Breeding Ecology Nest Site Selection and Human Influence of White-tailed Hawks on
the Texas Barrier Islands
by
Carey L. Haralson, B.S.
A Thesis
In
WILDLIFE SCIENCE
Submitted to the Graduate Faculty
of Texas Tech University in
Partial Fulfillment of
the Requirements for
the Degree of
MASTER OF SCIENCE
Approved
Dr. Clint W. Boal
Dr. Craig Farquhar
Dr. Mark C. Wallace
Fred Hartmeister
Dean of the Graduate School
May, 2008
COPYRIGHT 2008, CAREY L. HARALSON
ACKNOWLEDGEMENTS
This project would not have been possible without funding from Texas Parks and
Wildlife Department, and the logistical support from the USGS - Texas Cooperative Fish
and Wildlife Research Unit, USFWS - Aransas National Wildlife Refuge, NPS – Padre
Island National Seashore, and the Rob and Bessie Welder Wildlife Refuge. I also thank
Houston Safari Club for their gracious scholarship, which helped personal ends meet
when things were tight.
I also extend my gratitude to Darrell Echols, Michelle Havens and Wade Stablein
from Padre Island National Seashore, as well as Joe Saenz, Felipe Prieto, and Adolfo
Cantu from Aransas National Wildlife Refuge for all of their assistance and suggestions.
I also thank Dr. Lynn Drawe, Dr. Selma Glasscock and Dr. Terry Blankenship for always
making room for me at the Welder Wildlife Refuge.
I thank Dr. Clint Boal for giving me the opportunity to come to Texas Tech. The
effort he put forth as my advisor to challenge and expand my professional skills, while
offering encouragement and guidance are of immeasurable value and has certainly helped
me prepare for my future goals. I thank my committee members; Dr. Mark Wallace and
Dr. Craig Farquhar, their suggestions and expertise proved invaluable. A special thanks
to Dr. David Wester and Dr. Matthew Butler for the countless hours they spent helping
me with my analyses. I thank my fellow students, C. Huber, N. and H. Mannan, and
many others that have provided me with camaraderie and counsel throughout the last few
years.
ii
Finally I thank my family, DRH III, and J. and C. Heiting; thanks for your love,
support and encouragement as I struggled to figured out where I was going. Thanks for
teaching me how wonderful the outdoors can be and allowing me to grow up in an area
where I was free to explore wildlife at an early age. I also thank N. Gripentrog for
understanding the need for a sister to move across the country, and always being there to
listen to my frustrations. Last but certainly not least, I thank my husband, B. N. Strobel,
you were always there to offer support, encouragement, and love, in spite of the ordeals
of your own research. Thanks for putting up with me on days when things did not go
right. You are the “best technician” I had, and someone from whom I will never stop
learning.
iii
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ................................................................................. ii
ABSTRACT .......................................................................................................... vi
LIST OF TABLES ............................................................................................. viii
LIST OF FIGURES ............................................................................................ xii
I.
INTRODUCTION ......................................................................................... 1
Literature Cited ............................................................................... 3
II. BREEDING ECOLOGY OF WHITE-TAILED HAWKS ON THE
TEXAS BARRIER ISLANDS ...................................................................... 4
Abstract............................................................................................. 4
Introduction ...................................................................................... 5
Study Area ........................................................................................ 7
Methods........................................................................................... 11
Results ............................................................................................. 15
Discussion........................................................................................ 20
Management Implications ............................................................. 26
Literature Cited ............................................................................. 27
III. NEST SITE SELECTION OF WHITE-TAILED HAWKS ON THE
TEXAS BARRIER ISLANDS. ................................................................... 43
Abstract........................................................................................... 43
iv
Introduction .................................................................................... 44
Study Area ...................................................................................... 46
Methods........................................................................................... 50
Results ............................................................................................. 56
Discussion........................................................................................ 58
Management Implications ............................................................. 62
Literature Cited ............................................................................. 63
IV. BEHAVIOR OF WHITE-TAILED HAWKS BREEDING AT TWO
LEVELS OF HUMAN DISTURBANCE ON THE TEXAS BARRIER
ISLANDS ...................................................................................................... 76
Abstract........................................................................................... 76
Introduction .................................................................................... 76
Study Area ...................................................................................... 79
Methods........................................................................................... 83
Results ............................................................................................. 87
Discussion........................................................................................ 89
Management Implications ............................................................. 91
Literature Cited ............................................................................. 92
v
ABSTRACT
I conducted fieldwork on Matagorda, Mustang and North Padre Islands along the
Texas coast in 2006 and 2007. I located breeding White-tailed Hawk (Buteo
albicaudatus; WTHA) pairs using road and point surveys. I monitored productivity, and
nest success for 64 actively nesting pairs. I compared the proportion of nesting pairs per
occupied territory between islands. I used a nonparametric Mann-Whitney U test to
determine differences between nestling and fledgling production on Matagorda and
Mustang Islands. North Padre Island was omitted due to a small sample size. The mean
earliest clutch initiation for all islands was March 3 (± 3.2 days). Observed nest success
on North Padre Island (22.2%) was markedly lower than Matagorda (56.8%) and
Mustang (58.3%) Islands. Mayfield nest success estimate for all sites was 41.6%. There
was no difference in nestling production (Matagorda x̄ = 1.05 ± 0.91; Mustang x̄ = 1.00 ±
1.83) or in fledgling production (Matagorda x̄ = 0.89 ± 0.87; Mustang x̄ = 1.08 ± 1.16)
between the two islands. Productivity on Mustang Island is not different than Matagorda
Island despite having a high level of human disturbance. This may be a result of WTHAs
adapting to human disturbance and breeding pairs having larger territories and no
density-dependence influence, such as what may be occurring on Matagorda Island where
WTHAs may be at population saturation.
I measured nest site selection at 38 nest sites and 38 paired random sites. I
created a resource selection probability function for WTHA nest site selection using a
logistic regression model of the characteristics measured at a subset of 19 nest sites and
paired random sites on Matagorda Island. Models were evaluated using Akaike
vi
Information Criterion. The best model on Matagorda Island used the parameters of shrub
category, nearest-neighbor distance, and distance to road to correctly differentiate 83% of
nest sites from random sites on Matagorda Island, 70% on Mustang Island, and 50% on
North Padre Islands. I then created model sets for Mustang and North Padre Islands, of
which the best model for both islands used the parameters of shrub height, shrub
circumference, and their interaction. The resource selection probability function from the
best model on Matagorda Island should be used with caution. Overall, it appears that
densely branched and thorned shrub species are important to WTHA nest site selection.
I conducted behavioral observations on breeding WTHA pairs on Matagorda,
Mustang and North Padre Islands, Texas in 2007. These islands were classified into high
human impact (Mustang and North Padre Islands) and low human impact (Matagorda
Island). Observations were conducted only during 2-3.5 hours after sunrise, after which
visibility decreased due to shimmer caused by radiated heat. I used a generalized liner
model with a logit link function that tested for differences between islands. Data
collected from two breeding stages were analyzed with a repeated measures analysis.
Pairs on Matagorda Island spent more time flying than pairs Mustang and North Padre
Islands. This may be a result of an increase in interspecific and intraspecific territorial
defense on Matagorda Island. There appeared to be no direct human induced influences
to WTHA behavior.
vii
LIST OF TABLES
2.1
Descriptive statistics of White-tailed Hawk breeding ecology
for Matagorda, Mustang, and North Padre Islands between
2006 and 2007. .......................................................................................................33
2.2
Descriptive statistics of White-tailed Hawk breeding ecology
averaged for Matagorda, Mustang, and North Padre Islands
during 2006-2007. ..................................................................................................34
2.3
Descriptive statistics of White-tailed Hawk breeding ecology
for Matagorda Island during 2006-2007. ...............................................................35
2.4
Descriptive statistics of White-tailed Hawk breeding ecology
for Mustang Island during 2006-2007. ..................................................................36
2.5
Descriptive statistics of White-tailed Hawk breeding ecology
for North Padre Island during 2006-2007. .............................................................37
2.6
The distribution of the number of nestlings produced in Low
Human Disturbance (LHD) nests versus High Human
Disturbance (HHD) nests during 2006-2007. ........................................................38
2.6
The distribution of the number of fledglings produced in Low
Human Disturbance (LHD) nests versus High Human
Disturbance (HHD) nests during 2006-2007. ........................................................38
3.1
Candidate models from Matagorda Island describing the
probability of a potential nest site being selected by Whitetailed Hawks built from 2006-2007. Models in italics are
within the model confidence interval (Burnham and Andreson
2002). .....................................................................................................................67
3.2
Coefficients of variables and their standard errors for the
Matagorda Island resource probability function of White-tailed
Hawk nest site selection. ........................................................................................68
3.3
Candidate models from Mustang Island describing the
probability of a potential nest site being selected by Whitetailed Hawks built from 2006-2007. Models in italics are
within the model confidence interval (Burnham and Andreson
2002). .....................................................................................................................69
viii
3.4
Candidate models from North Padre Island describing the
probability of a potential nest site being selected by Whitetailed Hawks built from 2006-2007. Models in italics are
within the model confidence interval (Burnham and Andreson
2002). .....................................................................................................................70
3.5
Means and standard deviations for variables collected at
White-tailed Hawk nest sites on Matagorda, Mustang and
North Padre Islands in 2006 and 2007. ..................................................................71
3.6
Means and standard deviations of nest site and random site
variables on Matagorda Island in 2006 and 2007. .................................................72
3.7
Means and standard deviations of nest site and random site
variables on Mustang Island in 2006 and 2007. ....................................................72
3.8
Means and standard deviations of nest site and random site
variables on North Padre Island in 2006 and 2007. ...............................................73
3.9
Table 2.9. The proportion of shrubs encountered at nest and
random sites. The shrubs are listed in their respective category.
DT = densely branched and thorned; OT = openly branched and
thorned; D = densely branched; O = openly branched ..........................................74
3.10.
The proportion of all shrubs used as nesting substrate. The shrubs are
listed in their respective category. DT = densely branched and thorned; OT
= openly branched and thorned; D = densely branched; O = openly
branched .................................................................................................................75
4.1
Percent of time spent perched by breeding white-tailed hawks
during morning observation periods on Matagorda and Mustang
Island. Proportions are presented by the nesting stage (egg or
nestling) and according to island. Due to no significant
interaction P-values are reported for the stage effect and island
effect only. .............................................................................................................97
4.2
Percent of time spent perched on nest by breeding white-tailed
hawks during morning observation periods on Matagorda and
Mustang Island. Proportions are presented by the nesting stage
(egg or nestling) and according to island. Due to no significant
interaction P-values are reported for the stage effect and island
effect only. .............................................................................................................97
ix
4.3
Percent of time spent preening by breeding white-tailed hawks
during morning observation periods on Matagorda and Mustang
Island. Proportions are presented by the nesting stage (egg or
nestling) and according to island. Due to no significant
interaction P-values are reported for the stage effect and island
effect only. .............................................................................................................98
4.4
Percent of time spent flying by breeding white-tailed hawks
during morning observation periods on Matagorda and Mustang
Island. Proportions are presented by the nesting stage (egg or
nestling) and according to island. Due to no significant
interaction P-values are reported for the stage effect and island
effect only. .............................................................................................................98
4.5
Percent of time spent feeding by breeding white-tailed hawks
during morning observation periods on Matagorda and Mustang
Island. Proportions are presented by the nesting stage (egg or
nestling) and according to island. Due to no significant
interaction P-values are reported for the stage effect and island
effect only. .............................................................................................................99
4.6
Percent of time spent incubating/brooding by breeding whitetailed hawks during morning observation periods on Matagorda
and Mustang Island. Proportions are presented by the nesting
stage (egg or nestling) and according to island. Due to no
significant interaction P-values are reported for the stage effect
and island effect only. ............................................................................................99
4.7
Percent of time spent out of sight in an unknown location by
breeding white-tailed hawks during morning observation
periods on Matagorda and Mustang Island. Proportions are
presented by the nesting stage (egg or nestling) and according to
island. Due to no significant interaction P-values are reported
for the stage effect and island effect only. ...........................................................100
x
4.8
Percent of time spent out of sight in a known location by
breeding white-tailed hawks during morning observation
periods on Matagorda and Mustang Island. Proportions are
presented by the nesting stage (egg or nestling) and according to
island. Due to no significant interaction P-values are reported
for the stage effect and island effect only. ...........................................................100
4.9
Prey items of breeding White-tailed Hawks observed through
nest checks and direct observations on Matagorda, Mustang and
North Padre Islands, Texas 2006 and 2007. Items are classified
into the lowest possible taxon. .............................................................................101
xi
LIST OF FIGURES
2.1
White-tailed Hawk nesting chronology on Matagorda, Mustang,
and North Padre Islands in 2006 and 2007. Estimated nestling
age was back-dated to estimate egg laying date. (Matagorda n =
29; Mustang n = 9; North Padre n = 3) ..................................................................39
2.2
White-tailed hawk nest locations on Matagorda Island, Texas,
2006 and 2007. .......................................................................................................40
2.3
White-tailed hawk nest locations on Mustang Island, Texas,
2006 and 2007. .......................................................................................................41
2.4
White-tailed hawk nest locations on North Padre Island, Texas,
2006 and 2007. .......................................................................................................42
4.1
Proportion of 5 white-tailed hawk prey categories observed on
Matagorda, Mustang and North Padre Islands, Texas in 2006
and 2007. ..............................................................................................................102
xii
CHAPTER I
INTRODUCTION
Along the coastal bend region of southeast Texas, the White-tailed Hawk (Buteo
albicaudatus; hereafter WTHA) is listed as a state-threatened species. In the U.S., this
species is found only on the coastal grasslands and adjacent inland savannahs of Texas
(Farquhar 1992). The WTHA population size was estimated at 200 breeding pairs for the
state of Texas in 1977 (Morrison 1978), but there are insufficient data to accurately
estimate the current population. Preliminary surveys suggest WTHAs may breed at
higher densities on some barrier islands than on the mainland (Boal and Haralson,
unpublished data). This may be related to human associated development occurring on
the mainland, such as habitat conversion into crop production.
Urban and agricultural development have fragmented and degraded much of
coastal Texas, posing serious threats to this region’s biological health (The Nature
Conservancy 2002). Although WTHAs demonstrate little tolerance for human
disturbance near their nests by readily abandoning clutches (Stevenson and Meitzen
1946), no study has specifically examined the potential impacts of human activities on
the breeding ecology of WTHAs. It is important to understand how human disturbance
may influence breeding behavior in order to develop ways to minimize human
disturbance impacts on breeding avian species.
1
During the summers of 2006 and 2007 I collected nesting and observation data on
Matagorda Island in Calhoun County, Mustang Island in Nueces County and North Padre
Island in Nueces, Kleberg and Kenedy Counties, Texas. This study focused on the
breeding ecology of the WTHA on three barrier islands with varying levels of human
impact and compared how these populations may be influenced by human disturbance.
The objectives of this study were (1) to assess and compare densities, productivity, and
chronology of breeding WTHAs across islands with different levels of human
disturbance, (2) to develop nest site selection models to predict nest sites most suitable
for breeding WTHAs, and (3) to assess differences in WTHA breeding behavior between
two levels of human impact.
The following chapters are formatted to facilitate future publication of results.
Each chapter has been written as a stand-alone document which results in some
redundancy in the introduction, justification, and study area. However, included in
Chapter IV with the behavioral data, are WTHA prey selection data which were observed
during the breeding season. Due to limited knowledge of WTHA prey selection I felt that
these data should be included in this thesis. I included it with this chapter due to overlap
in methodology, however it will be removed from this chapter for publication purposes as
analytically it does not fit. In addition, some overlap exists in portions of the
methodology sections, but different analytical techniques are used in each chapter. The
following chapters are formatted to meet the guidelines required by the Wildlife Society
for The Journal of Wildlife Management (Chamberlain and Johnson 2007). The chapters
2
are the responsibility of the author; however, in publication each chapter will have more
than one author.
Literature Cited
Chamberlain, M. J., and C. Johnson. 2007. Journal of Wildlife Management guidelines.
<http://jwm.allentrack.net/html/JWM_Manuscript_Guidelines.pdf>. Accessed 3
November 2007.
Farquhar, C. C. 1992. White-tailed hawk. in A. Poole, P. Stettenheim, and F. Gill,
editors. The Birds of North America, No. 30. Philadelphia: The Academy of
Natural Sciences; Washington, D.C. The American Ornithologists’ Union.
Morrison, M. L. 1978. Breeding characteristics, eggshell thinning, and population trends
of white-tailed hawks in Texas. Texas Ornithological Society Bulletin 11:35-40.
Stevenson, J. O., and L. H. Meitzen. 1946. Behavior and food habits of Sennett’s whitetailed hawk in Texas. Wilson Bulletin 58:198-205.
The Nature Conservancy. 2002. The gulf coast prairies and marshes ecoregional
conservation plan. Gulf coast Prairies and marshes Ecoregional Planning Team,
The Nature Conservancy, San Antonio, TX, USA.
3
CHAPTER II
BREEDING ECOLOGY OF WHITE-TAILED HAWKS ON THE TEXAS
BARRIER ISLANDS
Abstract
I observed the density, chronology and productivity of breeding White-tailed
Hawk (Buteo albicaudatus; WTHA) pairs on Matagorda, Mustang, and North Padre
Islands, Texas, in 2006 and 2007. The proportion of nesting pairs on each island was
compared between islands. I used nonparametric Mann-Whitney U tests to determine
differences between nestling and fledgling production on Matagorda and Mustang
Islands. North Padre Island was not used in this comparison due to a small sample size.
The mean earliest clutch initiation for all islands was March 3 (± 3.2). Observed nest
success on North Padre Island (2 of 9; 22.2%) was markedly lower than Matagorda (25 of
44; 56.8%) and Mustang (7 of 12; 58.3%) Islands. Summarized across the study area, the
Mayfield nest success estimate was 41.6%. There was a difference in the frequency
distribution of nestling and fledgling production between the high human disturbance
(HHD) nests and low human disturbance (LHD) nests. The HHD area has more nests
which produce more nestlings despite having a higher level of human disturbance. This
may be a result of WTHAs adapting to human disturbance and breeding pairs having
larger territories; whereas in the LHD area pairs may be influenced by densitydependence factors where WTHAs may be at population saturation.
4
Introduction
A species’ habitat is heterogeneous on many scales due to both natural processes
and human activities (Lord and Norton 1990). Loss of a species habitat may negatively
affect breeding success (Kurki et al. 2000), and dispersal success (With and Crist 1995,
Pither & Taylor 1998). Furthermore, the partitioning of a landscape can alter the stability
of species interactions and opportunities for coexistence in competitive and predator-prey
systems (Wiens 1989). With human population increasing, the resulting land cover
changes may reduce, perforate, isolate, and degrade bird habitat across all scales
(Marzluff 2001).
Coastal areas in particular are experiencing rapid human population growth
(Beach 2002). Coastal counties accounted for half the U.S. population in 2000 (Hobbs
and Stoops 2002). Along the Texas coast, the human population growth increased 52%
between 1980 and 2003, and is predicted to reach 7.7 million by 2008 (Crossett et al.
2004). Additionally, over one-third of the state’s permanent residents and 70% of its
economic activity are located within 160 km of the Texas coast (NOAA 1996).
Furthermore, half of the nation’s petrochemical industry and more than a quarter of its
refining capacity are found along the Texas coast along with some of the busiest port
facilities (NOAA 1996, USFWS 2000). Combined, these pressures from urban growth,
tourism, agriculture, development and industry have intensified competition for Texas
coastal resources (NOAA 1996). Historic information shows that this area has already
undergone substantial fragmentation and degradation, with 95% of the coastal grasslands
having been lost between the early 1900s and 1988 (Jahrsdoerfer and Leslie 1988).
5
Coincidentally, coastal Texas is considered one of the most biologically diverse areas of
the state (Rappole and Blacklock 1985). The variety of bird species found in this area is
among the greatest anywhere in the U.S. (Rappole and Blacklock 1985). Among this
avian diversity is the White-tailed Hawk (Buteo albicaudatus; WTHA) which, in the
United States, can only be found along coastal Texas (Farquhar 1992).
The state-threatened WTHA is one of the least studied raptors occurring in North
America (Farquhar 1992). In 1977 the WTHA population size was estimated at 200
breeding pairs in Texas (Morrison 1978), but there are insufficient data to accurately
estimate the current population. The few studies that have been conducted on WTHAs
have been on large tracts of private property or on a national wildlife refuge (Farquhar
1986, Kopeny 1988, Actkinson 2006), which typically have a more complex vegetative
community than the Texas barrier islands. Preliminary surveys suggested WTHAs may
breed at higher densities on some barrier islands than on the mainland (Boal and
Haralson, unpublished data). This may be related to habitat conversion into crop
production and/or other human associated development on the mainland. Although
WTHAs demonstrate little tolerance for human disturbance near their nests by readily
abandoning clutches (Stevenson and Meitzen 1946), no study has specifically examined
the potential impacts of human activities on WTHA densities and productivity, or the
species ecology on barrier islands. To assess how human activities may influence
WTHA breeding ecology, I examined the productivity, breeding density and breeding
chronology of WTHAs across three barrier islands with different levels of human impact.
6
Study Area
This study was conducted on Matagorda, Mustang, and North Padre Islands along
the Texas coast. Structurally, these long and narrow barrier islands are similar in having
rows of dunes along the Gulf side which are constantly being formed and moved by the
wind (Weise and White 1980, McAlister and McAlister 1993). Some dunes are held in
place by vegetation and form a ridgeline of dunes parallel to the beach. More sand may
be blown inward, creating additional dunes further inland (Weise and White 1980).
Behind the dunes, the islands are primarily flat with little topography. Vegetation on the
Texas barrier islands is simple when compared with vegetation communities found on the
mainland (Rappole and Blacklock 1985, McAlister and McAlister 1993). This is
predominantly due to salinity levels, proximity to the Gulf of Mexico, the moving sand
dunes, and the sometimes harsh weather to which the islands are exposed (Jahrsdoerfer
and Leslie 1988). Ground cover across the upland areas is typically a matrix of sedges,
grasses, and forbs interspersed with various shrub species. Both the vegetation and
climate on the barrier islands is greatly influenced by the Gulf of Mexico (Texas Parks &
Wildlife Department 1984).
Matagorda Island was the northern most island of this study area and was located
in Calhoun County, Texas. Calhoun County has a mild climate and receives about 101
cm of precipitation annually (Handbook of Texas Online 2007). The island was
approximately 61 km long with an area of 202 km2 (McAlister and McAlister 1993).
Historically, the island was primarily used for ranching and later as a bombing range for a
military air base (Texas Parks and Wildlife Department 1984, McAlister and McAlister
7
1993). In 1982 the U.S. Air Force transferred 77 km2, the northern 45 km of the Island,
to the U.S. Fish and Wildlife Service (USFWS) for “wildlife conservation purposes” and
permanent inclusion in the National Wildlife Refuge System. State lands, released by the
Air Force in 1979, comprising 106 km2 acres of adjoining salt marshes and Gulf beach,
were placed under the supervision of the Texas Parks and Wildlife Department (TPWD)
under lease from the Texas General Land Office (GLO). In 1988 the USFWS acquired
fee title of the privately held lower third portion of Matagorda Island (47 km2). In 1989,
the USFWS, TPWD and GLO conceptually agreed to a partnership arrangement for
management of the entire Island. Currently, TPWD is responsible for public use and the
USFWS is responsible for wildlife and habitat management (F. Prieto, Aransas National
Wildlife Refuge, pers. comm.). The name for this all-inclusive entity is known as
Matagorda Island National Wildlife Refuge and State Natural Area (F. Prieto, Aransas
National Wildlife Refuge, pers. comm.).
Matagorda Island was broken down into a subset of management units which are
burned on a 3-5 year rotation (F. Prieto, Aransas National Wildlife Refuge, pers. comm.).
Although Matagorda Island was open to the public, access was difficult as there was no
vehicular access to the island. This also makes Matagorda Island unique among the
barrier islands in this study. Although there was no vehicle access to the island, there
was one road which ran the length of the island and was used by USFWS, TPWD and
petroleum exploration vehicles. With exception of the sand dunes, Matagorda was flat to
gently rolling (Texas Parks and Wildlife Department 1984, McAlister and McAlister
1993). The vegetation on the island appeared to grow in bands parallel to the shoreline
8
with varying degrees of tolerance to salt (McAlister and McAlister 1993). Shrubs found
on Matagorda Island were yaupon holly (Ilex vomitoria), honey mesquite (Prosopis
glandulosa torreyana), Mexican persimmon (Diospyros texana), huisache (Acacia
farnesiana), and baccharis (Baccharis spp.) (McAlister and McAlister 1993). For this
study, I consider Matagorda Island as having low human impact across the whole island.
Mustang Island was approximately 29 km long (Tyler et al. 1996) and 85 km2,
located in Nueces County, Texas. The climate was considered humid sub-tropical for
Nueces County and received approximately 76 cm of rain annually (Handbook of Texas
Online 2007). The city of Port Aransas was located on the north end of the island and
connected to the mainland by a ferry (Tyler et al. 1996). The population of Port Aransas
was over 3,000 in 2000 (Handbook of Texas Online 2007). The beach side of Mustang
Island was being converted to resorts and condominiums, whereas the bay side of the
island was undergoing residential development on a lesser scale (i.e. houses, pastures).
Except for the sand dunes, Mustang Island was primarily flat to gently rolling. Mustang
Island was primarily private property except for the 1.2 km2 Mustang Island State Park
near the south end of the island (Tyler et al. 1996). The south end of Mustang Island was
connected to North Padre Island by a causeway (Weise and White 1980). During peak
tourism, the human population on the island would often swell to over 20,000 (Tyler et
al. 1996). Primary shrub species observed on this island were black mangrove
(Avicennia germinans), yaupon holly, honey mesquite, and baccharris. For purposes of
this study, I categorized Mustang Island as highly human impacted.
9
At over 160 km long, Padre Island was the longest sand-barrier island in the U.S.,
extending southward from Corpus Christi nearly to Mexico. It was located in Cameron,
Nueces, Kenedy, Kleberg, and Willacy Counties. These counties received between 66
and 76 cm of annual rainfall (Handbook of Texas Online 2007). Port Mansfield Channel
divided the island and was maintained to provide shipping access to the Gulf Intracoastal
Waterway (Weise and White 1980, Tyler et al. 1996). Due to the length of Padre Island
this study was limited to the northern 61 km of North Padre Island, resulting in 205 km2
surveyed.
North Padre Island was privately owned for approximately the first 32 km at the
north end, where the main uses were residential and recreational development (Tyler et
al. 1996). The remaining 109 km of the island was managed by the National Park
Service (NPS) as the Padre Island National Seashore. In 2006, the seashore attracted
732,794 visitors (Public Use Statistics Office 2007). North Padre Island was connected
to both the mainland and Mustang Island by causeways (Weise and White 1980). North
Padre Island fluctuated from 0.8 km wide to 6.4 km in width. The inner island varied
from flat and primarily tidal flats to tall inner dune ridges scattered across the island with
bayside dune ridges. Shrub species observed on North Padre Island were wax-myrtle
(Myrica pusilla), black willow (Salix nigra), honey mesquite, and huisache (Acacia
farnesiana). For purposes of this study, I considered the north end of North Padre Island
as highly impacted by human activities, but diminishing to low human influence near
Port Mansfield Channel on the south end of the island.
10
Methods
Field Methods
I conducted road surveys for WTHAs on Matagorda, Mustang and North Padre
Islands and point sampling from dune ridges on North Padre Island. Road surveys
consisted of driving and scanning for soaring or perched WTHAs (Fuller and Mosher
1987, Bibby et al. 2000). Roads provide easy access for large areas of land to be
surveyed efficiently; however not all areas across the study area may have roads (Fuller
and Mosher 1987), limiting the usefulness of this survey method. In addition,
detectability of a species is greatly influenced by the surrounding landscape (Fuller and
Mosher 1987). However, road surveys are especially useful for soaring raptors, such as
the WTHA, and in areas of open habitat (Fuller and Mosher 1987, Bibby et al. 2000).
Since vehicle access was from the beach side only, I conducted point sampling
from the dune ridge on Padre Island National Seashore (Buckland et al 2001). Point
sampling was used to acquire locations of WTHA pairs on the Padre Island National
Seashore, due to the inability to see past the dune ridge from the beach. Discrepancies
occur when trying to estimate abundances of rare species using point sampling (Hutto et
al. 1986), therefore I did not attempt to calculate WTHA abundances. Points were spaced
3.2 km apart along the Gulf side of the island and locations were recorded with a
handheld GPS unit (Garmin Etrex; Garmin Ltd, 2007). I conducted point sampling
surveys from sunrise until heat shimmer limited the ability to identify raptors to species at
a distance. At each point, I scanned the surrounding area for 10 minutes before moving
on to the next point.
11
During all surveys, I considered an area occupied if I observed individuals or
pairs engaged in breeding behavior (i.e. territorial or courtship displays, nest building).
Upon determining an area was occupied, I observed pairs to try to identify nest sites and
then conducted nest searches. In addition, I checked all accessible known nest areas from
previous years. I attempted to visit all occupied territories twice a month to monitor
breeding status. I recorded the location of all nests with a handheld GPS unit, and
returned approximately every 2 weeks to monitor activity. After a clutch had been
initiated, I then considered the territory to have a nesting pair.
I attempted to check nests bimonthly to monitor nesting status. If I observed
normal pair behavior (i.e. soaring over nest, flushing from nest) I considered the nest as
still active and avoided approaching the nest at this stage to reduce a chance of
abandonment. If I did not observe a pair in the vicinity of the nest, I would approach and
check the nest to verify the status of the nesting attempt. I used a mirror attached to a
pole to examine nest contents to count nestlings and estimate their age according to a
nestling age guide I created in 2006 (Haralson unpublished 2006).
I continued to monitor occupied territories of non-nesting WTHAs, and conduct
surveys for renesting attempts by failed pairs through June in 2006 and July in 2007. In
2006 pairs were less likely to abandon eggs after a nest check. In 2007, I attempted to
approach nests only after eggs had hatched because I detected an increased rate of nest
abandonment in 2007.
12
Analytical methods
Using ArcGIS 9.2, I digitized the surveyed portion of the islands from 2004
National Agricultural Imagery Program (NAIP) mosaics. This encompassed all of
Matagorda and Mustang Islands, but only the northern 61 km of North Padre Island.
Once the surveyed areas were digitized as polygons, areas of each polygon were
calculated in the ArcGIS table using Visual Basic code. I divided the surveyed areas into
5 landscape types: beach, tidal flats, uplands (from McAlister and McAlister 1993),
roads, and human impacted areas (i.e. residential, city limits, condominiums, oil drilling
sites). The area of each island was used to calculate the densities of occupied areas on
each island. Upland areas were also used to calculate densities of occupied areas on each
island, presuming this was a more accurate representation of available WTHA nesting
habitat. I determined nearest-neighbor distances for each nesting pair by calculating the
distance to the nearest nesting pair. I calculated nearest-neighbor distance using Hawth’s
Analysis Tools version 3.27 (Beyer 2006) for ArcGIS.
I summarize and report means and standard deviations for all reproductive
parameters, including renest attempts. I used the Mayfield calculation (Mayfield 1975) to
determine nest success for each island. I considered any pair that raised at least one
nestling to 80% of nestling age as a successful pair (Steenhof and Kochert 1982). I
omitted renest attempts from the Mayfield calculations. I compared Mayfield nest
success, observed nest success (proportion of successful nests per all nesting attempts)
and proportion of nesting pairs per total occupied territories between years for each island
using an analysis of a contingency table (Zar 1999). If there was no difference between
13
years for each island I combined the data for each island for the aforementioned
proportions and used a normal Z-test to compare more than two proportions (Zar 1999).
To compare nesting chronology among islands, I estimated the egg laying date
using an average incubation period of 31 days (Farquhar 1992). The estimated age of
nestlings when first observed was back-dated to estimate initiation of incubation
(Steenhof and Newton 2007). Nests which failed during the incubation period were
omitted from analysis of nesting chronology because the age of the egg(s) was unknown.
No known renest attempts were used in determining chronology. Clutch initiation dates
were compared between years for each island using a nonparametric Mann-Whitney U
test.
To make productivity comparisons between human disturbance levels, I pooled
data from the high human disturbance (HHD) portion of North Padre Island with data
from Mustang Island and considered them HHD pairs. Pairs on Matagorda Island were
considered to have low human disturbance (LHD). Within human disturbance levels, I
compared nestling and fledgling productivity of all nesting WTHAs between 2006 and
2007 breeding seasons. Assuming no difference was detected between years, I then
pooled nestling and fledgling productivity between years for comparison among LHD
and HHD. I compared LHD and HHD using a contingency table with a chi-square test to
determine island effects on number of nestlings and number of fledglings produced. All
analyses were completed in Statistica 6.1 (StatSoft, Inc. 2004) using an alpha of 0.05.
This project was conducted under Texas Tech University Animal Care and Use Protocol
06027-05
14
Results
All Islands
Across the study site I identified 41 occupied WTHA territories in 2006 and again
in 2007 (Table 2.1). Not all territories occupied in 2006 were observed in 2007 or vice
versa. However, it is interesting to note that the number of occupied territories stayed the
same between the two years across the study area. Of these 41 occupied territories,
thirty-two pairs initiated a clutch in each year (78%). The number of nesting pairs stayed
constant between the two years even though some of the territories in which pairs nested
in a given year were different. There was no statistical difference between observed nest
success in 2006 (63.6%) and 2007 (40.6%) (Zc = 1.61, 0.25 < P < 0.50). Similarly, the
Mayfield nest success estimates of WTHAs were not significantly different between (Zc =
1.78, 0.25 < P < 0.50) 2006 (55.9%) and 2007 (30.2%). Summarized across the entire
study area, the Mayfield nest success estimate was 41.6% (Table 2.2). Density and
nearest-neighbor distances were relatively similar between the two years (Table 2.1).
The average density of occupied territories across both years and all islands was 0.13
occupied territories per km2 (Table 2.2). Nearest-neighbor distances on Matagorda Island
(1.86 ± 0.87) are nearly half of what was observed on Mustang Island (2.56 ± 0.82) and a
third of what was observed on North Padre Island (5.60 ± 3.78).
Matagorda Island
On Matagorda Island I identified 26 and 27 occupied WTHA territories in 2006
and 2007 respectively (Table 2.3, Figure 2.2). Twenty-two pairs initiated a clutch in each
of 2006 (85%) and in 2007 (81%). Observed nest success of WTHAs on Matagorda
15
Island in 2006 (72.7%) was not statistically significant (Zc = 1.82, 0.25 < P < 0.50) from
2007 (30.4%). Similarly, differences in the Mayfield nest success estimates between
2006 (64.3%) and 2007 (33.1%) were not significantly different (Zc = 1.79, 0.25 < P <
0.50). However, the >30% difference between years in both measures suggests between
year differences may be biologically relevant. Combining 2006 and 2007 data, the
Mayfield nest success estimate for Matagorda Island was 43.9% (Table 2.2). The
average density of occupied territories between 2006 and 2007 on Matagorda was 0.23
pairs per km2 (Table 2.2). There were more nests predated in 2007 (n = 13) than in 2006
(n = 6). The percent of pairs which renested after their first nesting attempt failed on
Matagorda Island was 9.1 % (4 of 44 initial attempts). Only one renest attempt was
successful. All other reproductive parameters from 2006 and 2007 on Matagorda Island
are contrasted in Table 2.3.
Mustang Island
I identified 6 and 7 occupied WTHA territories on Mustang Island in 2006 and
2007 respectively (Table 2.4, Figure 2.3). Of these 5 (83%) and 7 (100%) pairs nested in
2006 and 2007, respectively (Table 2.4). There was no statistical difference in the
proportion of nesting pairs between the two years (Zc = 0.08, P > 0.50). Observed nest
success of WTHAs on Mustang Island in 2006 (80.0%) and 2007 (42.9%) did not differ
(Zc = 0.69, 0.95 < P < 0.975). Similarly, differences in the Mayfield nest success
estimates between 2006 (73.7%) and 2007 (34.9%) were not significantly different (Zc =
0.74, 0.95 < P < 0.975). Similar to Matagorda Island, the almost 40% differences
between years in both measures suggests between year differences may be biologically
16
relevant. Combining 2006 and 2007 data, the Mayfield nest success estimate Mustang
Island was 49.4% (Table 2.2). The average density of occupied WTHA territories in
2006 and 2007 for Mustang Island was 0.16 pairs per km2 (Table 2.2). The number of
nests predated in 2006 (n = 1) was less than in 2007 (n = 4). There were no renest
attempts observed on Mustang Island during the course of this study. All other
reproductive parameters from 2006 and 2007 on Mustang Island are contrasted in Table
2.4.
North Padre Island
I identified 9 and 7 occupied territories in which only 5 (55%) and 3 (43%) pairs
nested in 2006 and 2007 respectively (Table 2.5, Figure 2.4). Only 1 pair was successful
each year. Differences in the observed nest success of WTHAs on North Padre Island in
2006 (16.7%) and 2007 (33.3%) were not statistically significant (Zc = 0.28, 0.975 < P <
0.99). Similarly, the Mayfield nest success estimates between 2006 (14.4%) and 2007
(23.7%) did not differ (Zc = 0.67, 0.95 < P < 0.975). Combining 2006 and 2007 data, the
Mayfield nest success estimates for North Padre Island was 18.2%. The average density
of occupied territories in 2006 and 2007 was 0.05 pairs per km2. The proportion of pairs
which renested after their first failed nesting attempt was 8.3% (1 of 12 initial attempts)
on North Padre Island. All other reproductive parameters from 2006 and 2007 on North
Padre Island are contrasted in Table 2.5.
Occupancy and Nest Success
Combining 2006 and 2007 data, I compared observed nest success, Mayfield nest
success estimates, and proportion of nesting pairs from occupied territories between
17
Matagorda, Mustang and North Padre Islands. Although observed nest success on North
Padre Island (22.2%) was lower than Matagorda (56.8%) and Mustang (58.3%) Islands
there was no significant difference found (χ2 = 3.80, 0.25 < P < 0.10). Likewise, the
Mayfield nest success estimate on North Padre Island (18.2%) was lower than Matagorda
(43.9%) and Mustang (49.4%) Islands; however no significant difference was found (χ2 =
1.95, 0.90 < P < 0.95). Conversely, the percent of nesting pairs per occupied territories
did differ between islands (χ2 = 3.80, 0.005 < P < 0.01). A post-hoc analogous to the
Tukey’s test (Zar 1999) depicted a significant difference between Matagorda and North
Padre Islands (q = 4.65, 0.001 < P < 0.005), but no significant difference between
Mustang and Matagorda Islands (q = 0.73, P > 0.50) or Mustang and North Padre Islands
(q = 2.74, 0.01 < P < 0.02).
Chronology
Egg laying for breeding WTHAs on the barrier islands began around the 1st of
March (Figure 2.1). Pairs initiated clutches earlier on Matagorda Island in 2006 (x̄ =
March 27 ± 17.1) than in 2007 (x̄ = April 3 ± 22.9) though initiation dates were not
significantly different (U = 118.50, P = 0.340). Mustang Island pairs initiated clutches
later (U = 0.00, P = 0.034) in 2006 (x̄ = March 11 ± 3.8) than in 2007 (x̄ = March 19 ±
3.7). Sample size on North Padre Island was too small to test. Mean earliest clutch
initiation for all islands was March 3 (± 3.2). Matagorda Island has an extended period of
clutch initiation (x̄ = March 30 ± 20.0) compared to Mustang (x̄ = March 15 ± 5.1) and
North Padre Islands (x̄ = March 23 ± 15.9) (Figure 2.1); however this may be the
inclusion of renest attempts if early nest failures were missed.
18
Productivity
Data were analyzed by comparing total nestlings or fledglings per all nesting
pairs. Number of nestlings produced by WTHAs in LHD in 2006 (x̄ = 1.35 ± 0.81) was
nearly two times the productivity observed in 2007 (x̄ = 0.77 ± 0.92). However there was
no difference observed between the frequency distribution of the number of nestlings
produced (χ2(0.05, 3) = 5.31, 0.05 < P < 0.10) between 2006 and 2007. Similarly, fledgling
production in 2006 (x̄ = 1.14 ± 0.83) appeared to be substantively greater than in 2007 (x̄
= 0.64 ± 0.85), but there was no significant difference in the frequencies of fledglings
produced (χ2(0.05, 3) = 4.10, 0.10 < P < 0.25). Similarly, nestling production in HHD in
2006 (x̄ = 1.25 ± 1.26) appeared lower than that in 2007 (x̄ = 0.86 ± 1.26). The frequency
comparison of nestlings produced showed no significant difference between 2006 and
2007(χ2(0.05, 4) = 3.42, 0.25 < P < 0.50). Again the number of fledglings produced in 2006
(x̄ = 1.40 ± 1.14) was numerically greater than in 2007 (x̄ = 0.86 ± 1.22), but there was no
significant difference in the frequencies of fledglings produced (χ2(0.05, 4) = 1.42, 0.50 < P
< 0.75).
To examine general productivity between two levels of human disturbance, I
pooled data from both years for analysis in the LHD and the HHD. Although the means
did not appear numerically different between LHD (x̄ = 1.05 ± 0.91) and HHD (x̄ = 1.00
± 1.83) there was a significant difference in the frequency of nestlings produced between
LHD and HHD (χ2(0.05, 4) = 9.98, 0.01 < P < 0.025) (Table 2.6). Similarly, the mean
fledglings produced appeared to have no numerical difference (LDH x̄ = 0.89 ± 0.87;
19
HHD x̄ = 1.08 ± 1.16), but the frequency of fledglings produced was significantly
different (χ2(0.05, 4) = 9.15, 0.025 < P < 0.05) between the two areas (Table 2.7).
Discussion
Density
There are many factors contributing to variation in productivity of birds: breeding
density, time of season, predation, parental age, availability of food, competition, and
nest-site quality (Alatalo and Lundberg 1984). In this study Matagorda Island had the
highest density of WTHAs territories ever recorded in south Texas (0.22-0.23 pairs/km2).
In comparison, earlier studies conducted on the mainland recorded between 0.18 – 0.21
pairs/km2 at the Attwater National Wildlife Refuge (Farquhar 1986), and in 2 adjacent
pastures in Kleberg County, densities were estimated at 0.17 and 0.11 pairs/km2 (Kopeny
1988). Territory density on Mustang Island (0.15-0.17 pairs/km2) was comparable to
densities observed in previous studies (Farquhar 1986, Kopeny 1988). WTHAs on
Matagorda Island may be at their carrying capacity for the island, if optimal and
suboptimal areas are being used, this may result in decreased measures of WTHA
productivity on the island. The nearest-neighbor distances on Matagorda Island are the
lowest observed across the study site. In territorial birds, such as the WTHA, high
densities can result in a negative effect on reproductive success (Alatalo and Lundberg
1984). Pairs may spend more time defending their territory than tending to their young.
Given that a complete census within the study area on North Padre Island was not
conducted, densities from North Padre Island are not comparable.
20
Chronology
Although clutch initiation dates on Matagorda Island were not statistically
different between years, clutch initiation occurred approximately a week earlier in 2006
than in 2007. In contrast, on Mustang Island pairs initiated clutches later in 2006 than in
2007. The differences between these islands were unexpected but could be explained by
rainfall and the occurrence of prescribed burns.
The early half of 2006 was extremely dry, leaving much of southeast Texas in
drought conditions. As a result of this drought, on Matagorda Island there were very few
prescribed burns conducted in February and early March, during the WTHA nest building
and courtship period (Farquhar 1992). However, mid-2006 and continuing into early
2007 rainfall had increased across much of southeast Texas, allowing more prescribed
burns to be conducted on Matagorda Island. The average rainfall for Corpus Christi, TX
from January to August in 2006 was 7.1 cm compared to 11.6 cm during the same period
in 2007 (National Weather Service 2007). The dry spring of 2006 may have caused
WTHAs to delay clutch initiation until later when the female would potentially be in
better condition. The ample rainfall in 2007 may have increased prey which resulted in
female WTHAs being in better condition to initiate clutches earlier and therefore pairs
nested earlier. Many avian species have shown correlation between rainfall and annual
productivity (Rotenberry and Wiens 1991, Morrison et al. 2007). However, prescribed
burns occurred across some areas of Matagorda Island during the nest building period of
WTHAs, which could have disturbed if not burned nests. This could have caused pairs to
rebuild and delayed clutch initiation on Matagorda Island in 2007. In contrast, Mustang
21
Island received no prescribed burns or wildfires, allowing WTHAs to continue with the
initiation of clutches.
Occupancy and Nest Success
The observed difference between proportions of nesting pairs per occupied
territory between the 3 islands in our study should be viewed with caution. Due to
limited roads and minimal infrastructure within the Padre Island National Seashore, the
survey methods on North Padre Island were not consistent within the island or with the
methods used for Matagorda and Mustang Islands. I feel that a complete census was
conducted on Matagorda and Mustang Islands, due to adequate access. In addition the
interiors of those islands do not have as many inland dunes, allowing further visibility.
However; this was not the case for North Padre Island. The small sample size from
North Padre Island may be biased due to these logistic limitations, and that may not be
representative of the true population of breeding WTHAs on North Padre Island. More
research should be conducted focusing on the population of WTHAs on North Padre
Island to gain a better understanding of that population.
There was no difference in Mayfield or observed nest success or the proportion of
nesting pairs among islands. This suggests that WTHA pairs and productivity was
relatively stable on these islands during this two year period. Matagorda Island had
higher occupied territory density than Mustang Island. High densities in territorial birds
such as the WTHA can result in a negative effect of productivity (Alatalo and Lundberg
1984). Decreases in a birds territory size resulting from high breeding population density
has been shown to explain some variation in avian reproductive success (Both and Visser
22
2000). The mechanism that causes reduced reproductive success may be the intensified
competition for some limiting resource, usually food which can decrease reproduction in
a territory (Newton 1980). However, these potential factors did not appear to influence
nest success on Matagorda Island as there was no difference between it and Mustang
Island.
The Mayfield and observed nest success on Mustang Island were similar to those
reported on the mainland of Texas (Actkinson 2005, Kopeny 1988). However, Farquhar
(1986) observed high nest success rates (100%) in two of his three years of study. This
may be due to lower predation because of intensive predator control on the Attwater
National Wildlife Refuge. Low nest success of WTHAs is reported to be influenced by
egg and nestling predation, or caused by abandonment of eggs due to disturbances near
nest sites (Stevenson and Meitzen 1946). Shrubs or stunted trees were often the only
nesting substrate available on the islands. WTHA nest locations were often placed near
the apex of low shrubs, as low as 1 m and up to 5 m tall. Such placement may lead to
high predation rates due to the nests being easily accessible for mammalian predators or
visible to avian predators. Most WTHA nests located on North Padre Island were
predated in 2006 and 2007. In addition, individual pairs were extremely sensitive to
disturbances, which resulted in two nest abandonments on Matagorda Island and one on
Mustang Island.
Productivity
The comparison and contrast of productivity among populations offers a
meaningful benchmark for analyzing the status of avian populations (Newton 1998).
23
Furthermore, comparing productivity and nesting success within and among populations
provides insight into the factors that affect reproduction, such as predation, weather,
human disturbance and breeding densities.
Numerically, LHD nests produced fewer fledglings in 2007 than in 2006
primarily due to a higher predation rate in 2007. Predation rates could have been
influenced by the lack of rainfall which resulted in a difference in the burn regime
between 2006 and 2007. A combination of these factors may have influenced the nest
success on the LHD area in 2007. Although no prescribed burns were conducted on the
HHD area, a similar trend in lower nestling production in 2007 versus 2006 still
persisted. Comparing the frequency distribution of productivity between the HHD and
LHD areas showed a significant difference in both nestling and fledgling production.
This further supports the possibility of the LHD area being influenced by density
dependent factors, as populations breeding close to saturation often have lower
productivity (Alatalo and Lundberg 1984, Both and Visser 2000). Therefore, this data
may not infer that high levels of human influence results in high WTHA productivity, but
perhaps there may be more resources available due to lower densities which then result in
a higher productivity.
The successful pairs on Matagorda Island did not only nest in natural available
substrate, but on artificial nesting platforms as well. Matagorda Island has several
artificial nesting platforms provided for the experimental population of Aplomado falcons
(Falco femoralis). WTHAs used one such nesting platform in 2006 and 2007 and
successfully produced young each year. This is the only WTHA territory in which the
24
pair used an artificial nesting platform on Matagorda Island; most other platforms on
Matagorda Island were occupied by breeding Aplomado falcons. This is the first
recorded WTHA nest on an artificial platform and suggests that artificial nest platforms
are acceptable by breeding WTHAs when natural nest sites are limiting. Other raptors
have been known to use artificial nest platforms, which increased their nesting density
and distributions in areas where natural sites were lacking (Newton 1998).
With an increased breeding density, sub-adult birds may opt for residing within
the same territory of a breeding pair, potentially assisting that pair, due to lack of
sufficient area for the young birds to take up residence. One such observation consisted
of two adult plumaged WTHAs and one sub-adult (Basic II) plumaged bird in 2007 (B.
Clark pers. comm.). This territory was not known to have a nesting pair in 2006. The
sub-adult was once observed attempting to incubate the clutch; however the female came
in to the nest and, with no aggression towards the sub-adult, moved to brood the eggs.
The sub-adult was also observed pirating food from the adult male. The nestlings were
depredated, and the pair attempted to renest, and the sub-adult was observed in the area
of the new nest as well. A similar situation has been observed in WTHAs on one
occasion in Venezuela, where the immature bird resided in its natal territory the
following year and a half (Madar 1981).
Other interesting observations include the number of actual breeding sub-adult
WTHAs. One pair of WTHAs consisting of two sub-adult plumaged individuals on
Matagorda Island successfully fledged two young in 2007. When they initiated their
clutch, the pair was in Basic II and Basic III according to B. Clark (pers. comm.). The
25
same year on North Padre Island in Corpus Christi a pair consisting of a typical adult
plumaged male and a female with a dark throat successfully fledged two young as well.
Kopeny (1988) had observed a sub-adult male breeding with an adult plumaged female.
Usually WTHAs breed on their third year (Farquhar 1986). Birds in immature plumage
are capable of breeding but typically do not do so because territory gaps are usually filled
by older birds (Newton 1979). An increase in breeding sub-adult plumaged birds can
signify an increase in adult mortality (Newton 1979, Steenhof et al. 1983), or an increase
in the availability of a resource such as nest sites or food supply, when a population is
increasing (Newton 1976).
Management Implications
WTHAs in the LHD area have a lower frequency of fledglings produced than
pairs nesting in HHD areas. This may be an artifact of this study or density dependence
factors influencing WTHA nest success on Matagorda Island (LHD). Productivity of
nests in HHD areas is higher despite having a high level of human influence. This may
be a result of WTHAs adapting to human disturbance and breeding pairs having larger
territories; whereas in the LHD area pairs may be influenced by density-dependence
factors where WTHAs may be at population saturation. Nesting pairs of WTHAs on
Matagorda Island should be examined to determine the indirect effect of the timing of
prescribed burns on breeding success. On North Padre Island more research should be
conducted to determine if and what the limiting factors are for that island. Artificial nest
platforms have been used by WTHAs and should be looked at as a potential tool to
increase breeding densities where the limiting factor is nesting substrate.
26
Literature Cited
Alatalo, R. V., and A. Lundberg. 1984. Density-dependence in breeding success of the
pied flycatcher (Ficedula hypoleuca). Journal of Animal Ecology 53: 969-977.
Actkinson, M. A. 2006. Productivity and nest-site selection of a breeding raptor
community in south Texas. Thesis, Texas A&M University, Kingsville, USA.
Beach, D. 2002. Coastal sprawl: The effects of urban design on aquatic ecosystems in
the United States. Pew Oceans Commission, Arlington, Virginia, USA.
Beyer, H. L. 2006. Hawth’s analysis tools. Version 3.27.
<http://www.spatialecology.com/htools/>. Accessed 10 October 2006.
Bibby, C. J., N. D. Burgess, D. A. Hill, and S. Mustoe. 2000. Bird census techniques.
Second edition. Academic Press, San Diego,California, USA.
Both, C., and M. E. Visser. 2000. Breeding territory size affects fitness: An experiment
study on competition at the individual level. Journal of Animal Ecology 69:
1021-1030.
Buckland, S. T., D. R. Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers, and L.
Thomas. 2001. Introduction to distance sampling: Estimating abundance of
biological populations. Oxford University Press, Oxford, New York, USA.
Crossett, K. M., T. J. Culliton, P. C. Wiley, T. R. Goodspeed. 2004. Population trends
along the coastal United States: 198 0-2008. National Oceanic and Atmospheric
Administration, U.S. Department of Commerce, USA.
27
Farquhar, C. C. 1986. Ecology and breeding behavior of the white-tailed hawk on the
northern Coastal Priaries of Texas. Dissertation, Texas A&M University, College
Station, USA.
Farquhar, C. C. 1992. White-tailed hawk. in A. Poole, P. Stettenheim, and F. Gill,
editors. The Birds of North America, No. 30. Philadelphia: The Academy of
Natural Sciences; Washington, D.C. The American Ornithologists’ Union.
Fowler, J., L. Cohen, and P. Jarvis. 1998. Practical statistics for field biology. Second
edition. John Wiley & Sons Ltd, Chichester, West Sussex, England.
Fuller, M. R., and J. A. Mosher. 1987. Raptor survey techniques. Pages 37-65 in B.A.
Giron Pendleton, B. A. Millsap, K. W. Cline, and D. M. Bird, editors. Raptor
management techniques manual. National Wildlife Federation, Washington D.C.
Handbook of Texas Online. 2007.
<http://www.tsha.utexas.edu/handbook/online/articles/PP/hjp11.html>. Accessed
9 October 2007.
Hobbs, F., and N. Stoops. 2002. Demographic Trends in the 20th Century. U.S. Census
Bureau, Census 2000 Special Reports, Series CENSR-4. U.S. Government
Printing Office. Washington D.C., USA.
Hutto, R. L., S. M. Pletschet, P. Hendricks. 1986. A fixed-radius point count method for
nonbreeding and breeding season use. Auk 103: 593-602.
Jahrsdoerfer, S. E., and D. M. Leslie Jr. 1988. Tamaulipan brushlands of the Lower Rio
Grande Valley of south Texas: description, human impacts, and management
options. U.S. Fish and Wildlife Service, Biological Report 88 (36).
28
Kopeny, M. T. 1988. Effect of thornbrush on distribution and nest site selection of
white-tailed hawks (Buteo albicaudatus) in south Texas. Thesis, North Dakota
State University, Fargo, USA.
Kurki, S., A. Nikula, P. Helle, H. Linden. 2000. Landscape fragmentation and forest
composition effects on grouse breeding success in boreal forests. Ecology 81:
1985-1997.
Lord, J. M., and D. A. Norton. 1990. Scale and spatial concept of fragmentation.
Conservation Biology 4: 197-202.
Madar, W. J. 1981. Notes on nesting raptors in Llanos of Venezuela. Condor 83: 48-51.
Marzluff, J. M. 2001. Worldwide urbanization and its effects on birds. Pages 19-47 in
Marzluff, J. M., R. Bowman, R. Donnelly., editors. Avian conservation and
ecology in an urbanizing world. Kluwer Academic Publishers, Boston,
Massachusetts, USA.
Mayfield, H. F. 1975. Suggestions for calculating nest success. Wilson Bulletin 87:456466.
McAlister, W. H., and M. K. McAlister. 1993. A naturalist’s guide: Matagorda Island.
University of Texas Press, Austin, USA.
Morrison, J. L., M. McMillian, J. Cohen, and D. H. Catlin. 2007. Environmental
correlates of nesting success in red-shouldered hawks. Condor 109: 648-657.
Morrison, M. L. 1978. Breeding characteristics, eggshell thinning, and population trends
of white-tailed hawks in Texas. Texas Ornithological Society Bulletin 11:35-40.
29
National Oceanic and Atmospheric Administration [NOAA]. 2006. Storm data and
unusual weather phenomena.
<http://www.srh.noaa.gov/crp/stories/StormReport/jul06.pdf>. Accessed 30
October 2007.
National Oceanic and Atmospheric Administration [NOAA], and State of Texas Coastal
Coordination Council. 1996. Texas coastal management program: Draft
environmental impact statement. Office of Ocean and Coastal Resource
Management, NOAA, U.S. Department of Commerce, USA.
National Weather Service. 2007. Corpus Christ Climate Archive.
<http://www.srh.noaa.gov/crp/>. Accessed 8 November 2007.
Newton, I. 1976. Breeding of sparrowhawk Accipiter nisus in different environments.
Journal of Animal Ecology 45: 831-849.
Newton, I. 1979. Population ecology of raptors. Buteo Books, Vermillion, South
Dakota, USA.
Newton, I. 1980. The role of food in limiting bird numbers. Ardea, 68: 11-30.
Newton, I. 1998. Population limitation in birds. Academic Press, San Diego, California,
USA.
Pither J., Taylor P. D. 1998. An experimental assessment of landscape connectivity.
Oikos 83:166–74.
Public Use Statistics Office. 2007. 10-157 Reporting: National Park Service.
<http://www2.nature.nps.gov/stats/>. Accessed 2 November 2007.
30
Rappole, J. H., and G. W. Blacklock. 1985. Birds of the Texas coastal bend. Texas
A&M University Press, College Station, USA.
Rotenberry, J. T., and J. A. Wiens. 1991. Weather and reproductive variation in
shrubsteppe sparrows: a hierarchical analysis. Ecology 72: 1325-1335.
StatSoft, Inc. (2004). STATISTICA (data analysis software system), version 6.
www.statsoft.com.
Steenhof, K., and M. N. Kochert. 1982. An evaluation of methods used to estimate
raptor nesting success. Journal of Wildlife Management 46:885-893.
Steenhof, K., M. N. Kochert, and J. H. Doremus. 1983. Nesting of sub-adult golden
eagles in southwestern Idaho. Auk 100: 743-747.
Steenhof, K., and I. Newton. 2007. Assessing raptor nesting success and productivity.
Pages 181-192 in Raptor research and management techniques. D.M. Bird and
K.L. Bildstein, editors. Hancock House Publishers, Blaine, Washington, USA.
Stevenson, J. O., and L. H. Meitzen. 1946. Behavior and food habits of Sennett’s whitetailed hawk in Texas. Wilson Bulletin 58:198-205.
Texas Parks and Wildlife Departement [TPWD]. 1984. Master Plan and Program: 5 year
plan for Matagorda Island State Park and Wildlife Management Area. Draft.
Texas Parks and Wildlife Department, Texas, USA.
Tyler, R., D. E. Barnett, R. R. Barkley, P. C. Anderson, and M. F. Odintz, editors. 1996.
The new handbook of Texas. Texas State Historical Association, Austin, USA.
31
U. S. Fish and Wildlife Service [USFWS]. 2000. Natural resource management
priorities of the U.S. Fish and Wildlife Service along the Texas coast. Draft. U.S.
Fish and Wildlife Service, Houston, Texas, USA.
Weise, B. R., and W. A. White. 1980. Padre Island National Seashore: A guide to the
geology, natural environments, and history of a Texas barrier island. University
of Texas, Austin, USA.
Wiens, J. A. 1989. Spatial Scaling in Ecology. Functional Ecology 3:385-397.
With, K. A, and T. O. Crist. 1995. Critical thresholds in species’ responses to landscape
structure. Ecology 76:2446–59.
Zar, J. H. 1999. Biostatistical analysis. Second edition. Prentice-Hall, Upper Saddle
River, New Jersey, USA.
32
Table 2.1. Descriptive statistics of White-tailed Hawk breeding ecology for Matagorda,
Mustang, and North Padre Islands between 2006 and 2007.
All Islands
2006
(± SD)
2007
(± SD)
Occupied Territories
41
41
Nesting Pairs
32
32
Renest Attempts
2
3
Area of Islands (km2)
493.2
493.2
Density (occupied territory/km2)
0.08
0.08
Upland Area of Islands (km2)
304
304
Upland Area Density (occupied territory/km2)
0.13
0.13
Nearest-Neighbor Distance (km)
2.51 (1.57)
2.39 (2.23)
Mean Clutch Size
1.80 (0.83)
1.50 (0.71)
# Nestlings/All Nest Attempts
1.23 (0.97)
0.78 (0.98)
# Fledglings/All Nest Attempts
1.06 (0.97)
0.69 (0.93)
# Fledglings/Successful Nests
1.67 (0.60)
1.69 (0.58)
Observed Nest Success
63.6%
40.6%
Mayfield Nest Success
55.9%
30.2%
33
Table 2.2. Descriptive statistics of White-tailed Hawk breeding ecology averaged for Matagorda, Mustang, and North Padre Islands
during 2006-2007.
Matagorda
(± SD)
Mustang
(± SD)
North Padre
(± SD)
All Islands
(± SD)
0.23
0.16
0.05
0.13
Upland Area Density
(occupied territory/km2)
Nearest-Neighbor Distance (km)
1.86
(0.87)
2.56
(0.82)
5.60
(3.78)
2.45
(1.92)
Mean Clutch Size
2.03
(0.38)
2.00
(0.53)
1.71
(0.76)
1.98
(0.47)
# Nestlings/All Nests
1.05
(0.91)
1.00
(1.83)
0.78
(1.20)
1.02
(0.99)
# Fledglings/All Nests
0.89
(0.87)
1.08
(1.16)
0.55
(1.13)
0.88
(0.96)
# Fledglings/Successful Nests
1.56
(0.51)
1.86
(0.90)
2.50
(0.71)
1.68
(0.64)
Observed Nest Success
56.8%
58.3%
22.2%
52.3%
Mayfield Nest Success
43.9%
49.4%
18.2%
41.6%
34
Table 2.3. Descriptive statistics of White-tailed Hawk breeding ecology for Matagorda
Island during 2006-2007.
Matagorda Island
a
2006
(± SD)
2007
(± SD)
Occupied Territories
26
27
Nesting Pairs
22
22
Renest Attempts
1
3
Area of Island (km2)
202.7
202.7
Density (occupied territory/km2)
0.13
0.13
Upland Area of Island (km2)
117.1
117.1
Upland Area Density (occupied territory/km2)
0.22
0.23
Nearest-Neighbor Distance (km)
1.97 (0.78) 1.86 (0.99)
Mean Clutch Size
1.95 (0.23) 2.13 (0.50)
# Nestlings/All Nest Attempts
1.35 (0.81) 0.77 (0.92)
# Fledglings/All Nest Attempts
1.14 (0.83) 0.53 (0.85)
# Fledglings/Successful Nests
1.56 (0.51) 1.56 (0.53)
Observed Nest Success
72.7%
40.9%
Mayfield Nest Success
– Represents a significant difference at the 0.1 level
61.5%
29.7%
35
Table 2.4. Descriptive statistics of White-tailed Hawk breeding ecology for Mustang
Island during 2006-2007.
Mustang Island
2006
(± SD)
2007
(± SD)
Occupied Territories
6
7
Nesting Pairs
5
7
Renest Attempts
0
0
Area of Island (km2)
84.9
84.9
Density (occupied territory/km2)
0.07
0.08
Upland Area of Island (km2)
40.9
40.9
Upland Area Density (occupied territory/km2)
0.15
0.17
Nearest-Neighbor Distance (km)
2.76 (0.72) 2.41 (0.92)
Mean Clutch Size
2.25 (0.50) 1.75 (0.50)
# Nestlings/All Nest Attempts
1.25 (1.26) 0.86 (1.26)
# Fledglings/All Nest Attempts
1.40 (1.14) 0.86 (1.22)
# Fledglings/Successful Nests
1.75 (0.96) 2.00 (1.00)
Observed Nest Success
80.0%
42.9%
Mayfield Nest Success
73.7%
34.9%
36
Table 2.5. Descriptive statistics of White-tailed Hawk breeding ecology for North Padre
Island during 2006-2007.
North Padre Island
2006
(± SD)
2007
(± SD)
Occupied Territories
9
7
Nesting Pairs
5
3
Renest Attempts
1
0
Area of Island (km2)
205.6
205.6
Density (occupied territory/km2)
0.04
0.03
Upland Area of Island (km2)
146
146
Upland Area Density (occupied territory/km2)
0.06
0.05
Nearest-Neighbor Distance (km)
4.61 (2.86) 7.24 (5.20)
Mean Clutch Size
1.80 (0.83) 1.50 (0.71)
# Nestlings/All Nest Attempts
0.83 (1.33) 0.67 (1.15)
# Fledglings/All Nest Attempts
0.50 (1.26) 0.67 (1.15)
# Fledglings/Successful Nests
3.00 0.00
2.00 0.00
Observed Nest Success
16.7%
33.3%
Mayfield Nest Success
14.4%
23.7%
37
Table 2.6. The distribution of the number of nestlings produced in Low Human
Disturbance (LHD) nests versus High Human Disturbance (HHD) nests during 20062007.
LHD Nests
HHD Nests
Total
Number of Nestlings
0
1
2
16
8
18
6
3
3
22
11
21
3
0
3
3
Total
42
15
Table 2.7. The distribution of the number of fledglings produced in Low Human
Disturbance (LHD) nests versus High Human Disturbance (HHD) nests during 20062007.
LHD Nests
HHD Nests
Total
0
19
7
26
Number of Fledglings
1
2
11
14
3
3
14
17
38
3
0
3
3
Total
44
16
Figure 2.1. White-tailed Hawk nesting chronology on Matagorda, Mustang, and North Padre Islands in 2006 and 2007.
Estimated nestling age was back-dated to estimate egg laying date. (Matagorda n = 29; Mustang n = 9; North Padre n = 3)
39
Figure 2.2. White-tailed Hawk nest locations on Matagorda Island, Texas, 2006 and 2007.
40
Figure 2.3. White-tailed Hawk nest locations on Mustang Island, Texas, 2006 and 2007.
41
Figure 2.4. White-tailed Hawk nest locations on North Padre Island, Texas, 2006 and
2007.
42
CHAPTER III
NEST SITE SELECTION OF WHITE-TAILED HAWKS ON THE TEXAS
BARRIER ISLANDS.
Abstract
I measured vegetation and landscape characteristics at White-tailed Hawk (Buteo
albicaudatu; WTHA) nest sites and paired random sites on Matagorda, Mustang and
North Padre Islands, Texas, in 2006 and 2007. I create a resource selection probability
function for WTHA nest site selection using a logistic regression model of the
characteristics measured at a subset of 19 nest sites and paired random sites on
Matagorda Island. Models were evaluated using Akaike Information Criterion. The best
model on Matagorda Island used the parameters of shrub category, nearest-neighbor
distance, and distance to road to correctly differentiate 83% of nest sites from random
sites on Matagorda Island, 70% on Mustang Island, and 50% on North Padre Islands. I
then created model sets for Mustang and North Padre Islands, the best model for each of
these islands used the parameters of shrub height, shrub circumference, and their
interaction. The resource selection probability function from the best model on
Matagorda Island should be used with caution in other areas due to inconsistent
predictions of nest sites from random sites. Overall, it appears that the shrub species is
important to WTHA nest site selection.
43
Introduction
The primary threat currently facing wildlife populations in general is the
fragmentation and loss of native landscapes (Wilcove et al. 1998, Wilson 1999). Urban
development is one of the key factors influencing the abundance and distribution of many
native species world-wide (Fernández-Juricic and Jokimäki 2001). Urbanization often
results in decreased habitat availability, reduced patch size, and increased non-native
vegetation (Marzluff 2001). In the history of the United States, the largest human
population increase occurred between the 1990 to 2000 census (Hobbs and Stoops 2002).
Suburbs accounted for most of the urban growth, and coastal counties accounted for half
the U.S. population in 2000 (Hobbs and Stoops 2002). Therefore, the effect of human
population increase and urban development on wildlife within cities and the surrounding
landscape is an area of growing ecological concern (Hadidian et al. 1997, Grimm et al.
2000), especially in coastal areas.
Urban and agricultural development have fragmented and degraded much of
coastal Texas, posing serious threats to this region’s biological health (The Nature
Conservancy 2002). Human population growth along the Texas coast increased 52%
between 1980 through 2003, and it is estimated that the population will reach 7.7 million
by 2008 (Crossett et al. 2004). In addition to the rapid population growth, 95% of coastal
grasslands had been altered by agricultural and urban development by 1988 (Jahrsdoerfer
and Leslie 1988). Coincidentally, coastal Texas is also one of the most biologically
diverse areas of the state (Rappole and Blacklock 1985, NOAA 1996); the variety of bird
species found in coastal Texas alone is among the greatest anywhere in the U.S. (Rappole
44
and Blacklock 1985, The Nature Conservancy 2002). This is of concern for conservation
of avian species in general. Bird communities are often most susceptible to habitat loss
and fragmentation, but few studies have compared the impacts of habitat degradation and
loss across a gradient (Marzluff 2001).
At the northern extent of its range in southern Texas, the White-tailed Hawk
(Buteo albicaudatus, WTHA) remains one of the least studied raptors occurring in North
America (Farquhar 1992). In Texas, where it is listed as a threatened species, it is a
resident on the coastal grasslands and adjacent inland savannahs (Kopeny 1988, Farquhar
1992). Stevenson and Meitzen (1946) observed breeding WTHAs have little tolerance
for human disturbance near their nest (Stevenson and Meitzen 1946). Thus, loss of
coastal grasslands (Jahrsdoerfer and Leslie 1988) and increases in human presence
(Crossett et al. 2004) present, is of potential management concern. As demands on
coastal resources increase due to tourism, petrochemical, agricultural, and urban
development, wildlife managers will be faced with ensuring a suitable environment for
the WTHA.
Previous research on WTHA nesting habitat has been conducted on the mainland
of Texas on large tracts of private ranch land or on the Attwater Prairie Chicken National
Wildlife Refuge (Farquhar 1986, Kopeny 1988, Actkinson 2006) were human access and
presence is largely regulated. Scattered thorny shrubs and stunted trees are typical nest
sites of WTHAs in Texas (Farquhar 1986, Kopeny 1988, Actkinson 2006). On average,
WTHAs nest on lower substrates relative to other Buteonine hawks (Actkinson 2006).
However, this may be a factor of shrubs and stunted trees being the only available nesting
45
sites (Stevenson and Meitzen 1946). Unfortunately, there are no data available
describing the importance of landscape and nest site characteristics for WTHAs on the
Texas barrier islands which, with few exceptions, are subject to human development and
extensive recreational activities.
Understanding vegetation and landscape characteristics that increase the
probability of an area being selected by nesting WTHAs would facilitate development of
sound conservation and management strategies for the species. The objectives of this
study were threefold. The first objective was to model WTHA nesting habitat selection
in a continuous landscape with low human impact. The second objective was to use the
best model to develop a resource selection probability functions (RSPF; Manly et al.
2002). The first and second objectives were based on the assumption that WTHA
resource selection would be most natural in settings least impacted by human activities.
Once resource selection from a relatively undisturbed setting was obtained and a RSPF
developed, the third objective was to test the RSPF across three islands with varying
levels of human impact. This would facilitate a better understanding of how breeding
WTHAs utilize areas with different land use pressures.
Study Area
This study was conducted on Matagorda, Mustang, and North Padre Islands along
the Texas coast. Structurally, these long and narrow barrier islands are similar in having
rows of dunes along the Gulf side which are constantly being formed and moved by the
wind (Weise and White 1980, McAlister and McAlister 1993). Some dunes are held in
place by vegetation and form a ridgeline of dunes parallel to the beach. More sand may
46
be blown inward, creating additional dunes further inland (Weise and White 1980).
Behind the dunes, the islands are primarily flat with little topography. Vegetation on the
Texas barrier islands is simple when compared with vegetation communities found on the
mainland (Rappole and Blacklock 1985, McAlister and McAlister 1993). This is
predominantly due to salinity levels, proximity to the Gulf of Mexico, the moving sand
dunes, and the sometimes harsh weather to which the islands are exposed (Jahrsdoerfer
and Leslie 1988). Ground cover across the upland areas is typically a matrix of sedges,
grasses, and forbs interspersed with various shrub species. Both the vegetation and
climate on the barrier islands is greatly influenced by the Gulf of Mexico (Texas Parks &
Wildlife Department 1984).
Matagorda Island was the northern most island of this study area and was located
in Calhoun County, Texas. Calhoun County has a mild climate and received about 101
cm of precipitation annually (Handbook of Texas Online 2007). The island was
approximately 61 km long with an area of 202 km2 (McAlister and McAlister 1993).
Historically, the island was primarily used for ranching and later as a bombing range for a
military air base (Texas Parks and Wildlife Department 1984, McAlister and McAlister
1993). In 1982 the U.S. Air Force transferred the northern 45 km of the Island (77 km2 ),
to the U.S. Fish and Wildlife Service (USFWS) for “wildlife conservation purposes” and
permanent inclusion in the National Wildlife Refuge System. State lands, released by the
Air Force in 1979, comprising 106 km2 of adjoining salt marshes and Gulf beach, were
placed under the supervision of the Texas Parks and Wildlife Department (TPWD) under
lease from the Texas General Land Office (GLO). In 1988 the USFWS acquired fee title
47
of the privately held lower third portion of Matagorda Island (47 km2). In 1989, the
USFWS, TPWD and GLO conceptually agreed to a partnership arrangement for
management of the entire Island. Currently, TPWD is responsible for public use and the
USFWS is responsible for wildlife and habitat management (F. Prieto, Aransas National
Wildlife Refuge, pers. comm.). The name for this all-inclusive entity is known as
Matagorda Island National Wildlife Refuge and State Natural Area (F. Prieto, Aransas
National Wildlife Refuge, pers. comm.).
Matagorda Island was divided into management units which were burned on a 3-5
year rotation (F. Prieto, Aransas National Wildlife Refuge, pers. comm.). Although
Matagorda Island was open to the public, access was difficult as there was no vehicular
access to the island. This makes Matagorda Island unique among the barrier islands in
this study. Although there was no public vehicle access to the island, there was one road
which ran the length of the island and was used by USFWS, TPWD and petroleum
exploration vehicles. With exception of the sand dunes, Matagorda was flat to gently
rolling (Texas Parks and Wildlife Department 1984, McAlister and McAlister 1993).
The vegetation on the island appeared to grow in bands parallel to the shoreline with
varying degrees of tolerance to salt (McAlister and McAlister 1993). Shrubs found on
Matagorda Island were yaupon holly (Ilex vomitoria), honey mesquite (Prosopis
glandulosa torreyana), Mexican persimmon (Diospyros texana), huisache (Acacia
farnesiana), and baccharis (Baccharis spp.) (McAlister and McAlister 1993). For this
study, I consider Matagorda Island as having low human impact across the whole island.
48
Mustang Island was approximately 29 km long (Tyler et al. 1996) and 85 km2,
located in Nueces County, Texas. The climate was considered humid sub-tropical for
Nueces County and received approximately 76 cm of precipitation annually (Handbook
of Texas Online 2007). Except for the sand dunes, Mustang Island was primarily flat to
gently rolling. The city of Port Aransas was located on the north end of the island and
connected to the mainland by a ferry (Tyler et al. 1996). The population of Port Aransas
was over 3,000 in 2000 (Handbook of Texas Online 2007). The beach side of Mustang
Island was progressively being converted to resorts and condominiums, whereas the bay
side of the island was undergoing residential development on a lesser scale (i.e. houses,
pastures). Mustang Island was primarily private property except for the 1.2 km2 Mustang
Island State Park near the south end of the island (Tyler et al. 1996). The south end of
Mustang Island was connected to North Padre Island by a causeway (Weise and White
1980). During peak tourism, the human population on the island can swell to over 20,000
(Tyler et al. 1996). Primary shrub species observed on this island were black mangrove
(Avicennia germinans), yaupon holly, honey mesquite, and baccharris. For purposes of
this study, I categorized Mustang Island as highly human impacted.
At over 160 km long, Padre Island was the longest sand-barrier island in the U.S.,
extending southward from Corpus Christi nearly to Mexico. It was located in Cameron,
Nueces, Kenedy, Kleberg, and Willacy Counties. These counties received between 66
and 76 cm of annual rainfall (Handbook of Texas Online 2007). Port Mansfield Channel
divided the island and was maintained to provide shipping access to the Gulf Intracoastal
Waterway (Weise and White 1980, Tyler et al. 1996). Due to the length of Padre Island
49
this study was limited to the northern 61 km of North Padre Island, resulting in 205 km2
surveyed.
North Padre Island was privately owned for approximately the first 32 km at the
north end, where the main uses were residential and recreational development (Tyler et
al. 1996). The remaining 109 km of the island was managed by the National Park
Service (NPS) as the Padre Island National Seashore. In 2006, the seashore attracted
732,794 visitors (Public Use Statistics Office 2007). North Padre Island was connected
to both the mainland and Mustang Island by causeways (Weise and White 1980). North
Padre Island fluctuates from 0.8 km wide to 6.4 km in width. The inner island varied
from flat and primarily tidal flats to tall inner dune ridges scattered across the island with
bayside dune ridges. Shrub species observed on North Padre Island were wax-myrtle
(Myrica pusilla), black willow (Salix nigra), honey mesquite, and huisache (Acacia
farnesiana). For purposes of this study, I considered the north end of North Padre Island
as highly impacted by human activities, but diminishing to low human influence near
Port Mansfield Channel on the south end of the island.
Methods
Field methods
I conducted road surveys for WTHAs on Matagorda, Mustang and North Padre
Islands and point sampling from dune ridges on the beach side of the island on Padre
Island Nation Seashore. Road surveys consisted of driving and scanning for soaring or
perched WTHAs (Fuller and Mosher 1987, Bibby et al. 2000). Roads provide easy
access and large areas of land to be surveyed efficiently, however not all areas across the
50
study site may have roads (Fuller and Mosher 1987), limiting the usefulness of this
survey method. In addition, detectability of a species is greatly influenced by the
surrounding landscape (Fuller and Mosher 1987). However, road surveys are especially
useful for soaring raptors and in areas of open habitat (Fuller and Mosher 1987, Bibby et
al. 2000), making them well suited for a survey method of WTHAs on the coastal
grasslands.
Since vehicle access was from beach side only, and the inability to see past the
dune ridge from the beach, I conducted point sampling from the dune ridge on Padre
Island National Seashore (Buckland et al 2001). Discrepancies occur when trying to
estimate abundances of rare species using point sampling (Hutto et al. 1986), therefore I
did not attempt to calculate WTHA abundances. Points were spaced 3.2 km apart along
the Gulf side of the island and locations were recorded with a handheld GPS unit
(Garmin Etrex; Garmin Ltd, 2007). I conducted point sampling surveys from sunrise
until heat shimmer limited the ability to identify raptors to species at a distance. At each
point, I scanned the surrounding area for 10 minutes before moving on to the next point.
I considered an area occupied if I observed WTHAs that appeared to be paired or
individuals engaged in breeding behavior (i.e. territorial defense, nest building) (Steenhof
and Newton 2007). Upon determining an area was occupied, I observed pairs to try to
identify nest sites and then conducted nest searches. In addition, I checked all accessible
known nest areas from previous years. I recorded the location of all nests with a
handheld GPS unit, and returned approximately every 2 weeks to monitor breeding
51
status. After a clutch had been initiated, I then considered the territory to have a nesting
pair.
To characterize nesting habitat I conducted vegetation measurements at nest sites
and at paired random sites. The paired random sites were selected by choosing a random
distance between 120 – 400 m from the nest in a random direction. I used a maximum
distance of 400 m, which was almost half of the shortest nearest-neighbor distance, to
ensure that the random site was within the same territory. The nearest available shrub
from the random point was selected, assuming it could support a nest. If there was no
available shrub within visibility of the random point I would try a different random
bearing or halve the random distance if it was still greater than 120 m. If no shrub was
available then the nest site was dropped from the analysis; this occurred only once. Nest
and random site locations were recorded using a handheld GPS unit. I measured nest
substrate or random point substrate height and circumference, nest height at nest sites,
and recorded shrub species. I recorded percent ground cover at four 1 m2 plots, one in
each cardinal direction at random distances, within a 0.04 ha area centered on the nest or
random shrub. Ground cover categories were grass, forb, bare ground, litter, and water.
In order to gain an understanding of the ground cover at a larger scale, I also conducted
four 60 m point intercept transects in each of the four cardinal directions, categorizing
ground cover as bare ground, vegetation, wetland, water, tidal flat, low prostrate shrub,
upright shrub, and other. Ground cover was recorded to the nearest centimeter at a broad
scale. I collected shrub height, species, and circumference at all accessible nest sites;
however, plots and transects were only measured on a subset of randomly selected nests
52
on Matagorda Island. To minimize disturbance to the hawks, I postponed conducting
these measurements until at least three weeks after the young had fledged or the nesting
attempt had failed.
In addition to on the ground measurements, I used ArcGIS 9.2 (ESRI 2006) to
measure distance from the nest or random point to the nearest maintained road.
Maintained roads varied among islands, but consisted of any maintained dirt or paved
road. Since beaches were open to public vehicle traffic on Mustang and North Padre
Island, I included them in distance to road measurements. I also calculated nearestneighbor distance using Hawth’s Analysis Tools version 3.27 (Beyer 2006) for ArcGIS,
for each nest site and the paired random site to the nearest neighboring active nest.
Analytical Methods
I used 6 variables for each nest site to assess habitat selection. I selected the
variables based on previous research conducted on the mainland (Farquhar 1986, Kopeny
1988, Actkinson 2006) and my observations in the field. Variables were: shrub height
(HT), shrub circumference (CIRC), their interaction (HT*CIRC), nearest-neighbor
distance (NND), distance to road (DISTRd), and shrub species (ShCAT). I classified
ShCAT as a categorical variable in which I grouped the shrub species in to four
categories based on structural characteristics. These categories were: densely branched
and thorned substrate (DT), openly branched and thorned substrate (OT), densely
branched substrate (D), and openly branched substrate (O). I used these variables to
construct 10 a priori models and a global model which incorporated all 6 variables in the
model set.
53
Since Matagorda Island has low human impact and no direct connection to the
mainland, I used the WTHA population on Matagorda Island as the reference population.
To build the model set, I took a random subset (n = 19) of nests and paired random points
from the sample (n = 28) on Matagorda Island. I conducted a logistic regression with
nest site or random site as the dependent variable criteria. Logistic regression was
appropriate because of its robustness to heteroscedasticity and no assumptions of
normality. I used reference cell coding for ShCAT, with DT as the reference cell or
control in order to compare the use of the more exposed nest shrubs (Hosmer and
Lemeshow 2000). I calculated second order Akaike Information Criterion (AICc) values
to alleviate small sample size bias. In addition I calculated differences between AICc
values of all models and the lowest scoring model (Δi), and Akaike weights (ωi) for each
model (Burnham and Anderson 2002). From the best model in this set I created an RSPF
using the estimated coefficients for that model. I tested the accuracy of the RSPF against
the remaining data from Matagorda Island, and then tested it on data from Mustang and
North Padre Islands.
Finally, using the same methods, I built a model set for Mustang and North Padre
Islands to compare important characteristics across all three islands. For each island
model set, I calculated a 95% confidence interval by summing the Akaike weights for the
top ranked models until this sum was > 0.95 (Burnham and Anderson 2002). This gave a
criterion to measure model importance. All analyses were done using Minitab15.1
software (Minitab Inc. State College, Pennsylvania).
54
Post-hoc Analysis
These data were omitted from the models due to observations made in the field. I
felt, after seeing the dense vegetated ground cover across the upland portion of the island,
that ground cover was not an important characteristic to nesting WTHAs on the barrier
islands. However, this scale needed to be addressed due to the observed importance of
ground cover to nesting WTHAs on the mainland (Farquhar 1986). I averaged the
proportions of each cover type for the four plots and four transects at each site. I omitted
data from 2006 due to the drastic amounts of rainfall (June = 28.4 cm at Corpus Christi;
July = 34.2 cm at Aransas National Wildlife Refuge) that resulted in substantial changes
in ground cover between the fledging period and the date vegetation collection took place
(National Weather Service 2006, National Weather Service and NOAA 2007). Pooling
the remaining data across all islands, I used an ANOVA, to test for any differences of
cover types at nest sites versus random sites both at the 0.04 ha and the 1.1 ha scale.
In order be comparable to other WTHA nest site selection studies, I pooled 2006
and 2007 data within each island. I then conducted an ANOVA to determine differences
between nest and random sites using mean shrub height, shrub circumference, nearestneighbor distance, and distance to road. I also compared the use of nest shrub species to
that which was observed at random sites on Matagorda Island using similar methods of
Neu et al. (1974). For a contingency table analysis, I used Macartney rose, yaupon,
honey mesquite, and baccharis, and pooled all other species into an ‘other’ category.
Samples sizes on Mustang and North Padre Islands were insufficient for statistical
analysis, but I qualitatively compared shrub species use and composition among the
55
islands. Pooling data from each island, I used contingency tests to examine use versus
availability of shrub based on the previously determined shrub categories (ShCAT).
Results
The Hosmer-Lemeshow test indicated that the global model was a good fit for the
Matagorda Island data (χ2 = 1.516, P = 0.992). However, the global model had only
0.1% of the Akaike weight (Table 3.1). The best model for Matagorda Island included
NND, DISTRd, and ShCAT with an Akaike weight of 0.393 (Table 3.1). The second
ranked model was DISTRd and ShCAT which also had a high Akaike weight (0.315), but
included only two of the three variables from the best model (Table 3.1). The odds ratios
for the shrub category parameter (ShCAT) in the best model showed that WTHAs were
less likely to choose shrubs which were OT, O, and D when compared to the reference
variable DT (Table 3.2). Therefore WTHAs are more likely to use densely branched and
thorned shrubs.
Using the estimated coefficients of the parameters for the best model, the RSPF
correctly identified nest sites from random sites 83% of the time, with data which was not
used to build the model from Matagorda Island. When tested on data from Mustang
Island and North Padre Island, the RSPF correctly distinguished nest sites from random
sites 70% and 50% of the time, respectively.
The best logistic regression model for Mustang Island consisted of all shrub
specific measurements (HT + CIRC + HT*CIRC; ωi = 0.714, Table 3.3). The HosmerLemeshow test indicated that the global model for Mustang Island data was a good fit (χ2
56
= 5.33, P = 0.721). In contrast, the best model created from the Matagorda Island subset
ranked third among the Mustang Island model set (ωi = 0.07, Table 3.3).
Similar to Mustang Island, the best model for North Padre Island consisted of all
shrub specific measurements (HT + CIRC + HT*CIRC; ωi = 0.694, Table 3.4). North
Padre Island had one nest omitted from the data set due to lack of available random point.
This was a nest located in huisache, which was not observed at any other data point.
However, not all models ran using North Padre Island data, including the global model,
possibly due to the following reasons; an over-fitted model, the response variables are
nearly all the same, or separation is present with one factor completely describing the
response variable. However, the best model created from the Matagorda Island subset
ranked seventh with 0.1% of the Akaike weight in the model set from North Padre Island
(Table 3.4).
Post-Hoc Results
Ground cover characteristics, did not differ between nest sites and random sites
within the 0.04 ha nest site scale (F6, 19 = 1.90, P = 0.133), or at the larger scale of 1.1 ha
(F8, 14 = 0.74, P = 0.654). Shrub height, shrub circumference, nearest-neighbor distance,
and distance to road for nest sites on each island, differed among islands (F8,64 = 3.87, P
= 0.001). Tukey HSD post-hoc tests indicated nearest-neighbor distance was closer on
Matagorda than on North Padre Island (P = 0.004). In addition, nests were closer to
roads on Mustang Island than on and North Padre Island (P = 0.029; Table 3.5).
Measures of shrub height, shrub circumference, nearest-neighbor distance, and distance
57
to road for nest sites did not differ from random sites on Matagorda (Table 3.6), Mustang
(Table 3.7), and North Padre (Table 3.8) Islands.
White-tailed Hawks did not select nest substrates proportional to availability on
Matagorda Island on basis of shrub category (χ23 = 242.6, P < 0.0001) or species (χ24 =
195.9, P < 0.0001). White-tailed Hawks nested most frequently in densely branched and
thorned (47%) and densely branched (36%) categories, which totaled only 8% of the
random shrub categories (Table 3.9). When nest and random plots are pooled for all
three islands, the pattern of non-random selection of shrub categories held (χ23 = 223.1, P
< 0.0001); WTHA on barrier islands appeared to prefentially nest in DT (37%) and D
(42%) compared to 3% and 10% availability, respectively (Table 3.10). Including all
nests sites used by WTHAs, on a species basis the most commonly used nest shrub
species on Matagorda Island was yaupon (45%), followed closely by Macartney rose
(35%). On Mustang Island yaupon (50%) and baccharis (20%) were the most frequently
used shrub species for nesting (Table 3.10). In contrast, the two most frequently used
shrub species on North Padre Island were black willow (38%) and wax myrtle and
yaupon both at 25% (Table 3.10).
Discussion
The best predictive model of WTHA nesting habitat on Matagorda Island
included the parameters ShCAT, NND and DISTRd. This suggests nest site selection in
a low human impacted area was influenced not only by nesting substrate availability, but
also behavioral aspects (NND) associated with intra-specific spacing.
58
Previous studies have documented that WTHAs nest more frequently in thorny
shrub species than what is randomly available (Kopeny 1988, Actkinson 2006). Since
WTHAs nest in lower substrates relative to other Buteo spp. (Actkinson 2006) they may
select thorny shrub species as a means of predator defense. Also, the structural
characteristics of the DT category of shrubs may facilitate nest support and protection
from the almost constant and sometimes very strong, coastal winds.
Additionally, the main road on Matagorda Island runs down the middle of the
island. Therefore the negative coefficient for that parameter may not mean that WTHAs
are selecting for areas close to the road, but rather for terrestrial areas which have a
suitable nest shrub, generally closer to the center or upland portion of the island. Indeed,
because there is low human presence on the island, presence of the road may not be a
detracting factor to nest selection by WTHAs. However, the low human presence may
also result in WTHAs being less habituated to and, hence, less tolerant of, disturbances
caused by vehicle traffic. Although I did not quantify my observations, WTHAs will
frequently flush from nests several hundred meters from the road when a vehicle passes
by.
With Matagorda Island viewed as a relatively contiguous landscape in this study,
WTHAs may be nesting at, or near, their maximum density on this island. High nesting
density may be allowed by sufficient presence of adequate shrub species, in this case
mostly Macartney rose and yaupon, for nest placement. However, intra-specific
tolerances as indicated by low NND distances compared to other locations and by NND
59
being an important parameter in the model set, may suggest the island is saturated with
breeding pairs as suggested in Chapter II.
The RSPF of the best predicting model from Matagorda Island performed well on
Mustang Island, even though the model had a low Akaike weight. However, the best
model from the Mustang Island model set included only parameters consisting of shrub
measurements. The preferred shrub category (DT) observed on Matagorda Island was
not available on Mustang Island. When choosing yaupon or baccharis, size of the shrub
appears to have more importance on Mustang Island. These results are difficult to
interpret. Several changes are occurring along the Texas coast, primarily due to human
impact (NOAA 1996). As these pressures increase on the natural landscape, the drive to
reproduce may result in WTHAs habituating to human presences and associated
parameters in order to locate and use suitable nest shrubs. In addition, nearest-neighbor
distance may not be an important factor on the island due to fragmentation of the natural
landscape. Availability of foraging areas and suitable nest sites in a fragmented
landscape may result in nearest neighbor distances that are greater than intra-specific
territory sizes. However, the sample size obtained from Mustang Island is small due to
the island primarily consisting of private property and a lower density of WTHAs.
Therefore the models created from Mustang Island should be interpreted with care.
The RSPF from the best model from Matagorda Island was not as accurate in its
predictions for North Padre Island. Even though it was ranked low in the North Padre
Island model set, it still accurately predicted 50% of nest sites from random sites
correctly. The best model from North Padre Island data set was similar to that from
60
Mustang Island in suggesting shrub characteristics were clearly the most important
parameters. However, a complete census of nesting WTHAs was not conducted on North
Padre Island; therefore all variables may not hold the same precedence. For example,
NND on North Padre Island may be lower than what this study observed. In addition, the
area surveyed on North Padre Island has a different island structure compared to
Matagorda Island and Mustang Island. The northern extent of the island has many inland
dunes, including areas of dunes which run parallel to the bayside of the island. There are
very few shrubs scattered across the landscape; instead they appear more clustered,
especially along the bayside dune lines which get covered in black willow. Near
Yarbrough Pass the inner island is flat with very little upland area. At this point the
island is no more than 0.8 km across. These observations and the results of the best
model from North Padre Island may be indicative that suitable nest shrubs are a limiting
factor on this island.
The post-hoc ANOVAs conducted at the 0.04 and 1.1 ha scales suggest WTHAs
are not selecting nest sites on basis of ground cover. This is likely due to relatively
simple and consistent patterns of vegetative cover on the barrier islands compared to the
mainland (Rappole and Blacklock 1985).
There was a significant difference of distance to road between Mustang and North
Padre Islands. This is probably a result of limited length of road traversing the center of
North Padre Island; afterward driving is limited to the beach side of the island. There
was also significant difference in nearest-neighbor distance between Matagorda and
North Padre Island. This may be a true difference or a result of different survey
61
methodology resulting in an incomplete census of North Padre Island, and therefore a
biased nearest-neighbor distance for North Padre Island. Finally, several thorny shrub
species were not observed in either nest or random sites on Mustang and North Padre
Islands. This suggests the low nesting density of WTHAs on these islands may be a
result of limited availability of suitable shrub species. Mesquite was used once on
Mustang Island, but was inaccessible, and huisache was used on North Padre Island,
however a random point without a remnant nest could not be located. The shrub
categories used most frequently by WTHAs on barrier islands were DT and D.
Management Implications
This study indicates the importance of suitable nest substrate availability for
WTHA on the Texas barrier islands. The results show that the shrub type, nearestneighbor distance, and distance to road are all important characteristics to WTHA nesting
habitat selection in areas with low human impact. However, in areas where shrubs might
be a limiting factor, the characteristics of these shrubs appear to be important in WTHA
nest site selection. Overall, shrub species and shrub characteristics are important to
WTHA nest site selection; removal of certain shrub species may result in a localized
decline in WTHA breeding populations and / or productivity. Alternatively, WTHA
populations may be increased by providing suitable shrub species as nesting substrates.
Ground cover around the nest site does not appear to be a significant factor in WTHA
nest site selection. The RSPF from the best model on Matagorda Island appears
relatively robust when used on different islands. However the RSPF should be used with
caution, since it has shown to decline in predictability when extrapolated to other areas.
62
Literature Cited
Actkinson, M. A. 2006. Productivity and nest-site selection of a breeding raptor
community in south Texas. Thesis, Texas A&M University, Kingsville, USA.
Beyer, H. L. 2006. Hawth’s analysis tools. Version 3.27.
<http://www.spatialecology.com/htools/>. Accessed 10 October 2006.
Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference.
Springer, New York, USA.
Crossett, K. M., T. J. Culliton, P. C. Wiley, and T. R. Goodspeed. 2004. Population
trends along the coastal United States: 1980-2008. National Oceanic and
Atmospheric Administration, U.S. Department of Commerce, USA.
Farquhar, C. C. 1986. Ecology and breeding behavior of the white-tailed hawk on the
northern Coastal Priaries of Texas. Dissertation, Texas A&M University, College
Station, USA.
Farquhar, C. C. 1992. White-tailed hawk. in A. Poole, P. Stettenheim, and F. Gill,
editors. The Birds of North America, No. 30. Philadelphia: The Academy of
Natural Sciences; Washington, D.C. The American Ornithologists’ Union.
Fernández-Juricic, E., and J. Jokimäki. 2001. A habitat island approach to conserving
birds in urban landscapes: case studies from southern and northern Europe.
Biodiversity Conservation 10:2023-2043.
Grimm, N. B., J. M. Grove, S. T. Pickett, and C. L. Redman. 2000. Integrated
approaches to long-term studies of urban ecological systems. BioScience 50:571584.
63
Hadidian, J., J. Sauer, C. Swarth, P. Hanly, S. Droege, C. Williams, J. Huff, and G.
Didden. 1997. A citywide breeding bird survey for Wahsington, DC. Urban
Ecosystems 1:87-102.
Handbook of Texas Online. 2007.
<http://www.tsha.utexas.edu/handbook/online/articles/PP/hjp11.html>. Accessed
9 October 2007.
Hobbs, F., and N. Stoops. 2002. Demographic Trends in the 20th Century. US Census
Bureau, Census 2000 Special Reports, Series CENSR-4. U.S. Government
Printing Office. Washington D.C., USA.
Hosmer, D. W., and S. Lemeshow. 2000. Applied logistic regression. Second edition.
John Wiley & Sons, Inc., New York, USA.
Jahrsdoerfer, S. E., and D. M. Leslie Jr. 1988. Tamaulipan brushlands of the Lower Rio
Grande Valley of south Texas: description, human impacts, and management
options. U.S. Fish and Wildlife Service, Biological Report 88(36).
Kopeny, M. T. 1988. Effect of thornbrush on distribution and nest site selection of
white-tailed hawks (Buteo albicaudatus) in south Texas. Thesis, North Dakota
State University, Fargo, USA.
Manly, B. F. J., L. L. McDonald, D. L. Thomas, T. L. McDonald, and W. P. Erickson.
2002. Resource selection by animals: statistical design and analysis for field
studies. Second Edition. Kluwer, Boston, Massachusetts, USA.
Marzluff, J. M. 2001. Worldwide urbanization and its effects on birds. Pages 19-47 in
Marzluff, J. M., R. Bowman, R. Donnelly., editors. Avian conservation and
64
ecology in an urbanizing world. Kluwer Academic Publishers, Boston,
Massachusetts, USA.
McAlister, W. H., and M. K. McAlister. 1993. A naturalist’s guide: Matagorda Island.
University of Texas Press, Austin, USA.
National Oceanic and Atmospheric Administration [NOAA], and State of Texas Coastal
Coordination Council. 1996. Texas coastal management program: Draft
environmental impact statement. Office of Ocean and Coastal Resource
Management, NOAA, U.S. Department of Commerce, USA.
National Weather Service. 2006. Storm data and unusual weather phenomena.
<http://www.srh.noaa.gov/crp/stories/StormReport/jul06.pdf>. Accessed 10
November 2007.
National Weather Service and National Oceanic and Atmospheric Administration
[NOAA]. 2007. Advanced hydrologic prediction service.
<http://water.weather.gov/>. Accessed 10 November 2007.
Neu, C. W., C. R. Byers, and J. M. Peek. 1974. A technique for analysis of utilizationavailability data. Journal of Wildlife Management 38: 541-545.
Public Use Statistics Office. 2007. 10-157 Reporting: National Park Service.
<http://www2.nature.nps.gov/stats/>. Accessed 2 November 2007.
Rappole, J. H., and G. W. Blacklock. 1985. Birds of the Texas coastal bend. Texas
A&M University Press, College Station, USA.
65
Steenhof, K., and I. Newton. 2007. Assessing raptor nesting success and productivity.
Pages 181-192 in Raptor research and management techniques. D.M. Bird and
K.L. Bildstein, editors. Hancock House Publishers, Blaine, Washington, USA.
Stevenson, J. O. and L. H. Meitzen. 1946. Behavior and food habits of Sennett’s whitetailed hawk in Texas. Wilson Bulletin 58:198-205.
Texas Parks & Wildlife Department [TPWD]. 1984. Master Plan and Program: 5 year
plan for Matagorda Island State Park and Wildlife Management Area. Draft.
Texas Parks and Wildlife Department, Texas, USA.
The Nature Conservancy. 2002. The gulf coast prairies and marshes ecoregional
conservation plan. Gulf coast Prairies and marshes Ecoregional Planning Team,
The Nature Conservancy, San Antonio, TX, USA.
Tyler, R., D. E. Barnett, R. R. Barkley, P. C. Anderson, and M. F. Odintz, editors. 1996.
The new handbook of Texas. Texas State Historical Association, Austin, USA.
Weise, B. R., and W. A. White. 1980. Padre Island National Seashore: A guide to the
geology, natural environments, and history of a Texas barrier island. University
of Texas, Austin, USA.
White, C. M., and T. L. Thurow. 1985. Reproduction of ferruginous hawks exposed to
controlled disturbance. Condor 87:14-22.
Wilcove, D. S., D, Rothstein, J. Dubow, A. Phillips, and E. Losos. 1998. Quantifying
threats to imperiled species in the United States. Bioscience 48: 607-615.
Wilson, E. O. 1999. The Diversity of Life. W. W. Norton & Company, New York,
USA.
66
Table 3.1. Candidate models from Matagorda Island describing the probability of a
potential nest site being selected by White-tailed Hawks from 2006-2007. Models in
italics are within the model confidence interval (Burnham and Andreson 2002).
A priori Models
K
-2LL
AICc
Δi ωi
NND + DISTRd + ShCAT
6
19.81
38.81
0.00
0.39
DISTRd + ShCAT
5
24.63
39.25
0.44
0.32
HT + NND + ShCAT
6
21.84
40.84
2.03
0.14
HT + DISTRd + ShCAT
6
23.81
42.81
4.00
0.05
ShCAT
7
18.73
42.91
4.10
0.05
HT + CIRC + ShCAT
6
25.61
44.61
5.80
0.02
ShCAT
7
20.60
44.78
5.97
0.02
HT + CIRC + HT*CIRC
3
41.43
49.03
10.22
0.00
9
12.43
50.43
11.62
0.00
NND
4
41.42
52.28
13.47
0.00
NND + DISTRd
2
52.66
57.41
18.60
0.00
HT + NND + DISTRd +
HT + CIRC + HT*CIRC +
HT + CIRC + HT*CIRC +
NND + DISTRd + ShCAT
HT + CIRC + HT*CIRC +
a
NND = nearest-neighbor distance; DISTRd = distance to maintained road; ShCAT =
shrub categories; HT = shrub height; CIRC = shrub circumference
67
Table 3.2. Coefficients of variables and their standard errors for the Matagorda Island
resource probability function of White-tailed Hawk nest site selection.
a
Variable Namea
Coefficiant
(±SE)
Constant
4.165
(3.0904)
ShCAT
-
-
D
-2.4551
(2.6101)
O
-27.4586
(10778.40)
OT
-7.9446
(3.5707)
DISTRd
-3.1751
(2.1419)
NND
1.306
(0.7012)
ShCAT = shrub categories; DT = densely branched and thorned, reference variable; OT
= openly branched and thorned; D = densely branched; O = openly branched; NND =
nearest-neighbor distance; DISTRd = distance to maintained road
68
Table 3.3. Candidate models from Mustang Island describing the probability of a
potential nest site being selected by White-tailed Hawks from 2006-2007. Models in
italics are within the model confidence interval (Burnham and Andreson 2002).
A priori Models
K
-2LL
AICc
Δi ωi
HT + CIRC + HT*CIRC
3
6.05
16.05
0.00
0.71
NND + DISTRd
2
13.84
19.56
3.50
0.12
NND + DISTRd + ShCAT
3
10.71
20.71
4.66
0.07
NND
4
5.39
21.39
5.34
0.05
DISTRd + ShCAT
3
12.02
22.02
5.96
0.04
HT + NND + ShCAT
4
11.05
27.05
11.00
0.00
HT + CIRC + ShCAT
4
11.57
27.57
11.52
0.00
HT + DISTRd + ShCAT
4
11.88
27.88
11.83
0.00
5
5.79
30.79
14.74
0.00
ShCAT
5
10.64
35.64
19.59
0.00
HT + CIRC + HT + NND +
7
5.25
75.25
59.19
0.00
HT + CIRC + HT*CIRC +
HT + CIRC + HT*CIRC +
ShCAT
HT + NND + DISTRd +
DISTRd + ShCAT
a
NND = nearest-neighbor distance; DISTRd = distance to maintained road; ShCAT =
shrub categories; HT = shrub height; CIRC = shrub circumference
69
Table 3.4. Candidate models from North Padre Island describing the probability of a
potential nest site being selected by White-tailed Hawks from 2006-2007. Models in
italics are within the model confidence interval (Burnham and Andreson 2002).
A priori Models
K
-2LL
AICc
Δi ωi
HT + CIRC + HT*CIRC
3
7.22
17.22
0.00
0.69
NND + DISTRd
2
13.86
19.57
2.35
0.21
HT + CIRC + ShCAT
4
6.37
22.37
5.14
0.05
DISTRd + ShCAT
3
13.86
23.86
6.63
0.03
HT + NND + ShCAT
4
10.55
26.55
9.33
0.01
HT + DISTRd + ShCAT
4
11.15
27.15
9.93
0.00
NND + DISTRd + ShCAT
4
13.86
29.86
12.63
0.00
5
6.35
31.35
14.12
0.00
5
10.38
35.38
18.15
0.00
6
0.00
-
-
-
4
0.00
-
-
-
HT + CIRC + HT*CIRC +
ShCAT
HT + NND + DISTRd +
ShCAT
HT + CIRC + HT*CIRC +
NND + DISTRd + ShCAT
HT + CIRC + HT*CIRC +
NND
a
NND = nearest-neighbor distance; DISTRd = distance to maintained road; ShCAT =
shrub categories; HT = shrub height; CIRC = shrub circumference
70
Table 3.5. Means and standard deviations for variables collected at White-tailed Hawk nest sites on Matagorda, Mustang and North
Padre Islands in 2006 and 2007.
All Islands
Matagorda
(SD)
Mustang (SD)
North Padre
(SD)
Shrub Height (m)
2.17 (± 0.56)
2.07 (± 0.37)
2.91 (± 1.56)
Shrub Circumference (m)
21.59 (± 9.92)
15.22 (± 3.84)
15.40 (± 6.16)
Nearest-neighbor Distance (km)
1.89 (± 1.02)*
3.13 (± 0.53)
3.98 (± 2.40)*
Distance to Road (km)
0.40 (± 0.37)
0.19 (± 0.08)**
0.75 (± 0.21)**
Variables
* Indicates means which are significantly different at P = 0.003 using the post-hoc Tukey test
** Indicates means which are significantly different at P = 0.029 using the post-hoc Tukey test
71
Table 3.6. Means and standard deviations of nest site and random site variables on
Matagorda Island in 2006 and 2007.
Matagorda Island
Variables
Nests (±SD)
Random (SD)
Shrub Height (m)
2.17 (± 0.56)
2.15 (± 0.58)
Shrub Circumference (m)
21.59 (± 9.92)
14.77 (± 10.65)
Nearest-neighbor Distance (km)
1.89 (± 1.02)
1.86 (± 1.00)
Distance to Road (km)
0.40 (± 0.37)
0.41 (± 0.49)
Table 3.7. Means and standard deviations of nest site and random site variables on
Mustang Island in 2006 and 2007.
Mustang Island
Variables
Nests (SD)
Random (SD)
Shrub Height (m)
2.07 (± 0.37)
1.91 (± 0.42)
Shrub Circumference (m)
15.22 (± 3.84)
12.96 (± 4.23)
Nearest-neighbor Distance (km)
3.13 (± 0.53)
3.10 (± 0.56)
Distance to Road (km)
0.19 (± 0.08)
0.19 (± 0.14)
72
Table 3.8. Means and standard deviations of nest site and random site variables on North
Padre Island in 2006 and 2007.
North Padre Island
Variables
Nests (SD)
Random (SD)
Shrub Height (m)
2.91 (± 1.56)
2.73 (± 1.48)
Shrub Circumference (m)
15.40 (± 6.16)
25.68 (± 9.93)
Nearest-neighbor Distance (km)
3.98 (± 2.40)
4.01 (± 2.27)
Distance to Road (km)
0.75 (± 0.21)
0.77 (± 0.36)
73
Table 3.9. The proportion of shrubs encountered at nest and random sites. The shrubs are listed in their respective category.
DT = densely branched and thorned; OT = openly branched and thorned; D = densely branched; O = openly branched
ShCAT Shrubs species
DT
OT
D
Mustang
North Padre
Nest
Random
Nest
Random
Huisache (Acacia farnesiana)
1 (4%)
-
-
-
Lime Prickly Ash (Zanthoxylum fagara)
1 (4%)
-
-
-
-
-
Macartney rose (Rosa bracteata)
11 (39%)
1 (4%)
-
-
-
-
Honey Mesquite (Prosopis glandulosa)
5 (18%)
10 (36%)
-
-
-
-
Tickle Tonge (Zanthoxylum hirsutum)
-
6 (21%)
-
-
-
-
Wax Myrtle (Myrica pusilla)
-
-
-
-
2 (50%)
2 (40%)
10 (36%)
1 (4%)
3 (60%)
1 (20%)
1 (25%)
-
Baccharis (Baccharis spp.)
-
7 (25%)
2 (40%)
3 (60%)
-
-
Black Mangrove (Avicennia germinans)
-
2 (7%)
-
1 (20%)
-
-
Black Willow (Salix nigra)
-
-
-
-
1 (25%)
2 (20%)
Saltcedar (Tamarix ramosissima)
-
1 (4%)
-
-
-
-
5 (100%)
5 (100%)
4 (100%)
4 (100%)
Yaupon (Ilex vomitoria)
O
Matagorda
Total
28 (100%) 28 (100%)
74
Nest
Random
-
Table 3.10. The proportion of all shrubs used as nesting substrate. The shrubs are listed in their respective category. DT =
densely branched and thorned; OT = openly branched and thorned; D = densely branched; O = openly branched
ShCAT Nest Shrubs Species
Matagorda
Mustang
North Padre
DT
Huisache (Acacia farnesiana)
Lime Prickly Ash (Zanthoxylum fagara)
Macartney rose (Rosa bracteata)
Honey Mesquite (Prosopis glandulosa)
Wax Myrtle (Myrica pusilla)
Texas Persimmon (Diospyros texana)
Yaupon (Ilex vomitoria)
Baccharis (Baccharis spp.)
Black Mangrove (Avicennia germinans)
Black Willow (Salix nigra)
1 (3%)
1 (3%)
14 (35%)
6 (15%)
18 (45%)
-
1 (10%)
1 (10%)
1 (10%)
5 (50%)
2 (20%)
-
1 (13%)
2 (25%)
2 (25%)
3 (38%)
Total
40 (100%)
10 (100%)
8 (100%)
OT
D
O
75
CHAPTER IV
BEHAVIOR OF WHITE-TAILED HAWKS BREEDING AT TWO LEVELS OF
HUMAN DISTURBANCE ON THE TEXAS BARRIER ISLANDS
Abstract
I conducted behavioral observations on breeding White-tailed Hawk (Buteo
albicaudatus; WTHA) pairs on Matagorda, Mustang and North Padre Islands, Texas in
2007. These islands were classified into high human disturbance (Mustang and North
Padre Islands) and low human disturbance (Matagorda Island). Observations were
conducted only during 2-3.5 hours after sunrise, after which visibility decreased due to
shimmer caused by radiated heat. I used a generalized liner model with a logit link
function that tested for differences between islands. Data collected from two breeding
stages were analyzed with a repeated measures analysis. Pairs in low human disturbance
areas spent more time flying than pairs in high human disturbance areas. This may be a
result of an increase in interspecific and intraspecific territorial defense on Matagorda
Island. Pairs in high human disturbance appeared to habituate to consistent human
disturbances near roads.
Introduction
Avifauna is increasingly affected by human disturbances that influence different
aspects of their biology (Marzluff 2001). From a conservation perspective, human
disturbance of wildlife is important only if it affects survival or productivity and results in
76
a population change (Gill et al. 2001). Several studies have investigated how human
activities may impact bird productivity (e.g. White and Thurow 1985, Ruhlen et al. 2003)
Nest abandonment and increased predation of eggs and young may reduce productivity
near areas of human disturbance (Hockin et al. 1992), but it is often unclear as to why
breeding bird populations suffer declines in productivity (Beale and Monaghan 2004).
The prominent point is that human disturbances may negatively influence avian
populations. In addition to outright landscape conversion from native habitat to
urbanization and agriculture crop production (e.g., Marzluff 2001), less obvious but
deleterious disturbances may occur simply by human presence (e.g., White and Thurow
1985, Beale and Monaghan 2004). This is of concern for conservation efforts, as the rate
of human visitation to biodiversity hotspots is likely to double by 2020 resulting in a
potential for increased human influence on wildlife populations (Christ et al. 2003).
Coastal areas in particular are experiencing rapid human population growth
(Beach 2002), with coastal counties accounting for half the U.S. population in 2000
(Hobbs and Stoops 2002). Along the Texas coast, the human population growth
increased 52% between 1980 and 2003, and is predicted to reach 7.7 million by 2008
(Crossett et al. 2004). Additionally, over one-third of the state’s permanent residents and
70% of its economic activity are located within 160 km of the Texas coast (NOAA 1996).
Furthermore, half of the nation’s petrochemical industry and more than a quarter of its
refining capacity are found along the Texas coast, in addition to some of the busiest port
facilities (NOAA 1996, USFWS 2000). Combined, these pressures from urban growth,
tourism, agriculture, development and industry have intensified competition for Texas
77
coastal resources (NOAA 1996). Historic information shows that portions of this area
have already undergone substantial fragmentation and degradation, with 95% of the
coastal grasslands having been lost between the early 1900s and 1988 (Jahrsdoerfer and
Leslie 1988). Coincidentally, coastal Texas is one of the most biologically diverse areas
of the state (Rappole and Blacklock 1985). The diversity of bird species found in this
area alone is among the greatest anywhere in the U.S. (Rappole and Blacklock 1985).
This avian community includes the white-tailed hawk (Buteo albicaudatus; WTHA)
which, in the United States, can only be found along coastal Texas (Farquhar 1992).
The state-threatened WTHA is one of the least studied raptors occurring in North
America (Farquhar 1992). In 1977 the WTHA population size was estimated at 200
breeding pairs in Texas (Morrison 1978), but there are insufficient data to accurately
estimate the current population. The few studies conducted on WTHAs have been on
large tracts of private property or on the Attwater Prairie Chicken National Wildlife
Refuge (Farquhar 1986, Kopeny 1988, Actkinson 2006), which typically have a more
complex vegetative community and restricted human access and activity than the Texas
barrier islands.
Preliminary surveys suggested WTHAs may breed at high densities on some
barrier islands compared to the mainland (Boal and Haralson, unpublished data).
However, human population growth and associated residential, recreational, and
commercial development on the barrier islands may degrade habitat quality for the
WTHA. Given the state-threatened status of the WTHA, the uncertain population size
and trend, and the unknown aspects of its ecology on barrier islands, it is prudent to
78
develop an understanding of how human disturbance may influence the species breeding
behavior. This information may facilitate development of sound management strategies
to minimize human disturbance on WTHAs as coastal development progresses. This is
of particular concern with WTHAs, as the species has demonstrated little tolerance for
human disturbance near their nests by readily abandoning clutches (Stevenson and
Meitzen 1946, Chapter II). However, no study has specifically examined the potential
impacts of human activities on breeding behavior of WTHAs. I conducted observations
of breeding WTHA pairs to characterize behavior between islands with low and high
levels of human disturbance.
Study Area
This study was conducted on Matagorda, Mustang, and North Padre Islands along
the Texas coast. Structurally, these long and narrow barrier islands are similar in having
rows of dunes along the Gulf side which are constantly being formed and moved by the
wind (Weise and White 1980, McAlister and McAlister 1993). Some dunes are held in
place by vegetation and form a ridgeline of dunes parallel to the beach. More sand may
be blown inward, creating additional dunes further inland (Weise and White 1980).
Behind the dunes, the islands are primarily flat with little topography. Vegetation on the
Texas barrier islands is simple when compared with vegetation communities found on the
mainland (Rappole and Blacklock 1985, McAlister and McAlister 1993). This is
predominantly due to salinity levels, proximity to the Gulf of Mexico, the moving sand
dunes, and the sometimes harsh weather to which the islands are exposed (Jahrsdoerfer
and Leslie 1988). Ground cover across the upland areas is typically a matrix of sedges,
79
grasses, and forbs interspersed with various shrub species. Both the vegetation and
climate on the barrier islands is greatly influenced by the Gulf of Mexico (Texas Parks
and Wildlife Department 1984).
Matagorda Island was the northern most island of this study area and was located
in Calhoun County, Texas. Calhoun County has a mild climate and receives about 101
cm of precipitation annually (Handbook of Texas Online). The island was approximately
61 km long with an area of 202 km2 (McAlister and McAlister 1993). Historically, the
island was primarily used for ranching and later as a bombing range for a military air
base (Texas Parks and Wildlife Department 1984, McAlister and McAlister 1993). In
1982 the U.S. Air Force transferred the northern 45 km of the Island (77 km2), to the U.S.
Fish and Wildlife Service (USFWS) for “wildlife conservation purposes” and permanent
inclusion in the National Wildlife Refuge System. State lands, released by the Air Force
in 1979, comprising 106 km2 of adjoining salt marshes and Gulf beach, were placed
under the supervision of the Texas Parks and Wildlife Department (TPWD) under lease
from the Texas General Land Office (GLO). In 1988 the USFWS acquired fee title of the
privately held lower third portion of Matagorda Island (47 km2). In 1989, the USFWS,
TPWD and GLO conceptually agreed to a partnership arrangement for management of
the entire Island. Currently, TPWD is responsible for public use and the USFWS is
responsible for wildlife and habitat management (F. Prieto, Aransas National Wildlife
Refuge, pers. comm.). The name for this all-inclusive entity is known as Matagorda
Island National Wildlife Refuge and State Natural Area (F. Prieto, Aransas National
Wildlife Refuge, pers. comm.).
80
Matagorda Island was broken down into management units which were burned on
a 3-5 year rotation (F. Prieto, Aransas National Wildlife Refuge, pers. comm.).
Matagorda Island unique among the barrier islands in this study in that, although open to
the public, access was difficult as there was no vehicular access to the island. Although
there was no vehicle access to the island, there was one road which ran the length of the
island and was used by USFWS, TPWD and petroleum exploration vehicles. With
exceptions of the sand dunes, Matagorda was flat to gently rolling (Texas Parks and
Wildlife Department 1984, McAlister and McAlister 1993). The vegetation on the island
appeared to grow in bands parallel to the shoreline with varying degrees of tolerance to
salt (McAlister and McAlister 1993). Shrubs found on Matagorda Island were yaupon
holly (Ilex vomitoria), honey mesquite (Prosopis glandulosa torreyana), Mexican
persimmon (Diospyros texana), huisache (Acacia farnesiana), and baccharis (Baccharis
spp.) (McAlister and McAlister 1993). For this study, I consider Matagorda Island as
having low human disturbance across the whole island.
Mustang Island was approximately 29 km long (Tyler et al. 1996) and 85 km2,
located in Nueces County, Texas. Except for the sand dunes, Mustang Island was
primarily flat to gently rolling with a humid sub-tropical climate, and received
approximately 76 cm of precipitation annually (Handbook of Texas Online 2007). The
city of Port Aransas was located on the north end of the island and connected to the
mainland by a ferry (Tyler et al. 1996). The population of Port Aransas was over 3,000
in 2000 (Handbook of Texas Online 2007). The beach side of Mustang Island was
progressively being converted to resorts and condominiums, whereas the bay side of the
81
island was undergoing residential development on a lesser scale. Mustang Island was
primarily private property except for the 1.2 km2 Mustang Island State Park near the
south end of the island (Tyler et al. 1996). The south end of Mustang Island was
connected to North Padre Island by a causeway (Weise and White 1980). During peak
tourism, the human population on the island often swells to over 20,000 (Tyler et al.
1996). Primary shrub species observed on this island were black mangrove (Avicennia
germinans), yaupon holly, honey mesquite, and baccharris. For purposes of this study, I
categorized Mustang Island as high human disturbance.
At over 160 km long, Padre Island was the longest sand-barrier island in the U.S.,
extending southward from Corpus Christi nearly to Mexico. It was located in Cameron,
Nueces, Kenedy, Kleberg, and Willacy Counties. These counties received between 66
and 76 cm of annual rainfall (Handbook of Texas Online 2007). Port Mansfield Channel
divided the island and was maintained to provide shipping access to the Gulf Intracoastal
Waterway (Weise and White 1980, Tyler et al. 1996). Due to the length of Padre Island
this study was limited to the northern 61 km of North Padre Island, resulting in 205 km2
surveyed.
North Padre Island was privately owned for approximately the first 32 km at the
north end, where the main uses were residential and recreational development (Tyler et
al. 1996). The remaining 109 km of the island was managed by the National Park
Service (NPS) as the Padre Island National Seashore. In 2006, the seashore attracted
732,794 visitors (Public Use Statistics Office 2007). North Padre Island was connected
to both the mainland and Mustang Island by causeways (Weise and White 1980). North
82
Padre Island fluctuated from 0.8 km wide to 6.4 km in width. The inner island varied
from flat and primarily tidal flats to tall inner dune ridges scattered across the island as
well as bayside dune ridges. Shrub species observed on North Padre Island were waxmyrtle (Myrica pusilla), black willow (Salix nigra), honey mesquite, and huisache
(Acacia farnesiana). For purposes of this study, I categorized the north end of North
Padre Island as high human disturbance.
Methods
Field methods used followed protocols approved by Texas Tech University’s
Animal Care and Use Committee Protocol 06027-05.
Field Methods
I conducted road surveys for WTHAs on Matagorda, Mustang and North Padre
Islands. Road surveys consisted of driving and scanning for soaring or perched WTHAs
(Fuller and Mosher 1987, Bibby et al. 2000). Roads provide easy access for large areas
of land to be surveyed efficiently, however not all areas across the study may have roads
site (Fuller and Mosher 1987), limiting the usefulness of this survey method. In addition,
detectability of a species is greatly influenced by the surrounding landscape (Fuller and
Mosher 1987). However, road surveys are especially useful for soaring raptors and in
areas of open habitat (Fuller and Mosher 1987, Bibby et al. 2000), making them well
suited for WTHA surveys on the coastal grasslands.
I considered an area occupied if I observed WTHAs that appeared to be paired or
an individual engaged in breeding behavior (i.e. territorial defense, nest building)
(Steenhof and Newton 2007). Upon determining an area was occupied, I monitored pairs
83
to try to identify nest sites and conduct nest searches. In addition, I checked all areas
where accessible nests had been located in previous years. I recorded the location of all
nests with a handheld GPS unit, and returned approximately every 2 weeks to monitor
breeding status. After a clutch had been initiated, I then considered the territory to have a
nesting pair.
I attempted to check nests bimonthly to monitor nesting status. If I observed
normal pair behavior (i.e. soaring over nest, flushing from nest) I considered the nest as
still active and avoided approaching the nest at this stage to reduce a chance of
abandonment. If I did not observe a pair in the vicinity of the nest, I would approach and
check the nest to verify the status of the nesting attempt. I used a mirror attached to a
pole to examine nest contents such as prey remains and to count nestlings.
To assess how human activities may influence WTHA breeding behavior, I
conducted behavioral observations on select breeding WTHA pairs on Matagorda, and
Mustang Islands, as well as one nest on North Padre Island. Nests on Matagorda Island
were categorized as exposed to low levels of human disturbance whereas nests on
Mustang and North Padre Islands were categorized as exposed to high human
disturbance.
Behavior observations were limited by several logistical constraints and therefore
are not representative of a daily activity budget. Observations were limited to the first 2
– 3.5 hours of daylight after which visibility over distances was degraded due to shimmer
caused by radiated heat. I choose to monitor behavior of pairs if the nest was visible at a
distance which would not cause behavioral changes (i.e. 200 – 500 m away), and if they
84
were visible from a vehicle or elevated hunting blind. This criterion was based on the
assumption that a person concealed in a vehicle is less disturbing where vehicles are
commonly seen (Mustang Island, North Padre Island) than a person on the ground. On
Matagorda Island vehicle traffic is limited but elevated hunting blinds have been in place
for several years across the island, and some WTHAs select nest sites near elevated
hunting blinds from which an observer could watch behavior unnoticed.
I conducted observations with a Nikon Field scope (20x-45x) and Canon
binoculars (10x40). To minimize disturbance, I arrived at the observation point before
sunrise. I used individual plumage characteristics and behaviors to identify the sex of
individuals within a pair. During observations, I used scan sampling using an audio cue
from a CD player and recorded the behavior for each individual of a pair on the minute.
In order to select adequate behavior categories, I conducted preliminary
observations. I then used the behavior categories of; perched, perched on nest, preening,
flying, feeding, incubating/brooding, out of sight unknown, out of sight known. A few of
these behaviors need to be defined. “Perched” was classified as individuals perched
either on posts, sand dunes, telephone poles, and shrubs other than the nest shrub.
“Perched on nest” was classified as anytime adults were standing on the nest or nest
substrate. It was often difficult to discern different behaviors when the birds were in
flight. Therefore, whenever the observed bird was in flight it was simply categorized as
“flying”. Often when feeding young the adult would feed as well and therefore I pooled
these as “feeding”. Individuals which left the viewable area and could not be accounted
for during observations were classified as “out of sight unknown”. Often individuals
85
would perch on the ground or behind other shrubs and, although their behavior could not
be determined, their location was still known. Therefore, they were classified as “out of
sight known”. Sometimes individuals were observed in incubation posture but preening
as well. In this case the behavior was recorded as incubating, since it was not always
clear if individuals were preening or rearranging nesting material.
Analytical Methods
I recorded behavior data according to date, pair, disturbance level and individual.
I pooled the single nest on North Padre Island with the Mustang Island data and
collectively analyzed them as high human disturbance (HHD), whereas I categorized
Matagorda Island as low human disturbance (LHD). I observed the same pairs until they
fledged young or the nest attempt failed. I estimated the hatching date according to the
approximate age of the nestlings at the first observation of nestlings. Using this estimate
and the incubation period (Farquhar 1992), I pooled each observation session into either
the “egg” or “nestling” stage within each human disturbance level. Analytically, this
allowed me to account for differences in adult behavior due to the breeding stage
(Farquhar 1986). The data I collected from two stages were analyzed with a repeated
measures analysis, to account for repeated observations on the same pairs. I made
comparisons to look for the presence of an interaction of breeding stage and human
disturbance level. After finding no significant interaction effect for any behavior, I
compared the means of each behavior between the human disturbance level and breeding
stage as well as their interaction with a generalized linear model (with a logit link
86
function). Means are presented in tables on an inverse link scale (McCulloch and Searle
2001).
Prey
I also recorded prey items of WTHAs. I identified prey items to the lowest
possible taxon when prey was present in nests during nest checks in 2006 and 2007, and
when prey deliveries were observed during behavior observations in 2007. Due to
several of the prey items being difficult to identify lower than family during observed
prey deliveries, I pooled prey items into 5 discrete taxonomic categories (small mammals,
bats, birds, reptiles, and frogs). As a result of small sample sizes, I pooled observed prey
items from all three islands to assess WTHA prey selection on barrier islands.
Results
I observed 5 pairs of WTHAs on Mustang Island, 1 pair on North Padre Island,
and 7 pairs on Matagorda Island in 2007. Some nesting attempts failed prior to fledging
which precluded further observations. Three pairs from Mustang Island and the one pair
from North Padre Island successfully fledged young, whereas only 3 pairs on Matagorda
Island made it to the nestling stage and only one successfully fledged young. A total of
44.3 hours of observation were conducted in LHD, and a total of 70.0 hours in HHD.
Statistically, there were no interaction effects for perched (F1,72,0.05 =0.11, P =
0.741), perched on the nest (F1,72,0.05 = 1.15, P = 0.286), preening (F1,72,0.05 = 0.05, P =
0.825), flying (F1,72,0.05 = 0.06, P = 0.806), feeding (F1,72,0.05 = 0.00, P = 0.972),
incubation (F1,72,0.05 = 1.09, P = 0.299), or out of sight known (F1,72,0.05 = 0.25, P = 0.616)
(Tables 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, and 4.8). The behavior of “out of sight unknown” was
87
the only variable for which the interaction of human disturbance level and breeding stage
approached significance (F1,72,0.05 = 3.60, P = 0.062) between LHD (Egg x̄ = 8.1 ± 4.6,
Nestling x̄ = 4.5 ± 3.4) and HHD (Egg x̄ = 6.3 ± 3.1, Nestling x̄ = 21.2 ± 7.2) (Table 4.7).
There was no significant interaction of human disturbance level and breeding
stage for any behavior. Therefore, I looked at breeding stage effect and human
disturbance level effect independently. Perched on nest (F1,72,0.05 = 0.49, P = 0.488),
preen (F1,72,0.05 = 2.42, P = 0.124), flying (F1,72,0.05 = 0.06, P = 0.815), and out of sight
unknown (F1,72,0.05 = 0.52, P = 0.475) were not affected by the breeding stage (Tables 4.2,
4.3, 4.4, and 4.7). Pairs during the nestling stage (x̄ = 44.3 ± 6.1) spent more time
perched than in the egg stage (x̄ = 30.0 ± 4.7) (F1,72,0.05 = 4.44, P = 0.039) (Table 4.1).
Similarly pairs during the nestling stage (x̄ = 2.2 ± 1.1) spent significantly (F1,72,0.05 =
7.79, P = 0.007) more time feeding than in the egg stage (x̄ = 0.06 ± 0.07) (Table 4.5).
As expected breeding stage had an effect on incubation (F1,72,0.05 = 13.30, P = 0.001),
where pairs in the egg stage spent more time (x̄ = 46.4 ± 5.5) incubating than brooding
during the nestling stage (x̄ = 17.5 ± 4.5) (Table 4.6). Also pairs spent more time out of
sight known (F1,72,0.05 = 6.85, P = 0.011) during the nestling stage (x̄ = 1.6 ± 0.8) than
during the egg stage (x̄ = 0.3 ± 0.2) (Table 4.8).
Human disturbance level had no effect on the time pairs spent perched (F1,11,0.05 =
0.02, P = 0.896), perched on nest (F1,11,0.05 = 1.12, P = 0.312), feeding (F1,11,0.05 = 0.00, P
= 0.960), incubation (F1,11,0.05 = 0.62, P = 0.447), out of sight unknown (F1,11,0.05 = 1.19,
P = 0.298), or out of sight known (F1,11,0.05 = 0.03, P = 0.856) (Table 4.1, 4.2, 4.5, 4.6,
4.7, and 4.8). Differences in time individuals spent preening between LHD (14.1%) and
88
HHD (10.1%) were not statistically significant but could be biologically meaningful
(F1,11,0.05 = 3.38, P = 0.093) (Table 4.3). Individuals spent more time flying (F1,11,0.05 =
6.16, P = 0.030) in LHD (4.6%) than in HHD (2.2%) areas (Table 4.4).
Prey
A total of 54 WTHA prey items were identified in 2006 and 2007 (Table 4.9).
Numerically, small mammals were the most frequent prey items observed (56.6%), most
of which were rats (Figure 4.1). Reptiles, consisting of snake species and glass lizards
(Ophisaurus attenuatus attenuatus), were also frequent (35.8%) prey items, (Figure 4.1).
In 2006, on the north end of Matagorda Island, a hoary bat (Lasiurus cinereus) was
observed as a prey item in a WTHA nest. This is the first record of hoary bats occurring
in Calhoun County, and only the second record of WTHAs consuming bats (Granzinolli
and Motta Jr. 2007).
Discussion
This study was to assess behavioral differences of WTHAs between islands with
different levels of human impact. However, differences between breeding stages are a
factor, since the behavior of adults was expected to change between the two stages
(Farquhar 1986). The differences in breeding behavior between breeding stages were not
an objective of this study, but needed to be incorporated into the analysis in case the
human disturbance effect was masked by breeding stage effect.
The interaction effect on the behavior out of sight unknown was nearly
statistically significant, but probably does not have any biological relevance. Due to
areas being highly human impacted on Mustang Island there were more buildings and
89
nonnative trees which obstructed visibility of the viewer. Also, there was a larger sample
size for Matagorda Island during the egg stage, after which several nests were predated,
resulting in a small sample size during the nestling stage. Thus, this nearly significant
difference between out of sight unknown at the human disturbance levels and breeding
stages may have been due to sample size issues within a breeding stage and differences
between island structure.
The data suggests that pairs in low human disturbance areas may spend more time
preening than pairs in high human disturbance areas. This may have biological
importance. Preening by bald eagles (Haliaeetus leucocephalus) has been shown to
decrease in areas of high human disturbance and pairs tended to spend more time at the
nest (Steidl and Anthony 1995). Essentially, preening may be viewed as a ‘relaxed
behavior’; birds that are experiencing disturbance related stress may not engage in
‘relaxed behaviors’ as frequently as those in low disturbance areas. This may be
indicative that WTHAs in the areas of high human activities, such as Mustang Island, are
experiencing disturbance. However, it appears the disturbance levels are not influential
at the reproductive level (Chapter II).
Pairs in high human disturbance areas spend less time flying than pairs in low
human disturbance areas. I suspect this may be due to higher densities occurring on
Matagorda Island (Chapter II). In territorial birds, such as the WTHA, high densities
may result in pairs spending more time defending their territory against intruders than in
low occupancy areas. Matagorda Island also hosts an experimental population of
Aplomado falcons (Falco femoralis). There were a few antagonistic interactions
90
incidentally observed between WTHAs and Aplomado falcons over nest sites and
territory intrusion after nestlings have hatched on Matagorda Island in 2006. On
Matagorda Island there may be interspecific or intraspecific territorial defense
influencing WTHA behavior more so than Mustang Island.
Prey
Overall WTHAs on the Texas barrier islands appear to focus on small mammals
and reptiles. Granzinolli and Motta (2007) recorded WTHAs consuming a high number
of invertebrates, although small mammals made up the largest proportion of biomass.
Small prey items will often be quickly consumed and not left in the nest for observation.
However, I did not observe insects being delivered during direct observations. Similar to
my findings, Stevenson and Meitzen (1946) reported that reptiles were the second mostconsumed group (33%), where Oberholser (1974) considered WTHAs a snake specialist,
and Farquhar (1988) found that reptiles were the third most important group (12.1%),
together with birds (12.1%). WTHAs appear to be opportunistic predators and able to
widen their diet breadth when food becomes scarce (Granzinolli and Motta 2007).
Management Implications
Although WTHAs readily abandon nests due to human disturbance (Chapter II,
Stevenson and Meitzen 1946), they appear to habituate to consistent disturbances (i.e.
traffic on roads, people riding bikes, fishermen), as seen on Mustang and northern North
Padre Island. However, areas that do not see these regular disturbance patterns
throughout the breeding season may result in WTHAs being more prone to failure due to
91
these disturbances. More focused work should be conducted to determine how the
intensity and duration of human disturbance influences breeding WTHAs.
Literature Cited
Alatalo, R. V., and A. Lundberg. 1984. Density-dependence in breeding success of the
pied flycatcher (Ficedula hypoleuca). Journal of Animal Ecology 53: 969-977.
Actkinson, M. A., 2006. Productivity and nest-site selection of a breeding raptor
community in south Texas. Thesis, Texas A&M University, Kingsville, USA.
Beach, D. 2002. Coastal sprawl: The effects of urban design on aquatic ecosystems in
the United States. Pew Oceans Commission, Arlington, Virginia, USA.
Beale, C. M., and P. Monaghan. 2004. Human disturbance: people as predation-free
predators? Journal of Applied Ecology 41: 335-343.
Bibby, C. J., N. D. Burgess, D. A. Hill, and S. Mustoe. 2000. Bird census techniques.
Second edition. Academic Press, San Diego, California, USA.
Christ, C., O. Hillel, S. Matus, and J. Sweeting. 2003. Tourism and biodiversity:
mapping tourism’s global footprint. Conservation International, Washington,
D.C., USA.
Crossett, K. M., T. J. Culliton, P. C. Wiley, and T. R. Goodspeed. 2004. Population
trends along the coastal United States: 198 0-2008. National Oceanic and
Atmospheric Administration [NOAA], U.S. Department of Commerce, USA.
Farquhar, C. C. 1986. Ecology and breeding behavior of the white-tailed hawk on the
northern Coastal Priaries of Texas. Dissertation, Texas A&M University, College
Station, USA.
92
Farquhar, C. C. 1988. Ecology and breeding behavior of the white-tailed hawk. Pages
306-315. in R. L. Glinski., editor. Southwest Raptor Management Symposium
and Workshop. National Wildlife Federation, Washington, D.C., USA.
Farquhar, C. C. 1992. White-tailed hawk. in A. Poole, P. Stettenheim, and F. Gill,
editors. The Birds of North America, No. 30. Philadelphia: The Academy of
Natural Sciences; Washington, D.C. The American Ornithologists’ Union.
Fuller, M. R., and J. A. Mosher. 1987. Raptor survey techniques. Pages 37-65 in B.A.
Giron Pendleton, B. A. Millsap, K. W. Cline, and D. M. Bird, eds. Raptor
management techniques manual. National Wildlife Federation, Washington D.C.,
USA.
Gill, J. A., K. Norris, and W. J. Sutherland. 2001. Why behavioural responses may not
reflect the population consequences of human disturbance. Biological
Conservation 97: 265-268.
Granzinolli, M. A. M., and J. C. Motta, Jr. 2007. Feeding ecology of the white-tailed
hawk (Buteo albicaudatus) in south-eastern Brazil. Emu 107: 214-222.
Handbook of Texas Online. 2007.
<http://www.tsha.utexas.edu/handbook/online/articles/PP/hjp11.html>. Accessed
9 October 2007.
Hobbs, F., and N. Stoops. 2002. Demographic Trends in the 20th Century. US Census
Bureau, Census 2000 Special Reports, Series CENSR-4. U.S. Government
Printing Office. Washington D.C., USA.
93
Hockin, D., M. Ounsted, M. Gorman, D. Hill, V. Keller, and M. A. Barker. 1992.
Examination of the effects of disturbance on birds with reference to its importance
in ecological assessments. Journal of Environmental Management 36: 253-286.
Jahrsdoerfer, S. E., and D. M. Leslie Jr. 1988. Tamaulipan brushlands of the Lower Rio
Grande Valley of south Texas: description, human impacts, and management
options. U.S. Fish and Wildlife Service, Biological Report 88(36).
Kopeny, M. T. 1988. Effect of thornbrush on distribution and nest site selection of
white-tailed hawks (Buteo albicaudatus) in south Texas. Thesis, North Dakota
State University, Fargo, USA.
Marzluff, J. M. 2001. Worldwide urbanization and its effects on birds. Pages 19-47 in
Marzluff, J. M., R. Bowman, R. Donnelly., editors. Avian conservation and
ecology in an urbanizing world. Kluwer Academic Publishers, Boston,
Massachusetts, USA.
McAlister, W. H., and M. K. McAlister. 1993. A naturalist’s guide: Matagorda Island.
University of Texas Press, Austin, USA.
McCulloch, C.E., and S.R. Searle. 2001. Generalized, Linear and Mixed Models. John
Wiley & Sons, New York, USA.
Morrison, M. L. 1978. Breeding characteristics, eggshell thinning, and population trends
of white-tailed hawks in Texas. Texas Ornithological Society Bulletin 11:35-40.
National Oceanic and Atmospheric Administration [NOAA], and State of Texas Coastal
Coordination Council. 1996. Texas coastal management program: Draft
94
environmental impact statement. Office of Ocean and Coastal Resource
Management, NOAA, U.S. Department of Commerce, USA.
Public Use Statistics Office. 2007. 10-157 Reporting: National Park Service.
<http://www2.nature.nps.gov/stats/>. Accessed 2 November 2007.
Oberholser, H. C. 1974. The bird life of Texas. Volume 1. University of Texas Press,
Austin, USA.
Rappole, J. H., and G. W. Blacklock. 1985. Birds of the Texas coastal bend. Texas
A&M University Press, College Station, USA.
Ruhlen, T. D., S. Abbott, L. E. Stenzel, and G. W. Page. 2003. Evidence that human
disturbance reduces snowy plover chick survival. Journal of Field Ornithology
42: 506-513.
Steenhof, K., and I. Newton. 2007. Assessing raptor nesting success and productivity.
Pages 181-192 in Raptor research and management techniques. D.M. Bird and
K.L. Bildstein, editors. Hancock House Publishers, Blaine, Washington, USA.
Steidl, R. J., and R. G. Anthony. 1995. Recreation and bald eagle ecology on the
Gulkana National Wild River, Alaska. Unpublished Final Report to the Bureau of
Land Management, Alaska, USA.
Stevenson, J. O., and L. H. Meitzen. 1946. Behavior and food habits of Sennett’s whitetailed hawk in Texas. Wilson Bulletin 58:198-205.
Texas Parks and Wildlife Departement [TPWD]. 1984. Master Plan and Program: 5 year
plan for Matagorda Island State Park and Wildlife Management Area. Draft.
Texas Parks and Wildlife Department, Texas, USA.
95
Tyler, R., D. E. Barnett, R. R. Barkley, P. C. Anderson, and M. F. Odintz, editors. 1996.
The new handbook of Texas. Texas State Historical Association, Austin, USA.
U. S. Fish and Wildlife Service [USFWS]. 2000. Natural resource management
priorities of the U.S. Fish and Wildlife Service along the Texas coast. Draft. U.S.
Fish and Wildlife Service, Houston, Texas, USA.
White, C. M., and T. L. Thurow. 1985. Reproduction of ferruginous hawks exposed to
controlled disturbance. Condor 87: 14-22.
Weise, B. R., and W. A. White. 1980. Padre Island National Seashore: A guide to the
geology, natural environments, and history of a Texas barrier island. University
of Texas, Austin, USA.
96
Table 4.1. Percent of time spent perched by breeding white-tailed hawks during morning
observation periods on Matagorda and Mustang Island. Proportions are presented by the
breeding stage (egg or nestling) and according to island. Due to no significant interaction
P-values are reported for the stage effect and island effect only.
Island
Matagorda
Mustang
Combined
Mean
Egg
29.5 (± 7.2)
30.5 (± 5.9)
30.0 (± 4.7)
Nestling
46.1 (± 9.8)
42.5 (± 7.2)
44.3 (± 6.1)
Nest Stage
P = 0.039
Combined Mean
37.4 (± 6.7)
36.3 (± 5.3)
P = 0.896
Table 4.2. Percent of time spent perched on nest by breeding white-tailed hawks during
morning observation periods on Matagorda and Mustang Island. Proportions are
presented by the breeding stage (egg or nestling) and according to island. Due to no
significant interaction P-values are reported for the stage effect and island effect only.
Island
Matagorda
Mustang
Combined
Mean
Egg
1.0 (± 0.6)
2.8 (± 1.0)
1.7 (± 0.6)
Nestling
2.2 (± 1.2)
2.4 (± 0.9)
2.3 (± 0.8)
Breeding Stage
P = 0.488
Combined Mean
1.5 (± 0.7)
2.6 (± 0.8)
97
P = 0.312
Table 4.3. Percent of time spent preening by breeding white-tailed hawks during
morning observation periods on Matagorda and Mustang Island. Proportions are
presented by the breeding stage (egg or nestling) and according to island. Due to no
significant interaction P-values are reported for the stage effect and island effect only.
Island
Matagorda
Mustang
Combined
Mean
Egg
12.0 (± 2.4)
8.9 (± 1.6)
10.4 (± 1.4)
Nestling
16.5 (± 3.0)
11.4 (± 1.9)
13.8 (± 1.7)
Breeding Stage
P = 0.124
Combined Mean
14.1 (± 1.9)
10.1 (± 1.2)
P = 0.093
Table 4.4. Percent of time spent flying by breeding white-tailed hawks during morning
observation periods on Matagorda and Mustang Island. Proportions are presented by the
breeding stage (egg or nestling) and according to island. Due to no significant interaction
P-values are reported for the stage effect and island effect only.
Island
Matagorda
Mustang
Combined
Mean
Egg
4.6 (± 1.1)
2.0 (± 0.5)
3.1 (± 0.5)
Nestling
4.6 (± 1.3)
2.3 (± 0.6)
3.2 (± 0.7)
Breeding Stage
P = 0.815
Combined Mean
4.6 (± 1.0)
2.2 (± 0.5)
98
P = 0.030
Table 4.5. Percent of time spent feeding by breeding white-tailed hawks during morning
observation periods on Matagorda and Mustang Island. Proportions are presented by the
breeding stage (egg or nestling) and according to island. Due to no significant interaction
P-values are reported for the stage effect and island effect only.
Island
Matagorda
Mustang
Combined
Mean
Egg
0.06 (± 0.11)
0.06 (± 0.10)
0.06 (± 0.07)
Nestling
2.05 (± 1.60)
2.31 (± 1.39)
02.2 (± 1.07)
Breeding Stage
P = 0.007
Combined Mean
0.34 (± 0.39)
0.37 (± 0.34)
P = 0.960
Table 4.6. Percent of time spent incubating/brooding by breeding white-tailed hawks
during morning observation periods on Matagorda and Mustang Island. Proportions are
presented by the breeding stage (egg or nestling) and according to island. Due to no
significant interaction P-values are reported for the stage effect and island effect only.
Island
Matagorda
Mustang
Combined
Mean
Egg
45.2 (± 8.8)
47.6 (± 6.7)
46.4 (± 5.5)
Nestling
23.3 (± 8.2)
13.0 (± 4.9)
17.5 (± 4.5)
Breeding Stage
P = 0.001
Combined Mean
33.3 (± 6.4)
26.9 (± 5.0)
99
P = 0.447
Table 4.7. Percent of time spent out of sight in an unknown location by breeding whitetailed hawks during morning observation periods on Matagorda and Mustang Island.
Proportions are presented by the breeding stage (egg or nestling) and according to island.
Due to no significant interaction P-values are reported for the stage effect and island
effect only.
Island
Matagorda
Mustang
Combined
Mean
Egg
8.1 (± 4.6)
6.3 (± 3.1)
7.1 (± 2.7)
Nestling
4.5 (± 3.4)
21.2 (± 7.2)
10.1 (± 4.1)
Breeding Stage
P = 0.475
Combined Mean
6.0 (± 3.1)
11.8 (± 4.1)
P = 0.298
Table 4.8. Percent of time spent out of sight in a known location by breeding white-tailed
hawks during morning observation periods on Matagorda and Mustang Island.
Proportions are presented by the breeding stage (egg or nestling) and according to island.
Due to no significant interaction P-values are reported for the stage effect and island
effect only.
Island
Matagorda
Mustang
Combined
Mean
Egg
0.24 (± 0.25)
0.39 (± 0.27)
0.30 (± 0.19)
Nestling
1.71 (± 1.44)
1.49 (± 0.95)
1.59 (± 0.84)
Breeding Stage
P = 0.011
Combined Mean
0.64 (± 0.48)
0.76 (± 0.47)
100
P = 0.856
Table 4.9. Prey items of breeding White-tailed Hawks observed through nest checks and
direct observations on Matagorda, Mustang and North Padre Islands, Texas 2006 and
2007. Items are classified into the lowest possible taxon.
2006
2007
Total
Unknown rodent
9
12
21
Marsh Rice Rat (Oryzomys palustris)
6
Mouse (Peromyscus spp.)
1
Hoary Bat (Ladiurus cinereus)
1
1
Wading bird
1
1
Laughing Gull size avian prey
1
1
Blackbird nestling
1
1
Unknown snake
3
3
Glass Lizard (Ophisaurus attenuatus)
5
Mammalian
6
1
2
Avian
Reptilian
3
8
8
8
Rio Grande Leopoard Frog (Rana berlandieri)
1
1
Unknown
1
1
26
54
Snake / Glass Lizard
Amphibian
Total
28
101
Figure 4.1. Proportion of 5 white-tailed hawk prey categories observed on Matagorda,
Mustang and North Padre Islands, Texas in 2006 and 2007
102
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