “used” locations.
Species Code
Common Name
Scientific Name
No.
%
CARW
REVI
NOCA
INBU
AMCR
CACH
ACFL
HOWA
SUTA
ETTI
YBCU
SCTA
UNK
BLJA
WOTH
YTVI
GCFL
PIWA
BGGN
RBWO
WEVI
YBCH
WBNU
WEWA
OVEN
EAWP
LOWA
BTNW
Carolina Wren
Red-eyed Vireo
Northern Cardinal
Indigo Bunting
American Crow
Carolina Chickadee
Acadian Flycatcher
Hooded Warbler
Summer Tanager
Eastern Tufted Titmouse
Yellow-billed Cuckoo
Scarlet Tanager
Unknown
Blue Jay
Wood Thrush
Yellow-throated Vireo
Great Crested Flycatcher
Pine Warbler
Blue-gray Gnatcatcher
Red-bellied Woodpecker
White-eyed Vireo
Yellow-breasted Chat
White-brested Nuthatch
Worm-eating Warbler
Ovenbird
Eastern Wood-Pewee
Lousiana Waterthrush
Black-throated Green
Warbler
Common Yellowthroat
Downy Woodpecker
Northern Parula
Pileated Woodpecker
Northern Bobwhite
Red-shouldered Hawk
Eastern Towhee
Great Blue Heron
Prairie Warbler
Thryothorus ludovicianus
Vireo olivaceus
Cardinalis cardinalis
Passerina cyanea
Corvus brachyrhyncos
Poecile carolinensis
Empidonax virescens
Wilsonia citrina
Piranga ruba
Baeolophus bicolor
Coccyzus americanus
Piranga olivacea
Cyanocitta cristata
Hylocichla mustelina
Vireo flavifrons
Myiarchus crinitus
Dendroica pinus
Polioptila caerulea
Melanerpes carolinus
Vireo griseus
Icteria virens
Sitta carolinensis
Helmitheros vermivorus
Seiurus aurocapillus
Contopus virens
Seiurus motacilla
Dendroica virens
42
36
33
22
21
21
18
18
18
17
17
16
15
12
12
12
11
10
9
9
9
9
8
8
7
6
6
6
8.7
7.4
6.8
4.5
4.3
4.3
3.7
3.7
3.7
3.5
3.5
3.3
3.1
2.5
2.5
2.5
2.3
2.1
1.9
1.9
1.9
1.9
1.6
1.6
1.4
1.2
1.2
1.2
Geothlypis trichas
Picoides pubescens
Parula americana
Dryocopus pileatus
Colinus virginianus
Buteo lineatus
Pipilo erythrophthalmus
Ardea herodias
Dendroica discolor
5
5
5
5
4
4
3
3
3
1.0
1.0
1.0
1.0
0.8
0.8
0.6
0.6
0.6
COYE
DOWO
NOPA
PIWO
NOBO
RSHA
EATO
GBHE
PRWA
121
APPENDIX G. Continued.
Species Code
Common Name
Scientific Name
No.
%
AMGO
BAOW
BWHA
YSFL
BASW
BAWW
BHCO
DEJU
HAWO
UWDP
American Goldfinch
Barred Owl
Broad-winged Hawk
Yellow-shafted Flicker
Barn Swallow
Black-and-White Warbler
Brown-headed Cowbird
Dark-eyed Junco
Hairy Woodpecker
Unknown woodpecker
Carduelis tristis
Strix varia
Buteo platypterus
Colaptes auratus
Hirundo rustica
Mniotilta varia
Molothrus ater
Junco hyemalis
Picoides villosus
-
2
2
2
2
1
1
1
1
1
1
0.4
0.4
0.4
0.4
0.2
0.2
0.2
0.2
0.2
0.2
122