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SURVIVAL, MOVEMENT PATTERNS, AND HABITAT USE OF JUVENILE
WOOD STORKS, M~ycteria amnericana
REBECCA A. HYLTON
A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
UNIVERSITY OF FLORIDA
Rebecca A. Hylton
I received tremendous support and encouragement from many friends and
colleagues along the way, and sincerely appreciate their tireless efforts in helping this
project run smoothly. My advisor, Peter Frederick, was ever supportive and patient in
guiding me to trust my instincts, think outside the box, and pursue my goals. His
perceptiveness and spirit were always inspiring, and I thank him for his candor and belief
in my abilities.
I especially want to thank my mother and the following friends for listening,
brainstorming, and sharing their lives with me, as they made this journey worthwhile:
Christa Zweig, Erin Slusser, Jamie Duberstein, Janell Brush, Jenifer Hilburn, Matthew
Bokach, and Zach Welch.
My previous experiences in the Everglades helping Julie Heath, John David
Semones, and Martin Ruane were all extremely influential in making this research a
success. In addition, I thank everyone who helped me drag ladders through the swamp,
capture unwilling quarry, crouch in muck for hours every day, maintain cranky boats and
trucks, keep money in the coffers, and laugh off all the critters that used us for breakfast.
These wonderful folks include Jamie Cloninger, Matthew Bokach, Jenifer Hilburn, John
David Semones, Eric Weis, Jeff Sloan, Madeline Schickel, Jody Bartz, Dawn Reding,
Ben Wollenzien, Laura Hayes, Sam Jones, Caprice McRae, Monica Lingberg, Janell
Brush, Sean O'Conner, Ricardo Zambrano, Paul Miller, and Samantha Musgrave. My
pilots (Matt Alexander and Romke Sikkema) always kept flying fun, despite my
stomach's insistence that I remain on the ground.
I thank Peter Frederick, Ken Meyer, Marilyn Spalding, and Teresa de la Fuente for
their guidance and assistance with field techniques and blood analysis. Marinela
Campanu's statistical assistance was immensely appreciated, as was the GIS advice of
Matthew Bokach, Christa Zweig, and Tom Hoctor. I thank my committee members Peter
Frederick, Ken Meyer, and Graeme Cumming for their thoughtful comments and
I thank Billy Brooks, Ricardo Zambrano, and John Ogden for always being very
helpful and supportive of this research. Finally, I want to thank Everglades National Park
for allowing me to conduct research on their premises; and the U.S. Army Corps of
Engineers and the U. S. Fish and Wildlife Service, for funding this proj ect.
TABLE OF CONTENTS
ACKNOWLEDGMENT S ............ ...... ._ .............. iii...
LI ST OF T ABLE S ............_ ..... ..__ .............. vii..
LIST OF FIGURES ............ _...... ._ ..............viii...
AB STRAC T ................ .............. ix
1 INTRODUCTION ................. ...............1.......... ......
2 FACTORS AFFECTING THE SURVIVAL OF JUVENILE WOOD STORKS,
M~ycteria amnericana, FROM THE EVERGLADES, FLORIDA............__. ...............3
Introducti on ................. ...............3._ _........
M ethods .............. .. ...............5....
Reproductive Success .............. ...............5.__........
Nestling health ............. ...............7._ _........
Satellite Telemetry............... ...............9
Statistical Analysis .............. ...............10....
Re sults.......... _... ......_ ...............12...
Reproductive Success .............. ...............12___ .......
Survival of Tagged Nestlings ....._......__. ..........__ ............1
Fledgling Survival .............. ...............13....
Analysis of Health Factors ........._ ...._. ......___ ............1
Discussion ............. ...............16___ .......
3 HABITAT USE AND MOVEMENT PATTERNS OF JUVENILE WOOD
STORKS (M~ycteria americana) INT THE SOUTHEASTERN UNITED STATES...23
Introducti on ............ ..... .._ ...............23...
M ethods .............. ...............27....
Study Area ............ ..... .._ ...............27...
Satellite Telemetry............... ...............2
Statistical Analysis .............. ...............30....
R e sults............... .. .... .. ...............33....
Movement Patterns ............_ ..... ..__ ...............33...
Habitat Use versus Availability ................. ...............44................
Discussion ................. ...............44.................
Movement Patterns ................. ...............44.................
H habitat U se .............. .. ...............50...
Conservation Implications ................. ...............52.................
4 CONCLUSIONS .............. ...............56....
A HARNESS DESIGN AND EFFICACY OF USING SATELLITE
T RAN SMIT TE RS .............. ...............59....
Harness Desi gn ................. ...............59.................
Efficacy of Teflon Harnesses .............. ...............61....
Efficacy of Satellite Transmitters .....__.....___ ..........._ ............6
B REFERENCE MASS, MEASUREMENTS, MERCURY LEVELS, AND
HEMATOLOGY OF JUVENILE WOOD STORKS .............. .....................6
LIST OF REFERENCES ................. ...............66................
BIOGRAPHICAL SKETCH .............. ...............76....
LIST OF TABLES
2-1 Mean (+ SE) clutch and brood sizes of Wood Storks in
Tamiami West colony ........... ..... .._ ...............11....
2-2 Nesting success of Wood Storks in Tamiami West colony in 2003 ........._.._...........12
2-3 Percent survival rates for juvenile Wood Storks in 2002 and 2003 .........................14
2-4 Multivariate analysis of the risk factors on overall survival in
juvenile Wood Storks (Cox's proportional hazards test) .............. ....................15
3-1 First-year movement rates of tagged juvenile Wood Storks between fledging
dispersal areas, summer ranges and winter ranges in 2002 and 2003 ......................38
3-2 Simplified ranking matrix of habitat preferences for juvenile Wood Storks of the
2002 cohort .............. ...............43....
3-3 Simplified ranking matrix of habitat preferences for juvenile Wood Storks of the
2002 cohort based on localized proportional habitat use ............ .....................44
B-1 Reference body measurements, mercury levels, and hematology of juvenile Wood
Storks ................. ...............65.................
LIST OF FIGURES
2-1 Survival curves of tagged storks in the 2002 and 2003 cohorts for the first 6
months after fledging. ............. ...............14.....
3-1 Map of Florida depicting colony locations (triangles) where juvenile
Wood Storks were tagged in 2002 and 2003 ................. ............... ......... ...28
3-3 Map of all location points for tagged juvenile Wood Storks ............ ..................36
3-4 Migratory path and movements of satellite tagged juvenile Everglades Wood
Storks that summered in Alabama (AL) and Mississippi (MS) in 2002. .................38
3-5 Migratory pathway of satellite juvenile Wood Storks tagged in Florida (FL) that
summered in Georgia (GA) in 2002............... ...............40..
3-6 Locations of 17 juvenile Wood Storks from Nov 2002 April 2003....................41
A-1 A satellite (30g PTT) and radio (10g VHF) transmitter attached to a juvenile Wood
Stork using a Teflon harness. ............. ...............61.....
Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science
SURVIVAL, MOVEMENT PATTERNS, AND HABITAT USE OF
WOOD STORKS, M~ycteria amnericana
Rebecca A. Hylton
Chair: Peter Frederick
Major Department: Wildlife Ecology and Conservation
I used satellite telemetry to analyze the survival, habitat use, and movement
patterns of 72 juvenile Wood Storks (M~ycteria americana) in the southeastern United
States in 2002 and 2003. Survival of juvenile storks varied significantly between years
during all periods (incubation, nestling, fledging, 6 month, 1 year), indicating large year
effects. In the first year, which was largely successful, 88% of the tagged young (n = 33)
survived to fledge, with a 41% first-year survival rate for fledglings (n = 29). In contrast,
tagged birds in second year were largely unsuccessful, with only 50% fledging success
(n = 39), and a 6% first-year survival rate for fledglings (n = 17). The survival rate for
birds 2 years old was 75%.
Using Cox's proportional hazard model, I found white blood cell count of nestlings
to be consistently the best health indicator of postfiedging survival. The models showed
that gender (when combined with health parameters) also played a significant role in
predicting survival, with males being most at risk.
In both years, storks initially dispersed from the Everglades, Florida natal colony
into southern Florida wetlands, but quickly spread north across Florida and the coastal
plains of Georgia, South Carolina, Alabama, and Mississippi. Three strong movement
patterns were identified in both years: rapid dispersal from south/central Florida in June;
a return to central and southern Florida in September/October; and establishment of
individually consistent summer and winter ranges. Results showed that Wood Storks can
exhibit migratory behavior, as the birds demonstrated rapid, predictable, circannual
movement patterns, with 88% of tagged birds showing Eidelity to specific summer ranges
as second-year birds.
Storks used cultivated lands, herbaceous uplands, and wetlands significantly more
than other habitat types in relation to availability. The storks' heavy use of landscapes
dominated by cultivated lands offers a challenging conservation problem, since foraging
within flooded agricultural lands or along drainage ditches may pose serious health risks
to the birds through exposure to agricultural contaminants.
Considering the high variability in annual survival, and the high mobility of this
species, conservation strategies should focus on long-term monitoring efforts that include
a focus at the landscape level. Continuing similar research with juvenile and adult storks
will enable biologists and managers to fully understand interannual variability in survival
rates, and the factors affecting survival.
Wood Storks (M~ycteria amnericana, Ciconiiformes) are large, highly mobile
wading birds found only in the Americas, ranging from the southern United States to
Northern Argentina (Hancock et al. 1992). The U. S. population of breeding Wood
Storks, located in the southeastern states, is federally endangered and is considered
genetically panmictic (Stangel et al. 1990). The wetlands of southern Florida were once
the stronghold of this species (Ogden and Nesbitt 1979). However, habitat degradation
through increased agricultural and urban land development, and subsequent drainage of
freshwater wetlands have probably driven both the storks' population decline and
breeding range expansion into northern Florida, Georgia, and South Carolina (Ogden
Appropriate foraging conditions for Wood Storks are ephemeral and are
irregularly distributed across the landscape both spatially and temporally due to dramatic
changes in water levels and pulses of prey availability (Hoffman et al. 1994). As
appropriate foraging conditions are often short-lived, storks typically require a large
home range because they must frequently change foraging locations (Erwin 1983,
Fleming et al. 1994, Hoffman et al. 1994).
Identifying landscape-level behaviors and survival information for this mobile
species has historically been challenging due to limitations in tracking technology.
Survival during nonbreeding periods has been particularly difficult to quantify, but is
known to significantly influence population fluctuations in many other wading bird
species (North 1979, Kanyamibwa et al. 1990, Cezilly et al. 1996, Saether et al. 1996,
Cezilly 1997). Understanding space-use patterns and population dynamics of storks is
necessary for developing successful conservation strategies across broad geographical
regions (Ims et al. 1993, Turchin 1998, Wiens 1989, Lima and Zollner 1996).
My study was the first attempt to closely follow a robust sample of individual
Wood Storks at the landscape scale, over multiple seasons, by using satellite telemetry. I
followed the nesting success of storks for 2 years and obtained postfiedging survival
estimates for juvenile storks up to 2 years of age. I also examined the impact of nestling
health on the postfiedging survival of tagged storks. Finally, I described the general
movement patterns of tagged birds, and analyzed their habitat use at multiple scales. The
information on juvenile survival will serve as the first step toward filling in a
demographic picture for this species, which can later be coupled with future research on
adult storks. Overall, this knowledge will be instrumental in enhancing the management
of the broader southeastern U. S. population and the habitats on which the population
FACTORS AFFECTING THE SURVIVAL OF JUVENILE WOOD STORKS, Mycteria
amnericana, FROM THE EVERGLADES, FLORIDA
In a multi-species analysis of avian demography, Saether and Bakke (2000) found
high variability in the ability of adult survival rate to explain population growth rates
among long-lived species such as owls, wading birds, and seabirds. For Grey Herons,
Ardea cinerea, the size of the breeding population was closely regulated by juvenile
survival rates (North 1979). Similarly, in some long-lived ungulates (Gaillard et al.
1998) and turtles (Crowder et al. 1994), juvenile survival affected variation in population
growth rates more than did adult survival. However, for those species that delay breeding
until at least 3 years of age, there are relatively few survival estimates for the period
between fledging and breeding. Immatures of these species often spend the prebreeding
period away from their natal areas, making reliable survival estimates difficult to obtain.
Little information is available for the survival of birds during nonbreeding periods
regardless of age class. Survival during the nonbreeding season is typically difficult to
quantify, but is known to have a significant influence on population fluctuations in many
species (North 1979, Cezilly et al. 1996, Saether et al. 1996, Cezilly 1997). For example,
in the temperate zone, survival rates and population trends have been significantly linked
to the severity of winter conditions (Den Held 1981, Kanyamibwa et al. 1990, Hafner et
al. 1994, Cezilly et al. 1996), particularly for first-year birds (Lack 1966, Stafford 1971,
North 1979, Reynolds 1979, Butler 1994).
Although there is considerable information about the fecundity of adult Wood
Storks (Palmer 1962, Rodgers et al. 1997, Coulter et al. 1999), there is very little
information of any kind on the survival or even life history of this species during
nonbreeding periods. In particular, there is almost nothing known about the time
between fledging and first reproduction, a significant period of 2-3 years (Coulter et al.
1999). This time after fledging is when wading birds often suffer the highest mortality
rates of their lifetime (Cezilly 1997, Frederick 2001), with mortality rates often estimated
to be 2-3 times greater than that of adults (Lack 1949, Kahl 1963). I will refer to young
birds less than one year old as juveniles, and prebreeding birds older than one year as
Although Wood Storks are considered a long-lived species with delayed breeding,
very little is actually known about age at first breeding or survival after fledging. Of
1,589 nestlings color-marked in Florida, 4 were subsequently seen in colonies at 3 years
of age with immature plumage, while 3 were seen in colonies displaying adult plumage
when 4 years of age (Coulter et al. 1999). An additional bird color-marked in Georgia
was reported breeding at three years of age (J. Robinette unpubl. data). Most breeding
birds are therefore likely to be at least three years old (Coulter et al. 1999). The White
Stork (Ciconia ciconia) begins breeding on average at 3.4 years (range 2-7 years)
(Barbraud et al. 1999).
R.P. Allen (in Palmer 1962) suggested a 60% survival rate in the first 12 months of
life for juvenile storks and 80% annually thereafter. However, there were no data given
to support these estimates, and they may have been guesses based on information from
other large Ciconiiforms. Little useful information on survival was gained from Ogden's
study either, despite the large number of young tagged (Coulter et al. 1999). The greatest
recorded longevities are 11.7 y for a wild Wood Stork (Hancock et al. 1992) and 27.5 y
for a captive bird (Brouwer et al. 1992).
The health status of birds at the nestling stage is known to have a significant effect
on postfiedging survival (Sagar and Horning 1990, Gaston 1997, Naef-Daenzer et al.
2001, Keedwell 2003). Hematological analysis is commonly used to characterize the
health of wild birds, and blood composition is strongly influenced by the bird' s
nutritional state (Latshaw 1991, Brown 1996, Svensson and Merila 1996, Merino and
My first obj ective was to follow the survival of tagged storks across multiple
seasons and years. I predicted that the highest levels of mortality would occur during the
first 6 months after fledging, when birds are first learning to forage for themselves, and
are moving across unfamiliar landscapes. I also predicted that survival would be lower in
the first year of life, compared to the second year.
My second objective was to compare nestling health and postfledging survival. I
predicted that the body condition, hematological parameters, stress index, and mercury
levels of nestlings would significantly affect their survival postfledging. Specifically, I
predicted that nestlings with lower immune parameters, higher stress indices, and poorer
body condition would have lower rates of postfiedging survival.
I worked in the Tamiami West colony (TW) (N25o45.31, W80o31.90), a
mixed-species wading bird colony located in Everglades National Park, Miami-Dade
County, Florida. Approximately 400 and 350 Wood Stork nests were initiated in TW in
2002 and 2003, respectively. To monitor nest success, I marked nests (120 in 2002, 108
in 2003) with orange surveyor flagging along looping or roughly north-south transects
within the tree island. In both years, only nests within approximately five meters of
transects were marked to avoid focusing efforts in a single area. Although nests were not
randomly selected, I believe I studied a representative cross-section of the nesting
population by traveling throughout much of the total area. At minimum, this design
produced a sample with both edge and center-located nests, which are known to have
different characteristics and risks (Coulson 1968, Brown and Bomberger-Brown 1987,
Simpson et al. 1987, Brunton 1997).
Nests in the Tamiami West colony were almost entirely built in the canopy (2-4m
above ground) of Pond Apple (Annona glabra), although a few nests were in Willow
(Salix caroliniana). I used three-meter long extension poles with attached mirrors to
view nest contents and determine numbers of eggs and young. I conducted nest checks
every 4-7 days throughout the nesting season to determine nest contents and age of
nestlings. I waited 12 days between one pair of successive nest visits, in late April 2002,
to avoid disturbing the large numbers of other nesting wading bird species during critical
egg-laying and incubation periods (Frederick and Collopy 1989).
I used the Mayfield Method (Mayfield 1961, 1975) to estimate nest survival rates,
which pro-rates survival on a daily basis. I calculated success rates separately for the
incubation and nestling periods, as well as an overall nesting success rate (probability that
a nest would survive both periods and produce at least one fledgling) (Hensler and
Nichols 1981). I pro-rated nest initiation dates in cases where a full clutch had yet to be
completely laid, or a chick in a nest was hatching on the nest check date. Nests were
successful if they produced at least one young to 55 days of age. The incubation period
extended from the lay date of the first egg to 27 days after the first egg was laid (Coulter
et al. 1997). The nestling period began on the day the first egg hatched. Brood size was
measured during the second week of the nestling period, after all eggs had hatched (8-14
Only nests visited more than once before termination (failure or success) were
included in the analysis. Nests were considered failed when nest contents were
completely missing, depredated, abandoned (eggs cold to touch), or where all nestlings
were dead. The nest failure date was estimated as the midpoint between the ultimate and
penultimate visits (Mayfield 1961, 1975). The nestling period was truncated at 55 days
after hatching, as birds were typically capable of flying by this time and had become
independent of their nest sites. On average, however, juvenile storks remained associated
with the colony and continued to be fed by their parents until at least 80 days old.
Nestlings were considered fledged only when they permanently left the colony.
Nestling storks were randomly selected for inclusion in the health and telemetry
studies between late April and early June in both years. Starting from the northern-most
section of the transects and moving southward on subsequent visits, I selected the first
marked nests I approached that had chicks of the appropriate age. Only one chick from
each nest was marked to avoid the nonindependence effect of siblings and to control for
biases related to hatching order (Mock 1984, Magrath 1990). Earliest-hatched nestlings
were preferred over later-hatched nestlings. In one case in 2002, the earliest-hatched
chick was too mobile for capture, and its later-hatched sibling was used instead. Hatch
order was determined by visually assessing relative culmen lengths among siblings.
Chicks were fitted with satellite transmitters and had health exams at 4-5 weeks of
age. In cases were nestling age was not known from hatch date, the approximate age of
chicks was based on size, feather growth, and presence of flight feathers (Kahl 1962).
Storks were considered to be at least 4 weeks of age when they had visible white contour
feathers on the back and coverts, and primaries 508cm in length. All nestlings were
caught by hand on the nest and were immediately hooded to reduce stress. I worked in
colonies only during early morning hours, when thermal stress was lowest and when I
was least likely to interrupt feedings by adults.
I fitted a United States Fish and Wildlife Service individually numbered aluminum
leg band to the tibiotarsus of each bird and recorded culmen and tarsus lengths (nearest
mm), and mass (nearest g). Each health assessment also included a physical examination
for oral parasites and ectoparasites (Forrester and Spalding 2003), and palpation for
Eustrongylides nematodes in the abdomen (Spalding et al. 1994). In addition, 4-6
growing scapular feathers were collected from each bird and analyzed within 2-3 months
for total mercury by the Florida Department of Environmental Protection Chemistry
Section (see Frederick et al. 2004 for detailed analysis methodology).
Blood was collected to determine gender, packed cell volume (PCV), leukocyte
counts, and the presence of blood parasites and diseases. I collected up to 2mL of blood
by venipuncture from the brachial vein. Blood samples were collected for sexing by
storing drops of whole blood in ethanol in 2002, and in 2003 by smearing a thin layer of
blood across a Zoomark card. Blood was analyzed for sexing purposes by Zoogen
Services, Inc., Davis, California. Two-four blood smears of whole, nonanticoagulated
blood were prepared for each bird in the field using a 2-slide method (Campbell 1988),
and preserved with a thorough wash of methanol. The remaining blood was transferred
to lithium heparin tubes (100 units/cc).
Hematological evaluations were performed within 4 hours of blood collection using
whole blood from the lithium heparin tubes. Blood was transferred to heparinized
microcapillary tubes and centrifuged at 12,000 rpm for 5 min to obtain PCV. PCV was
measured with a ruler as the percent cellular fraction of total whole blood volume. Total
white blood cell counts (WBC) were performed manually using the eosinophil Unopette
(Becton-Dickinson, Rutherford, NJ, USA) technique by counting the average number of
leucocytes observed within fiye fields under 50 X power (Campbell 1988).
Within four months of preparation, blood smears were stained with Wright-Geisma
stain (ACROS Organics, Morris Plains, NJ, USA) and examined for hemoparasites at the
University of Florida School of Veterinary Medicine, Gainesville, FL. Differential
leukocyte counts were determined for each bird from the blood smears by multiplying the
WBC counts by the percentage of each cell type in the differential. The differential count
included relative percentages of lymphocytes, heterophils, monocytes, basophils and
eosinophils based on descriptions by Hawkey and Dennett (1989). The H/L ratio is the
number of heterophils divided by the number of lymphocytes.
Following the health exam, each bird was fitted with a backpack harness that
carried a 10g VHF radio transmitter with a motion/mortality detector (2002: American
Wildlife Enterprises, Monticello, FL, USA; 2003: Model All20, Advanced Telemetry
Systems, Isanti, MN, USA) and a 35g solar-powered Argos certified PTT for satellite
tracking (Microwave Telemetry, Inc., Columbia, MD, USA, 10 h on/24 h off duty cycle)
(see Chapter 3 and Appendix). The Teflon harness (Bally Ribbon Mills, Bally, PA,
USA), VHF transmitter and PTT weighed approximately 48g. In 2002, I experienced
problems with vultures separating the VHF transmitters from the PTTs on carcasses of
dead birds, so in 2003 I further secured the VHF to the PTT using 2 small screws.
Location information for all PTTs was obtained daily by email from Service Argos, Inc.
(Landover, MD, USA).
I determined the survival of tagged birds by monitoring VHF frequencies daily
from a position near the colony prior to fledging, and by monitoring satellite transmitter
signals after fledging. Postfiedging mortalities were suspected when I stopped receiving
data or when birds did not move from a location for multiple days. To confirm a
mortality, I averaged the last PTT-derived locations for that bird as a guide for a ground
or aerial search, and then used VHF signals to hone in on the precise location of the
I used a Z-test to compare Mayfield nest success rates between years (Hensler and
Nichols 1981). For bivariate analyses, Mann-Whitney U-tests were used with a
Z-approximation. Values are reported as mean + SE, and a significance level of P I 0.05
was set a priori for all statistical tests.
l used Cox's proportional hazards model (Cox 1972, 1975) to determine the effects
of nestling health variables on the survival rate of postfiedging storks (White and Garrott
1990, Lee and Wang 2003). Explanatory variables included WBC, eosinophil,
lymphocyte, basophil, heterophil, monocyte, H/L ratio, body condition, tarsus, culmen,
mass, PCV, and gender. The model was run independently for each year of study,
because survival rates were significantly different between years.
I derived an index of body condition (body mass corrected for variation in body
size, Johnson et al. 1985) using principle component analysis (PROC PRINCOMP, SAS
Institute 2000) of tarsus and culmen lengths (Alisauskas and Ankney 1987, Dufour et al.
1993). The first principal component (PC1) accounted for 71% of the overall variation. I
then regressed body mass on PC1 to give an index of body condition (PROC GLM; SAS
Cox's proportional hazard model was run using PROC PHREG in SAS (SAS
Institute 2000, see Yoder et al. 2004 for a thorough description of this method). This
procedure yielded estimated regression coefficients for the hazard function using a partial
likelihood function that only included probabilities for birds that died within six-months
of fledging. All birds that remained alive on a given day in the model were considered
the at risk population. The threshold for stepwise inclusion of a specific variable into the
model was arbitrarily set at P < 0.20. The Wald test statistic, which uses a chi-square
distribution, was used to determine if the estimated regression coefficients were
significantly different from zero. I also used the Pearson correlation coefficient (PROC
CORR; SAS Institute 2000) to examine the relationship between white blood cell counts
Table 2-1. Mean (a SE) clutch and brood sizes of Wood Storks in Tamiami West colony
Year Average clutch size Average brood size
2002 3.09 & 0.08 (n = 46) 2.81 & 0.09 (n = 26)
2003 3.56 & 0.08 (n = 84) 2.97 & 0.15 (n = 38)
Florida average (1875-1967) 3.28 & 0.05 (n = 199) -
Average historic clutch size in Florida as reported in Rodgers (1990).
Table 2-2. Nesting success of Wood Storks in Tamiami West colony in 2003
Traditional Method Mayfield Method of Success (%)
of Success (%) Incubation Period ** Nestling Period ** Combined
2002 77.39 (n = 115) 49.66 & 1.02 (n = 54) 89.29 & 1.63 (n = 97) 44.34 & 0.62
2003 24.07 (n = 108) 19.04 & 0.57 (n = 84) 23.28 & 0.76 (n = 69) 4.43 & 0.17
Traditional nesting success is number of nests fledging at least one young / number of
nests studied. Mayfield method pro-rates survival on a daily basis. An asterisk (*)
indicates a significant difference of P < 0.01 between years and a double asterisk (**)
indicates a significant difference of P < 0.001.
At the time of initial nest-marking in early March, 57% of 1 15 nests were in the
early nestling stage in 2002 compared with only 4% of 84 nests in 2003; the remainder of
nests were being incubated. Thus the nesting in 2003 was initiated considerably later
than in 2002. The average clutch size of nests marked during the incubation period was
significantly smaller in 2002 at 3.09 compared to 3.56 in 2003 (z = 4.02, P < 0.0001)
(Table 2-1). The average brood size when chicks were 8-14 days old was 2.81 in 2002,
compared with 2.97 in 2003, and was not significantly different between years (z = 0.99,
P = 0.16).
Nesting success was significantly different between years for all stages of nesting
(Table 2-2). The proportion of nests studied with at least one young 55 days old for this
colony was 77.4% in 2002 and 24.1% in 2003 (X2 = 64.7, P < 0.01). The 2003 success
rate was 31% lower than in 2002. Mayfield nest success during the incubation stage was
61% lower in 2003 (19.04%) than in 2002 (49.66%, X = 14. 15, P < 0.001, Table 2-2).
Survival during the nestling period was also significantly lower in 2003 (23.28%) than in
2002 (89.29%, X = 73.84t, P < 0.001). The overall, combined Mvayfield nesting success
for these two periods in 2002 was 44.34%, while the combined overall nesting success
rate for 2003 was 4.43%.
Survival of Tagged Nestlings
Of the 33 birds tagged with satellite transmitters in 2002, 6 mortalities occurred
within the borders of the colony prior to the birds fledging (82% survival prior to
fledging). Two of these mortalities were of flighted birds that were still dependent on the
colony. Of the 34 birds tagged in the Tamiami West colony in 2003, 17 (50% survival)
died prior to fledging.
Twenty-seven birds tagged with satellite transmitters fledged in 2002. The survival
rate for the first 6 months after fledging (June-Nov) was 63.0% (n = 27) (Figure 2-1,
Table 2-3). There were no mortalities in the 2002 cohort between February and July
2003. Second-year survival rate (75%, n = 12, Mar 2003-Feb 2004) was significantly
higher than first-year postfiedging survival rate (41.4%, n = 29, Mar 2002-Feb 2003) for
2002 birds (X2 = 4.23, P < 0.05). Overall, a young bird from the 2002 cohort that became
independent of the colony had a 3 1.0% chance of surviving to 24 months of age. Of the
19 postfiedging mortalities that occurred by two years of age, 14 occurred in Florida
(74%), 2 in Georgia (11%), 1 in Alabama (5%), 1 in Mississippi (5%), and 1 in South
Carolina along the Georgia border (5%).
Seventeen birds tagged with satellite transmitters fledged in 2003. The survival
rate after the first 6 months for the 2003 cohort (23.5%, Figure 2-1, Table 2-3) was
significantly lower than survival in the same period for the 2002 cohort (63.0%, X2= 6. 15,
P < 0.02). Satellite data suggest that only 1 of the 17 fledglings in the 2003 cohort was
still alive after a year, resulting in a 5.9% first-year survival rate. First-year survival rate
Table 2-3. Percent survival rates for juvenile Wood Storks in 2002 and 2003
Survival Rates (%)
Year 6 months 1st year 2nd year
(1-6 months) (1-12 months) (13-24 months)
2002 63.0 41.4 75.0
2003 23.5 5.9-
Six-month survival indicates survival within the first six months of fledging. First year
survival rates are for the first 12-month period after hatching (March-February). The
second-year survival rate is for period of 13-24 months after hatching (March-February).
in 2003 was significantly lower than that of the 2002 cohort (X2 = 4.22, P < 0.05). The
study ended in March 2004 after the 2003 cohort reached 1 year of age, so the 2nd ya
survival rate for the 2003 cohort was not available for comparisons. The majority of
deaths of the fledged 2003 cohort occurred in Florida (13 birds, 81%), while 3 birds died
in Georgia (19%).
I considered using the Kaplan Meier product limit estimator (Kaplan and Meier
1958) as an additional method for estimating survival rates for the juvenile birds. This
estimator requires that birds of ambiguous fates be censored from the sample. My
inability to relocate most grounded transmitters from fledged birds resulted in few known
e May Jun Jul Aug Sep Oci
Figure 2-1. Survival curves of tagged storks in the 2002 and 2003 cohorts for the first
6 months after fledging. As survivorship is based on known outcomes, not
estimates, error bars are not available. Fledging occurred in May in both
mortalities (n = 3 in 2002; n = 4 in 2003) and an inadequate sample size. One other way
to deal with the uncertainty of mortality due to potential tag loss is to express the upper
limit of survival by considering only mortalities that were unambiguous (i.e., transmitters
were relocated with the carcass). Within the fledged 2002 cohort, first year survival rate
of these birds was 75.0% (n = 16), as compared to 41.4% (n = 27) estimated when
including all assumed mortalities. Using only birds with known fates within the fledged
2003 cohort, first year survival rate was 28.6% (n = 7), as compared to 5.88% (n = 17)
estimated when including all assumed mortalities.
Analysis of Health Factors
Multivariate regression analysis using Cox's proportional hazard model revealed
that year (P = 0.0007) and white blood cell counts (P = 0.003 5) significantly affected the
6 month postfiedging survival of juvenile storks (Table 2-4). There was a significant
negative correlation between WBC counts and survival (r = -0.37, P = 0.0335, n = 33).
For the 2002 cohort, white blood cell counts (P = 0.0071) and eosinophil counts
(P = 0.0311) were significant risk factors. Both lymphocytes (P = 0.0679) and gender
Table 2-4. Multivariate analysis of the risk factors on overall survival in juvenile Wood
Storks (Cox's proportional hazards test)
Years combined 2002 Cohort 2003 Cohort
P P P
White Blood Cell (WBC) 0.0035 0.0071 (+) 0.0398(-
Lymphocyte -0.0679 () 0.0271 (+)
Eosinophil -0.0311 () 0.1151 (+)
Gender (M/F) -0.0981 (+) 0.0265 (+)
Heterophil/Lymphocyte ratio --0.0187 (+)
Body condition --0.1126(-
A dash (-) indicates the variable did not meet the P < 0.2 threshold for entry into the
model. Model fit in 2003 was not significant at the 0.05 level. The signs (+/-) indicate
the direction of the variable's relationship to survival.
(P = 0.0981) also showed marginally significant power to explain survival rates in 2002.
When considering all model components together, females were 2.0 & 1.2 times as likely
as males to survive to 6 months of age. The survival rate for the 2003 cohort was not
consistent throughout the 6 month period as there was a large decline in survival during
the first month after fledging, followed by a survival rate similar to that of the 2002
cohort (Figure 2-1). Although the inconsistency in survival rate over the six-month
period resulted in a less accurate fit to the Cox Proportional Hazards Model (X2 = 9.81,
P = 0. 1997), the model for the 2003 cohort still had explanatory value.
Gender (P = 0.0265), WBC levels (P = 0.0398), and lymphocyte levels
(P = 0.0271) all significantly affected the survival rate of juvenile storks in the 2003
cohort. Controlling for health factors, females were 5.0 & 2.3 times as likely to survive 6
months compared to males. Unlike in the 2002 cohort, eosinophil levels (P = 0. 1151)
were not related to survival risk in the 2003 cohort. The H/L ratio, an indicator of stress
levels, was a significant factor in predicting survival rates in 2003 (P = 0.0187). Neither
variation in mercury (P = 0. 1775) nor body condition (P = 0.1126) influenced survival in
the 2003 cohort. Descriptive statistics for the body measurements, mass, mercury levels,
and health factors are in Appendix B.
There were large differences in survival rates for all of the developmental periods
of young storks between the two years of study, despite average to above average clutch
and brood sizes in both years. Nesting success was significantly higher in 2002 than
2003 during both the incubation and nestling periods than in 2003. In 2003, heavy rains
in early March preceded a large abandonment event involving approximately half the
nesting storks in Tamiami West. Rapid water level increases throughout the nesting
period were likely the cause of additional abandonments during the nestling phase (Kahl
1964, Kushlan et al. 1975, Ramo and Busto 1992). Similar abandonments were seen in
other stork colonies in the Everglades ecosystem during this period (Gawlik and Crozier
2003), so it seems unlikely that my own activities in the colony resulted in the
abandonments, and the synchrony of abandonments is in keeping with a weather-related
Although there were large differences in the survival rates of storks during the two
years, the general patterns that emerged largely matched my predictions. First, the wide
range in survival values exhibited by juvenile storks is fairly typical for first-year wading
birds, with high productivity and survival in some years and little to none in others
(Freeman and North 1990, Hafner 1998, Barbraud et al. 1999). Second, the survival rates
of first-year birds are typically lower and more variable than those of older birds. For
example, annual survival of banded juvenile White Storks has been highly variable across
years (0-100%), although adult survival has been relatively constant, averaging 78%
(Barbraud et al. 1999). Little Egrets (Egretta garzetta) are also estimated to have a
higher, less variable adult survival rate of 71.4% (range = 69-86%) compared to Birst-year
birds (7-55%) (Hafner et al. 1998).
The pattern of significantly lower survival in first-year birds compared to older
birds is common and is usually attributed to relative experience levels (Lack 1954, Botkin
and Miller 1974). The greatest mortality in birds occurred during the first six months
after fledging in both years. This is the period when birds are first developing their
foraging skills and independently making decisions regarding habitat selection and
predator avoidance. Juvenile storks often initially forage at inappropriate sites where
adults are not present and prey are unavailable (i.e., flooded lawns and rainwater
depressions) (Coulter et al. 1999). Limited prey availability, when coupled with
inexperience, could have a strong negative impact on survival in some years.
It is extremely unlikely that any birds from the 2003 cohort will reach breeding age.
Even in 2002, which saw significantly higher fledging and survival rates, a fledgling had
only a 3 1.03% chance of surviving to 24 months of age. If the fledglings do not begin
breeding until their 4th year, only approximately 5 of the 29 fledglings (17%) from the
2002 cohort will reach adulthood if the annual survival rate of 75% continues each year
as seen in other Ciconiiformes (Palmer 1968, Hafner et al. 1998, Barbraud et al. 1999).
The high initial mortality of fledglings is an important limiting factor for recruitment to
the breeding population, even in successful years. Characterizing only the nesting and
fledging success of storks may yield inaccurate and limited understanding of actual stork
The survival estimates of juvenile Wood Storks in my study are based on several
assumptions: 1) losses of telemetry devices were due to mortality, 2) PTT failure was
due to mortality, and 3) attachment of transmitters did not affect survival. There is no
evidence to suggest that grounded transmitters were the result of harness failure or
detachment from the harness. Although harnesses were not always found attached to
carcasses, particularly in the colony where scavenging rates were high, all of the
harnesses found were intact. The relocated harnesses were never tom or frayed, and the
stitchings were intact. The only visible wear on the harness was color fading from sun
There was also no evidence that PTTs simple stopped working. The solar power
source for the PTTs used in my study was designed to exceed the lifetime of battery-
powered PTTs (3 years minimum design lifetime). There are limited studies of failure
rate for PTTs due to the inherent difficulty in tracking highly mobile individuals by other
means. Britten et al. (1999) found only a 4.7% failure rate in 42 Peregrine Falcons
(Falco peregrinus) wearing 30Og battery-powered PTT-100s (Microwave Telemetry) that
was not attributable to battery exhaustion. K. Meyer (unpubl. data) reported that losses
of PTT signals for Swallow-tailed Kites (Elanoides forficatus) and Short-tailed Hawks
(Buteo brachyurus) were space/time clumped, suggesting localized sources of bird
mortality and not radio/harness failure. The PTTs of 9 tagged storks were still operating
after 2.25 years as of 1 July 04, and all grounded PTTs (n = 24) were still working upon
recovery. I had no indication that PTT failure was not due to mortality.
Assumption 3, attachment of transmitters did not affect survival, was not tested in
my study, though there is some evidence to support it. Survival estimates of the 42
PTT-tagged peregrines in the Britten et al. (1999) study were not significantly different
from previous survival estimates based on a mark/resighting study of banded peregrines.
K. Meyer (unpubl. data) reported no significant difference between survival estimates of
Swallow-tailed Kites from PTT-tagged and VHF-tagged birds, where PTTs were almost
twice as heavy as VHFs. The maximum migration distance flown for a PTT-tagged
peregrine was also comparable to that of a resighted, banded bird (Ambrose and Riddle
1988, Britten et al. 1999). Transmitter loads for these raptors were >3% of the birds'
mass, as they were in my study.
Although many studies of the effects of PTTs on albatrosses and petrels show an
increase in foraging trip duration and lowered nesting success, transmitter loads usually
exceeded 3% of adult mass, and adults were often tagged during sensitive nesting periods
(see Phillips et al. 2003). Phillips et al. (2003) did not find a significant increase in
foraging trip duration, meal mass, breeding success, or rate of return in adult albatrosses
and petrels when transmitter loads were less than 3% of adult mass and when birds were
tagged during less sensitive nesting periods. I tagged young storks 3-5 weeks prior to
fledging, which allowed for a period of recovery from handling and habituation to the
transmitter package prior to flight and fledging. In light of the existing knowledge about
transmitter effects, it seems unlikely that bird handling and transmitter attachment
affected postfiedging survival.
The hazard model results indicated the importance of the lymphatic system to
survival. WBC were negatively correlated with survival rates in 2003 and, but were
positively correlated in 2002. Eosinophil levels were also negatively correlated with
survival rates in 2002. High WBC and eosinophil counts are often indicative of
infections or blood disorders, while low WBC counts may indicate poor
immunocompetency (Campbell 1994, Svensson and Merila 1996, Howlett et al. 2002).
Thus it seems consistent that poor survival would be associated with both high and low
WBC counts. Similarly, the heterophil/lymphocyte ratio was a significant factor in 2003,
with high ratios negatively correlated with survival.
Although a sex bias was not apparent from the raw survival data, females were
twice as likely as males to survive in 2002 and five times more likely to survive in 2003,
when the effects of other model variables were taken into account. In many vertebrates,
males are negatively affected more often than females by adverse conditions during
growth (Clutton-Brock 1991). As male birds (including Wood Storks) are often larger
and have greater energy requirements than females (Slagsvold et al. 1986), males may
have greater sensitivity to adverse conditions (Clutton-Brock et al. 1985).
There are numerous effects of mercury on birds that may affect survival directly or
indirectly, depending heavily on dose, species and the effects of other stressors (Eisler
1987, Wolfe et al. 1996, Thompson 1996, Frederick 2000). Although mercury did not
appear to affect survival of the young storks in my study, the conditions may not have
resulted in an adequate test of the effect. I measured mercury during a period when
extremely rapid feather growth can effectively depurate body burdens of mercury in
young birds (Honda et al. 1986, Spalding et al. 2000, Sepulveda et al. 1999). In addition,
the young birds may have encountered widely varying levels of mercury exposure during
the postfiedging period (Spalding et al. 2000). Thus the contaminant levels I measured
during the late nestling period may not have been representative of the burdens at
fledging or later.
In general, the results of my study support my prediction that prefiedging health
can significantly affect postfiedging survival, although the variation in results makes
specific interpretations difficult. Overall, 2002 was a much more successful year for
juvenile storks than 2003. During 2003, health factors and gender were more closely
associated with survival, suggesting the may play a role in regulating survival during
years where storks are White blood cell count, an indicator of an organism's ability to
fight infection, was consistently the best health indicator of survival. The variation in
response of survival to high and low hematological values demonstrates the sensitivity of
blood chemistry to perturbations and the variability of health issues in different years.
Although I found that hematological factors were significantly correlated with survival,
there may be many other ecological or physiological factors that also directly impacts
According to the characterizations described by Saether et al. (1996), storks seem
to follow a "bet-hedging" life strategy, in which long-lived species tend to live in
generally favorable breeding and survival habitats, but in which the quality of the
breeding habitat may vary annually. A bet-hedging life-history strategy may be an
adaptation to living in variable environments, allowing for high productivity in
occasional favorable years. Bet-hedging strategies are common in waders, owls and terns
with large clutch sizes and early maturation (<3-yr-old) (Saether et al. 1996). In these
species, however, Saether and Baake found large variation in the contribution of adult
survival rate to population growth rate (2000).
Apart from telling us about the life history strategy of this species, the large
variation in survival rates and effects of health on survival between years and age-classes
demonstrates the importance of interannual effects, and therefore the necessity of
long-term monitoring this species. Continuing similar research with juvenile storks will
enable us to fully understand the interannual variability in survival rates and the factors
affecting survival. Conducting similar studies with adult storks would also provide much
needed information on longevity, age at first breeding, and variability in survival rates.
Long-term monitoring and a functional demographic model will allow managers and
biologists to understand the population dynamics of Wood Storks, enabling the
development of better conservation strategies.
HABITAT USE AND MOVEMENT PATTERNS OF JUVENILE WOOD STORKS
(M~ycteria amnericana) IN THE SOUTHEASTERN UNITED STATES
Conservation and management of highly mobile animals that have large home
ranges requires an understanding of space use patterns at an appropriately large scale
(Wiens 1989, Hansen et al. 1993, Ims et al. 1993, Frederick et al. 1996, Lima and Zollner
1996, Turchin 1998, Roshier et al. 2002, Graham 2001). The pattern of spatial
movements may be at least as critical as the scale for identifying successful conservation
strategies. For example, an accepted approach for seasonally migratory species is to
identify and protect high-use habitat patches and the corridors connecting these patches
(Noss et al. 1996, Wikramanayake et al. 1998, Poiani 2000, Mech and Hallett 2001,
Wikramanayake et al. 2004). Alternatively, a more nomadic species relying on
unpredictable resources might benefit little from such an approach; efforts instead might
focus on preserving ecosystem function that creates the temporary habitat, or on
preserving a mosaic of geographically widespread sites for use (Woinarski et al. 1992,
Frederick et al. 1996, Roshier et al. 2002). While an understanding of spatial behavior
and habitat use is generally recognized as important to conservation, this has proved to be
technically challenging for vagile animals with large spatial requirements (Mauritzen et
al. 2001, Roshier et al. 2002).
Wood Storks (M~ycteria amnericana, Ciconiiformes) are large, highly mobile wading
birds that capture aquatic prey that pass through their open bills as they slowly wade
through shallow water (Kahl and Peacock 1963). The stork's foraging technique is
effective in shallow water where prey are concentrated, but works less well in deeper
water where prey are dispersed (Kahl 1964, Gawlik 2002). Appropriate foraging
conditions for Wood Storks are therefore highly dependent upon the interplay of water
depths and prey densities, and are by nature ephemeral and irregularly distributed across
the landscape both spatially and temporally (Hoffman et al. 1994). Because appropriate
foraging conditions are often short-lived (days to weeks), storks typically require a large
home range and must frequently change foraging locations (Erwin 1983, Fleming et al.
1994, Hoffman et al. 1994).
Adult Wood Storks are generalists, commonly use a variety of wetlands for
foraging, including impoundments and inundated agricultural fields (Sykes and Hunter
1978, Browder 1984, Gawlik 2002). Coulter and Bryan (1993) found that adult storks
from the Birdsville colony in east-central Georgia foraged more frequently than expected
in open habitats such as ponds and marshes compared to hardwood and cypress swamps.
Pearson et al. (1992) and Gaines et al. (1998) found that foraging storks in coastal
Georgia used freshwater habitats more frequently than palustrine habitats compared to
availability. Pearson et al. (1992) also found that upland habitats were used less
frequently compared to availability. Each of these habitat-use studies were conducted
during the breeding season.
Little is known about habitat-use outside the breeding season, particularly for
juvenile storks. The lack of information is largely due to the high mobility and low
re-sighting potential for banded birds across their large range (Bancroft 1992, Coulter et
al. 1999, Saether and Bakke 2000). In other wading birds, survival during nonbreeding
periods has been shown to play an integral role in population regulation (North 1979,
Kanyamibwa et al. 1990, Cezilly et al. 1996, Cezilly 1997). Understanding the
behavioral responses of Wood Storks to local environmental conditions during
nonbreeding periods is essential, as habitat use is probably important for survival.
An intensive color-marking of storks in the 1970s showed that juvenile storks
fledging from southern Florida colonies exhibited rapid postfiedging dispersal across
Florida, Georgia, Alabama, and South Carolina upon the onset of the rainy season (May-
June). Juveniles from the Everglades were found to disperse further north than
conspecifies hatched in central and north Florida, with most Everglades storks resighted
in central Florida, coastal Georgia and South Carolina. Only 2 of 1589 marked juveniles
(<0.01% of all resightings) were relocated outside these states, with one bird resighted in
west-central Alabama and subsequently seen in east-central Mississippi with another
tagged conspecific. Banded storks then returned to south and central Florida during
winter months (Nov-Feb). Despite the large sample, little information was gained about
the migratory nature of this species, their movement patterns, or the general mechanisms
they use to make movement decisions.
Although Kushlan (1981) identified storks as migratory, the evidence was only that
they left southern Florida after breeding. More recently, Coulter et al (1999) did not
consider Wood Storks to be a true migratory species, and their movements were thought
to be defined only as a response to local environmental conditions (Coulter et al. 1999).
Adult storks have been identified as moving north from the Everglades after large nesting
failures when no nests are initiated, and prior to the beginning of the summer rainy
season (Coulter et al. 1999). Although large northward movements by juveniles were
identified in the 1970s, they were considered an example of postfiedging dispersal that is
typical of many birds, including ciconiiform species.
In my study I focused on the movements and habitat use of juvenile storks using
satellite telemetry. Since storks do not begin breeding until their third or fourth year
(Hancock et al. 1992, Coulter et al. 1999), and so the young birds I studied here were not
constrained to remain in one location for breeding purposes. I hypothesized that juvenile
Wood Storks would exhibit predictable seasonal movement patterns as seen in the
banding study, not just track resources at the local level.
First, I predicted that storks would initially move into local wetlands upon leaving
the natal colony. Local foraging areas near the colony are likely important during the
first weeks when storks are learning to fly and forage on their own. Local foraging areas
for the tagged birds included the wet prairies within Everglades National Park and the
nearby Water Conservation Areas. Second, I predicted that storks would move north into
northern Florida, Georgia, Alabama, and South Carolina for the summer, as was recorded
for banded storks in the 1970s (Coulter et al. 1999). Finally, I predicted that storks would
leave their summer locations and spend the winter months in southern Florida as
previously described (Bancroft et al. 1992, Coulter et al. 1999).
Based on the information known for adult storks, I also hypothesized that juveniles
would exhibit nonrandom use of habitat, and would prefer shallow, periodically
inundated wetland sites more often than upland or residential habitats. Habitats that are
at least periodically inundated include wetlands, agricultural and cultivated areas. Of
these inundated habitat types, I predicted that storks would use wetlands more often than
I studied movements of young birds originating from the Tamiami West (TW,
N25o45.31, W80o31.90, Figure 3-1) colony, in Everglades National Park, Miami-Dade
County, Florida as this colony was most accessible of all colonies in the Everglades
ecosystem, and had consistently hosted a large number of nesting Wood Storks (>400
pairs) in recent years. Nearly all nests in TW were built in the canopy of Pond Apple
(Annona glabra), although a few nests were located in Willow (Salix caroliniana). I
visited colonies on foot during early morning hours between March (maj ority of nests
incubating) through the end of all nesting in July.
After high levels of abandonment and mortality in TW in 2003, I placed an
additional 5 transmitters on juvenile storks in late May in the Martin County Spoil Island
2 colony MC2, N27 1 1.40, W80 1 1.27), located along the Atlantic coast of Florida just
south of Sewalls Point, Martin County, Florida (Figure 3-1). In 2003, MC2 was a mixed-
species wading bird colony with approximately 50 storks nesting in red mangrove
(Rhizophora mangle) and sea grape (Coccoloba uvifera). Satellite transmitters were
deployed in late May on five juvenile storks hatched in this colony.
Nestling storks are capable of flying by approximately 55 days after hatching.
However, juvenile storks typically remain in or in close proximity to the natal colony and
continue to be fed by their parents until at least 80 days (Coulter et al. 1999). Nestlings
were considered fledged only when they permanently left the colony. I refer to storks
aged 55-80 days as flighted.
Figure 3-1. Map of Florida depicting colony locations (triangles) where juvenile Wood
Storks were tagged in 2002 and 2003. The dark lines indicate county
After nestlings at TW reached 4-6 weeks of age, I randomly selected first-hatched
nestlings for inclusion in telemetry studies. I placed transmitter harnesses on 33 juvenile
Wood Storks between 4 and 6 weeks of age in TW between 26 April and 13 June 2002,
and on 34 juveniles in TW between 23 April and 16 May 2003. Storks were considered
to be at least 4 weeks of age when they had visible white contour feathers on the back and
coverts and primaries 5-8cm in length (Kahl 1962). In 2003, an additional 5 birds of
unknown hatch-order were tagged at MC2. Starting from the northern-most section of
my transects in TW and moving southward on subsequent visits, I attached transmitters to
the first chicks in marked nests (see Chapter 2) that were accessible and of an appropriate
age. Earliest-hatched nestlings were preferred over later-hatched nestlings to avoid the
problem of nonindependence of siblings and to control for biases related to hatching
order. In one case in 2002, the earlier-hatched chick was too mobile for capture, and the
later-hatched nestling was chosen instead. All nestlings were caught by hand on the nest
and were immediately hooded to reduce stress. Work in colonies took place only during
morning hours (06:30-11:00 EST), when thermal stress was lowest, and when the
possibility of interrupting feedings by adults was at a minimum.
Each captured bird was fitted with a backpack harness that carried a 10g VHF radio
transmitter (2002: American Wildlife Enterprises, Monticello, FL, USA; 2003: Model
All20, Advanced Telemetry Systems, Isanti, MN, USA) and a 35g solar-powered Argos
certified platform terminal transmitters (PTT) for satellite tracking (Microwave
Telemetry, Inc., Columbia, MD, USA). A detailed description of the harnessing method
can be found in Appendix A. The total weight of a Teflon (Bally Ribbon Mills, Bally,
PA, USA) harness, VHF transmitter and PTT did not exceed 3% of the Wood Stork' s
fledging mass (2-2.8 kg) in accordance with recommendations from the Office of
Migratory Bird Management, United States Geological Survey.
Grounded transmitters were those that showed evidence of the transmitter having
become immobile (stationary signal from PTT, mortality signal from VHF). Transmitters
collected from carcasses were either reused in the same year or refurbished by the
manufacturer and reused in the subsequent year. Because I experienced problems with
vultures separating the VHF transmitters from the PTTs on carcasses in 2002, I further
secured each VHF to its PTT with 2 machine screws in 2003.
Location information for all PTTs was obtained daily by email from Service Argos,
Inc. (Landover, MD, USA). The PTTs were programmed on a 10-hour on/24-hour off
cycle. Argos assigned each Eix to a location class (LC) based on their accuracy estimates.
Only locations with estimated accuracies of 11000 m (LC = 3, 2, or 1) were used in my
study (Service Argos 1996, Keating et al. 1991). All location data were managed in
Excel (Microsoft, Seattle, WA, USA) and analyzed in ArcView 3.3 or ArcGIS (ESRI,
Redlands, CA, USA). Movement patterns and habitat use were analyzed using Hooge
and Eichenlaub's (1997) Animal Movement Analysis extension for ArcView.
I tested for preferential habitat use of juvenile Wood Storks at two scales using
compositional analysis (Aebischer et al. 1993). First, I compared habitat used by each
bird (95% Eixed kernel density utilization distributions, UD) to total available habitat
within the entire range for all tagged storks. I defined the extent of the total habitat
available to tagged storks as the area within a minimum convex polygon of all telemetry
locations for all birds minus the areas covering the Atlantic Ocean and Gulf of Mexico.
Second, utilized habitat (telemetry locations) for each tagged bird was compared to its
available habitat within a 95% fixed kernel density utilization distribution, UD. The first
analysis examined general habitat preferences for storks in the context of their entire
range, while the second analysis examined habitat preferences within each stork' s
localized area of use (UD).
For each analysis, I tested the null hypothesis that habitat use was random with
respect to the habitat categories chosen. For each bird hatched in 2002 that survived at
least 3 weeks postfiedging, the log-ratios of the utilized habitat composition were
compared to the log-ratios of available habitat composition. If habitat use were found to
be significantly nonrandom, I tested for specific preferences by comparing proportional
use for all habitat types. To avoid using autocorrelated telemetry locations, a maximum
of one location per 24 hours per animal was used in this analysis. As storks are capable
of traveling across broad landscapes quickly, I assumed that locations separated by at
least 24 hours were biologically independent (Reynolds and Laundre 1990). When
multiple locations were available in a 24-hour period, the earliest, best quality
(LC 3>2>1) location was selected. Location data were collected from May 2002-
Proportional habitat use within 1km buffers of all locations ( x = 147.73 locations
per bird, SE = 18.93, range = 31-332) was pooled and averaged for each stork. Only
locations within the 95% fixed kernel UD were included in this analysis. I calculated
95% fixed kernel UDs using least squares cross validation to estimate the optimal
smoothing parameter (Silverman 1986; Worton 1989, 1995; Seaman and Powell 1996).
UJDs were standardized across individuals by determining a median optimal smoothing
parameter h at 95% fixed kernel UD levels during initial calculations (Worton 1995,
Churchill et al. 2002). Each stork' s UD was recalculated with the parameter set to the
To achieve linear independence of proportions, log-ratios of each used and
available habitat were created for each animal by dividing each habitat type proportion by
the proportion of upland forest and then taking the loge (Aitchison 1986). The habitat
type used as the divisor, upland forest, was randomly selected among all habitat types;
the specific habitat chosen does not influence the results as all habitat types are
proportional to one another in compositional analysis (Aebisher et al. 1993). To meet the
assumption of multivariate normality, I used Wilks' lambda (A) statistic to test for overall
habitat selection. Matrices composed of the differences between the log-ratios for each
animal were constructed for both used and available habitats. The A value, the difference
between the used and available matrices, was compared to a X2 distribution with D-1
degrees of freedom, (D = number of habitats). A matrix ranking habitat types was
created where ranks for each habitat type were assigned in order of use. If overall
selection was found, t-tests were used to assess differences among habitat type ranks
(Aebischer et al. 1993). Analyses were conducted using the statistical software R (R
Foundation for Statistical Computing).
I used 1995 vegetation coverage maps from the National Land Cover Data set
(United States Geological Survey). The National Land Cover Data were chosen because
they provide 30m2 TOSolution within a uniform habitat classification scheme across the
range of the focal storks (Florida, Georgia, Alabama, South Carolina, and Mississippi).
Similar habitat types were pooled to avoid statistical bias resulting from comparing large
numbers of unused habitat types (Aebischer et al. 1993). Twenty habitat types were
reduced to eight, with pooled categories listed in parentheses: 1) developed (low intensity
residential, high-intensity residential and commercial/industrial/ transportation), 2)
barren (bare rock/sand/clay, quarries/strip mines/gravel pits and transitional), 3)
shrubland, 4) herbaceous upland (grasslands/herbaceous), 5) cultivated
(orchards/vineyards, pasture/ hay, row crops, small grains, fallow, and urban/recreational
grasslands), 6) wetlandst~t~lt~t~lt~t~lt (woody wetlands and emergent herbaceous wetlands), 7) open
water, and 8) forest (deciduous forest, evergreen forest, and mixed forest).
Mann-Whitney U-tests were used with a Z-approximation for bivariate analysis of
movement data. Values are reported as mean + SE, and a significance level ofP I 0.05
was set a priori for all statistical tests.
In 2002, tagged birds were observed foraging with a few kilometers of TW
individually and in large mixed-age groups (50-150 individuals) composed of adult and
juvenile storks during and following fledging. Similar flocks were not noted in 2003,
perhaps due to higher water levels around the colony and fewer numbers of fledged birds.
After juveniles left the natal area, I received no indication that any of the tagged
storks traveled together. My ability to detect social relationships among tagged birds was
high since their movements were monitored daily, but individuals were rarely within
even 50 km of one another. This evidence is consistent with the idea that each tagged
bird's behavior was independent of other tagged birds, an important statistical
consideration. Many of these birds have frequently visited the same general areas
throughout the southeastern United States, though never simultaneously.
The mean known age of tagged storks to fledge from the colony was 81 days in
both 2002 (n = 14) and in 2003 (n = 5). In general, the birds hatched in 2002 (2002
cohort, 29 fledglings, mean fledge date = 9 June 2002) moved north through the large
local wetlands within the WCAs, Big Cypress National Preserve (Big Cypress), and
A.R.M. Loxahatchee National Wildlife Refuge (Loxahatchee, also known as WCA 1).
Within the first 3 weeks of fledging, 2 individuals (7%) visited ENP, 3 (10%) birds
visited Big Cypress, 17 birds (59%) visited WCAs 2 or 3, and 4 birds (14%) visited
Loxahatchee (Figure 3-2). Mean distance moved within the first 48 hours of fledging
was 60 + 1.6 km (n = 15). Within the first week, fifteen (52%) of the fledglings moved
into the extensive agricultural lands (Everglades Agricultural Area) surrounding Lake
Figure 3-2. Map with all locations of tagged birds from May 2002 October 2003 within
A) Loxahatchee National Wildlife Refuge, B) Water Conservation Areas 2
and 3, C) Everglades National Park, and D) Big Cypress National Preserve.
The initial movements of birds hatched in 2003 (2003 cohort, 16 fledglings, mean
fledge date 1 June) were quite different from those of the 2002 cohort. Very few birds
used the large local wetlands of the Everglades near the colony. Only two birds had
locations within WCA 3A, and both were immediately after fledging. No other locations
were identified within the other WCAs, ENP, Big Cypress, or Loxahatchee. Instead, all
birds in the 2003 cohort initially flew to the agricultural areas surrounding Lake
Okeechobee. Mean distance moved within the first 48 hours of fledging for the 2003
cohort was 109.5 + 3.6 km (n = 10) (Table 3-1). The initial flights by the 2003 cohort
were significantly longer than those of the 2002 cohort (z = 3.25, P = 0.0006).
Following these initial movements, birds from both years quickly moved into the
areas in which they then spent the remainder of the summer. I will refer to these areas
used during the period June to September as the storks' summer ranges. Of the 27 birds
that fledged in 2002, 11 (42%) remained in Florida for the summer of 2002. Although
mortality during the first three weeks following fledging was high for the 2003 cohort,
(47% of 17 birds died), a similar 44% of the 9 survivors remained in Florida for the
summer of 2003. In both years most of these birds summered around the edges of Lake
Okeechobee or further west along the Gulf Coast. These "western" birds were located
between Tampa and Fort Myers, with a concentration in the C.M. Webb Wildlife
Management Area southwest of Port Charlotte. The birds that did not remain in central
Florida for the summer continued moving north, spreading across peninsular Florida and
the coastal plains of Georgia, South Carolina, Alabama, and Mississippi (Figure 3-3).
Although individual movements were highly variable, 79% (n = 33) exhibited strong
seasonally-dependent movement patterns, which I will henceforth refer to as migrations.
In this paper, the term migration means "a regular round-trip movement of individuals
between two or more ... seasonal ranges" (White and Garrott 1990). Two birds from the
2002 cohort (8%) and 5 birds from the 2003 cohort (50%) did not demonstrate migratory
behavior, but instead remained in south-central Florida in the same area they moved to
In 2002, the tagged birds that left Florida did so in a roughly simultaneous way
during the second week of June. The rate of movement on the summer ranges was
significantly lower than the rate of movement during travel to the summer range
(z = 5.22, P < 0.0001, n = 23). The average rate of movement during the northward
migration for the birds in the 2002 cohort that exhibited migratory behavior (92%) was
43.4 & 4.0 km/d (n = 22), while their average rate of movement within the summer ranges
was 6.0 & 1.1 km/d (n = 24). The rate of movement during the northward migrations for
the birds in the 2003 cohort that exhibited migratory behavior (50%) was 53.0 & 4.2 km/d
(n = 5), while the average rate of movement within the summer range was
6.50 & 1.15 km/d (n = 9) (Table 3-1).
The northern migrations took an average of 12 days to complete (n = 22). On these
northern migrations, the birds moved an average of 388 42 km (n = 21, Table 3-1) from
their initial, local dispersal locations. In 2002, the number of days birds exhibited
0 ~ ~ i 30 60 90120Mioetr
Figur 3-.Mpo l oainpinsfrtge ueieWodSok n=4)fo h
-b etenMy202adJnur 04
Men niia AergeAverage Average Average
InitialAverage Movement Average Distance from Distance from
Aveage Southward Rate in Moeet Maximum Fledging Summer
Cohort Flight Northward Rate in.
Migration Summer Migration Dispersal Area Range to
Distance Migration Winter Range
Rate (km/d) Range Rate (km/d) to Summer Winter Range
(km) Rate (km/d) (km/d)
(m/d) Range (km) (km)
60 & 1.6 43.4 & 4.0 54.8 & 6.5 6.0 & 1.1 5.2 & 0.7 156 388 & 42 336 & 39
(n = 15) (n = 22) (n = 16) (n = 24) (n = 16) (n = 21) (n = 21) (n = 16
109.5 & 3.6 53.0 & 4.2 6.5 A 1.2 106 387 & 64
(n = 10) (n = 5) (n = 9) (n = 5) (n = 5)
First-year movement rates of tagged juvenile Wood Storks between fledging dispersal areas, summer ranges
na d winter ranges in 2002 and 2003
migratory behavior was not significantly different between birds that summered in FL
and those that left Florida (z = 0.668, P = 0.252, n = 22). The average rate of travel
during the northward migrations was greater for birds that established summer ranges
outside Florida compared to the rate of travel for the birds that summered in Florida in
2002, although this difference was not quite significant (z = 1.537, P = 0.062, n = 22).
During the migration period before birds established summer ranges, 11 birds
moved through Georgia, 8 through Alabama, 3 through South Carolina, and 1 briefly
crossed the border into North Carolina. A total of five birds eventually moved from
Figure 3-4. Migratory path and movements of satellite tagged juvenile Everglades Wood
Storks that summered in Alabama (AL) and Mississippi (MS) in 2002. Each
color represents a different individual (n = 6). The lines connect consecutive
location points obtained from satellite data.
Alabama into Mississippi, with the first bird arriving in Alabama the last week of June
2002. Fifteen of the 16 birds in the 2002 cohort that traveled outside Florida established
summer ranges outside of Florida: 2 (13%) in South Carolina, 7 (47%) in Georgia, and 6
(40%) in western Alabama/eastern Mississippi. The remaining bird established a summer
range in northeast Florida around Jacksonville. Unlike the 2002 cohort, which spread
across six southeastern states, the 5 birds that left Florida from the 2003 cohort all
established summer ranges in Georgia. These birds initially moved into Georgia between
12 June and 6 July 2003.
The tagged birds apparently did not travel together on their migrations, nor did all
of them follow the same route. In 2002, three birds left southern Florida and migrated
north through the west-central portion of peninsular Florida, turning northwest into
Alabama once they reached the Florida panhandle. Two other birds from the same
colony-year cohort arrived at the same destination, but followed a coastal path through
Florida along the Gulf of Mexico before making their way north into Alabama. All five
birds remained in Alabama or moved into northeastern Mississippi for the remainder of
the summer (Figure 3-4). These birds then established summer home ranges along the
Tennessee-Tombigbee Waterway (Tenn-Tom) in Alabama and Mississippi. An
additional six birds spent most of their summer (June-September) in Georgia in 2002
(Figure 3-6). Of these, two migrated north along the Gulf Coast of Florida, two along the
Atlantic Coast, and two directly through the center of peninsular Florida after leaving the
Figure 3-5. Migratory pathway of satellite juvenile Wood Storks tagged in Florida (FL)
that summered in Georgia (GA) in 2002. Each color represents a different
individual (n = 7). The lines connect consecutive location points obtained
from satellite data.
By the beginning of November 2002, all birds located outside of Florida had
moved back south into central and southern Florida (Figure 3-6), where they remained
through mid-May 2003. Three of the five birds from the 2003 cohort that established
summer ranges in Georgia died before returning south for the winter, while another died
in Florida immediately following the southward migration. Following relatively rapid
movements of the 2002 cohort during the southward migration ( x = 54.8 & 6.5 km/d,
n = 16), daily movement distances decreased markedly in winter (x = 5.2 & 0.7 km/d, n
= 16, Table 3-1). I will refer to these areas of use from approximately November 2002 to
May 2003 as the birds' winter ranges. Southwest Florida around Lake Okeechobee and
Figure 3-6. Locations of 17 juvenile Wood Storks from Nov 2002 April 2003. Stork
locations were concentrated in southwestern Florida. ENP = Everglades
National Park and WCAs = Everglades Water Conservation Areas, and
BCNP = Big Cypress National Park. The pink areas are highly urbanized
zones. The light blue patches with gray borders indicate conservation areas.
along the Gulf Coast between Tampa and Ft. Myers was the most heavily used wintering
areas for these juvenile birds.
The 2002 cohort remained in south and central Florida for most of the spring and
summer of 2003. Although the 2002 cohort did begin moving north again by late May
2003, only 3 of the remaining 14 live birds (12%) left Florida during the summer of 2003.
All three birds returned to the same summer range (successive summer ranges visually
overlapped by at least 75%) they had used in 2002: one to Georgia, and two to the Tenn-
Tom region of Alabama and Mississippi. All of the birds that summered in Florida
returned to those same areas in 2003 where they had been in 2002. In total, 82% (n = 11)
of the birds demonstrated fidelity in their 2nd year by returning to the same summer range
established in their first year.
The average total distance moved during the second year (summer 2003) northern
migrations by the 2002 cohort was 241 & 38 km (n = 8). Total distances moved during
migrations were calculated from the last location prior to accelerated travel rates to the
location where movement once again returned to a lower travel rate. The distance
traveled to the summer locations did not differ significantly for the 2002 cohort between
their first and second years (z = 0.70, P = 0.23, n = 7). The entire 2002 cohort returned to
south/central Florida by mid October in both 2002 and 2003.
The rate of movement for the 2002 cohort during the 2nd Summer was similar to that
during the first summer, at 5.4 & 0.71 km/d (n = 11). The average maximum rate for each
individual during either the summer or winter migratory period was 156 km/d for the
2002 cohort (n = 21) and 106 km/d for the 2003 cohort (n = 5) (Table 3-1). The
maximum rate of travel for any individual was 184 km/d, recorded for a bird during its
first-year summer migration from southern Florida to Alabama. Although 79% (n = 33)
of all birds that survived at least 3 weeks of age exhibited migratory behavior, 2 birds
from the 2002 cohort and 5 birds from the 2003 cohort did not (i.e., they stayed in south-
central Florida in the same region they moved to initially upon fledging). At no time
during the 18 months following fledging did any of the 2002 cohort spend more than 1
day within 20 km of its natal colony.
Table 3-2. Simplified ranking matrix of habitat preferences for juvenile Wood Storks of the 2002 cohort based on comparing
proportional habitat used with proportional habitat availability across the entire area used by all tagged storks
Herbaceous Upland Rn
Open Water Developed Barren ShrublandCrp WelnsRk
Upld r~sWtands Forest
Open Water +++ +++ +++ ---- --- --- 3
Developed -+ +++ ---- --- --- 2
Barren --- -+++ --- --- --- --- 1
Shrubland --- --- --- --- --- --- --- o
Upland Forest +++ +++ +++ +++ +++ --5
Wetlands Combined +++ +++ +++ +++ +++ + + 7
Herbaceous Upland + + +++ +++ --- --- --- 4
Cultivated/Planted +++ +++ +++ +++ +++ -+ 6
Signs indicate if a row habitat was used more (+) or less (-) than a column habitat relative to availability. A triple sign
indicates a significant deviation from random at P < 0.05. Ranks are based on the number of significant differences.
Habitat Use versus Availability
Habitat use (area within 95% UDs) differed significantly from habitat availability
(MCP of all telemetry locations) across the entire range of tagged storks (A = 0.50, 27 =
14.07, P = 0.027). The ranking matrix for habitat use indicated use of Wetlands >
Cultivated Lands > Upland Forest >>> Herbaceous Upland > Open Water > Developed >
Barren >>> Shrubland. Wetlands, Cultivated, and Upland Forest habitats were
preferentially selected over all other habitat types while Shrubland was used significantly
less than all other habitat types in relation to availability (Table 3-2).
Habitat use (telemetry locations) did not differ significantly from habitat
availability within the 95% UDs (A = 0.57, 27 = 12.67, P = 0.081), although the
marginally significant result suggest that habitat use was not random. The ranking matrix
for habitat use within the 95% fixed kernels indicated use of Cultivated Lands >
Herbaceous Uplands > Wetlands >>> Upland Forests >>> Shrubland> Barren >
Developed > Open Water. Cultivated Lands, Herbaceous Uplands, and Wetlands were
all used significantly more than all other habitat types (Table 3-3).
This was the first study to monitor the movement patterns and habitat use of a
robust sample of juvenile Wood Storks at the landscape scale over multiple seasons, and
the only study to date to focus on juvenile movement behavior. Although I had predicted
that storks would heavily use the local wetlands in southern Florida following fledging,
this was only partially true in 2002 and not evidenced at all in 2003. In 2003, the above
Table 3-3. Simplified ranking matrix of habitat preferences for juvenile Wood Storks of the 2002 cohort based on comparing
localized proportional habitat use with proportional habitat composition within 95% fixed kernel utilization
di stributi ons
OpnWater Developed Barren Shrubland Uplands Crops Wetlands Forest Rank
Open Water ------ --- --- -
Deeloped + --- --- --- --- --- 1
Barren + + ---- --- --- 2
Shrubland + +++ + --- --- -- 3
Upland Forest + +++ + +++ --- --- --- 4
Wetlands +++ +++ +++ + --+++ 5
Herbaceous Upland +++ +++ +++ +++ -+ +++ 6
Cultivated Lands +++ +++ +++ + + + +++ 7
Signs indicate if a row habitat was used more (+) or less (-) than a column habitat relative to availability. A triple sign
indicates a significant deviation from random at P< 0.05. Ranks are based on the number of significant differences.
average water levels in WCA 3A, WCA 3B, and ENP (Sklar 2003) probably precluded
the development of suitable foraging habitats near the colony throughout much of the
nesting season. The lengthy first-flights were likely to have been energetically costly to
the young, inexperienced birds and may have dramatically impacted the survival of the
2003 cohort (Bryan et al. 1995).
Following the initial movements, two periods of high mobility were identified for
the storks in both years: 1) rapid dispersal north from southern Florida in June, followed
by 2) a return to central and southern Florida in September/October. These patterns,
observed in both 1st and 2nd year birds, matched my predictions and confirmed the
previous findings described in Coulter et al. (1999).
In both years, the movement of tagged storks out of southern Florida coincided
with the advent of the rainy season (May-June). The only exception was a second-year
bird that remained in the metropolitan area near Fort Lauderdale from December 2002
through January 2004, and probably used a unique niche among urban ponds and canals.
The overwhelming evidence from my study and from previous work implies that habitat
conditions during the rainy season in southern Florida are highly inappropriate for storks.
Storks in the Llanos of Venezuela and the Usumacinta wetlands of southern Mexico also
leave the nesting grounds during the raining season (Coulter et al. 1999).
In general, rising water triggers abandonment of nesting by storks, and tends to
disperse foraging birds (Kahl 1964, Kushlan 1987, Frederick and Collopy 1989,
Frederick and Spalding 1994, Ramo and Busto 1992, Ogden 1994, Hoffman et al. 1994),
because rising water disperses prey. This mechanism suggests strongly that storks are
moving from the Everglades ecosystem of southern Florida northward during summer
months in search of better food availability. The pattern also suggests that young are
fledging at a time when they local foraging environment is largely hostile, which may
have ramifications for their survival.
Florida is obviously capable of supporting some storks during the summer months,
as approximately 43% of the tagged juveniles stayed in central Florida or northeastern
Florida in both years. Over half of the tagged storks moved to other states, flying with
elevated rates of travel past areas in central and northern Florida where other tagged
conspecifics established summer ranges. The results suggest that the availability of
adequate foraging habitats in summer may be limited in Florida, at least in some years,
and that the quality of foraging conditions in areas outside of Florida is worth the cost of
the lengthy flight over unfamiliar landscapes. The southern coastal plain is typically
experiencing a drying pattern during summer months, the opposite of conditions in
In my study, 82% of juvenile storks exhibited circannual movement patterns,
returning seasonally to specific areas within Florida, Georgia, Alabama, and Mississippi
in summer after wintering in southern Florida. This demonstrates evidence of migratory
behavior, with rapid, predictable, biannual movement patterns, and philopatry to defined
areas within a given season. The European White Stork (Ciconia ciconia) is migratory
(Liechti et al. 1996, Berthold et al. 2002, Chemnetsov et al. 2004), and the Wood Stork's
congeners, the Yellow-billed Stork (M~ycteria ibis), Painted Stork (M~ycteria
leucocephala), and Milky Stork (M~ycteria cinerea), all display either migratory or
nomadic behavior (Hancock et al. 1992).
None of the tagged storks traveled together. This result was interesting considering
that many of the young birds fledged from adj acent nests and had plenty of opportunity to
develop social relationships while in the colony. Storks are known to exhibit social
foraging, nesting, roosting and strongly flocking (Kahl 1972, Comer 1985, Coulter and
Bryan 1993), and the birds I tracked almost certainly socialized with other storks. It is
possible that some juvenile Wood Storks followed adult storks during migrations, which
would explain the rapid, direct movements to the summer ranges. In a recent
displacement experiment, Chernetsov et al. (2004) found that naive juvenile White Storks
that were separated from adults did not exhibit expected autumnal migratory behavior.
Chernetsov et al. (2004) suggested that White Storks, and perhaps other soaring migrants,
rely on social interactions with experienced conspecifies during their first migration.
Dispersing juvenile storks demonstrated high Eidelity to their summer ranges, with
82% of the tagged storks returning to the same areas in the 2nd Summer. The summer
ranges did not overlap completely between years, however, indicating that their specific
movements within a given season varied. Given what is known about the ephemeral
nature of foraging conditions for this species, it seems likely that the birds locally shifted
locations as resources were depleted and new foraging areas became available.
Despite the large percentage of birds from the 2002 cohort returning to the same
summer ranges in their second year, the spatial distribution of tagged birds was not
consistent between the two cohorts. In 2002, tagged storks spread across Hyve states,
while in 2003 the 5 birds that left Florida only established summer ranges in Georgia.
This apparent shift in distribution to only 2 states suggests that first-year summer ranges
may be established based on a number of factors. I hypothesize that juvenile storks may
initially establish their first-year summer range based on environmental cues and/or adult
behavior, while in subsequent years prior experience may play a greater role.
Similar seasonal movement patterns have been noted in other Wood Stork
populations. In the United States, thousands of storks in the United States annually
converge into Texas, Arkansas, Louisiana and the lower Mississippi floodplain in the
summer months. Large numbers of storks have been observed flying north along the
Gulf Coast of Mexico in June (Coulter et al. 1999), and are consistently seen soaring
south through Veracruz, Mexico (up to 4,000-5,000 per day) during peak periods of fall
raptor migration (Weidensaul 1999).
Of 1589 nestlings banded in southern Florida, J. Ogden (unpubl. data, study cited in
Coulter et al. 1999) could calculate crude movement rates for only six birds from
southern Florida. Movement rates for 5 of the birds ranged from 10.0-20.8 km/d, while 1
stork averaged 50.0 km/d. For juvenile birds followed directly by aircraft, estimates
ranged between 35 and 48 km/h (n = 5). With a minimum of six hours of flying time per
day, Ogden estimated that the juveniles could travel 210-288 km/d (Coulter 1999).
Adults are known to commonly travel 50 km one-way from a colony during foraging
flights, although a maximum of 130 km one-way has been recorded (Browder 1978;
Clark 1978; Kushlan 1986; Bryan and Coulter 1987; J. Ogden, unpublished data).
By comparison, the maximum rate of travel recorded for any stork in the current
study was 184 km/d, with the average maximum rates during migration at 156 km/d
(2002 cohort) and 106 km/d (2003 cohort). Although these values are accurate, they
must be considered minimum travel rates since it is not clear how many hours of actual
travel were involved. Based on minimum travel rates estimated from this and Ogden's
study, it is likely that storks may spend at least 6 hours a day in flight during peak
migration periods (Coulter et al 1999).
Across the entire range of tagged storks, habitat use differed significantly from
habitat availability (P = 0.027). The range of tagged storks was consistent with the
known range of the U. S. breeding population of storks (Coulter et al. 1999). From the
eight habitat types I used for analysis, storks showed the strongest selection for landscape
mosaics dominated by wetlands, cultivated lands and/or upland forest in relation to their
availability. The lack of significant differences in use among the top three habitat types
may indicate (1) the high degree of heterogeneity within the landscape, (2) the lack of
resolution of the telemetry data, and/or (3) that the fairly broad habitat classifications may
have obscured biologically important habitat differences.
These Eindings partially match my prediction of greater use of periodically
inundated habitats (wetlands and cultivated lands), except for the Einding that upland
forests were preferred. Storks commonly use hydric forested habitats like bottomland
hardwood forests for roosting (Pearson et al. 1992, Bryan et al. 1995) and nesting
(Coulter et al. 1987, Coulter and Bryan 1993, Pearson et al. 1993, Rodgers et al. 1996,
Coulter et al. 1999). The storks in my study may have spent relatively more time
roosting compared to foraging, which might explain the heavy use of forested habitats.
Storks may also have been using small isolated streams or wetlands within a denser
mosaic of upland forest. If this were true, the scale of 1km buffering radius around each
telemetry location may have overstated the importance of forests to these birds. Without
more precise location information, it is difficult to determine the actual role of upland
forests in stork habitat needs. It is clear, however, that storks do prefer habitats that occur
in matrices dominated by upland forests; for management purposes this is an important
I also looked at habitat use relative to availability within the 95% UDs specific for
each of the tagged birds. I found strong, though not significant, evidence for habitat
selection (P = 0.081) at this localized level. At this scale, storks showed significant
preference for landscapes dominated by cultivated lands, herbaceous uplands and
wetlands as compared to the other habitats. In addition, landscapes dominated by upland
forest were selected significantly more often than landscapes dominated by shrubland,
barren, developed, or open water habitats. Although storks showed preferences for
wetlands at both the general and local scales, there was no evidence to validate my
prediction that wetlands are preferred over other inundated habitats such as agricultural
and cultivated lands. Again, there is the potential problem that the scale at which I
identified use (1 km buffers around telemetry locations) was inappropriate if storks were
choosing habitats at a smaller scale.
In general the tagged birds avoided urban areas at both the regional and local
levels, except for one bird from the 2002 cohort that settled in the metropolitan area near
Ft. Lauderdale from December 2002 present. Although the birds were often located
just beyond the periphery of a town or city, they were infrequently found within high
intensity residential or commercial areas.
Storks are quite capable of moving large distances through the air, and the concept
of physical or man-made barriers to their movement (such as roads) does not apply in the
traditional sense (Meffe et al. 1997). One potential restriction to their range was seen in
that they did not move farther west than eastern MS, despite the fact that western states
hosted large numbers of storks in summer months (Hancock et al. 1992, Coulter et al.
1999). This pattern is consistent with the findings for juvenile storks from southern
Florida in the 1970s (Coulter et al. 1999). The tagged birds also generally avoided
coastal wetlands, traveling inland instead. This was unexpected, as storks commonly use
estuarine marshes for both foraging and colony sites in Georgia (Pearson et al. 1992,
Rodgers et al. 1996, Gaines et al. 1998). I saw no indications that the storks migrated
over the Atlantic or Gulf of Mexico.
It is known that the Wood Stork breeding range increased across the southeast in
the 1980s and 1990s (Ogden 1994, Rodgers and Schwikert 1997), though the historic
breeding range will probably never be known. The general range of movements of
juvenile storks reported here were consistent with the results of J. Ogden's tag study
(unpubl. data, cited in Coulter et al. 1999). A true comparison of Ogden's study with this
one is problematic as tag-resighting rates were generally low, and resighting rates in
Alabama and Mississippi may have differed from those in Florida and Georgia.
Nevertheless, there is evidence to indicate an overall increase in stork use in Mississippi
Only 2 of 66 (3.0%) storks banded in southern Florida in Ogden's study were
resighted in Alabama or Mississippi, contrasted with 8 of 29 (27.6%) fledged birds in
2002 that traveled to and established summer ranges in these two states (Ogden unpubl.
data). Since the 1960s, there has been a large increase in the number of storks reported at
both the Noxubee National Wildlife Refuge, Mississippi and along the Tenn-Tom in
Alabama and Mississippi, many of which likely originated from southern Florida
populations (Richardson 2003).
In both this and Ogden' s study, the Tenn-Tom region of west-central Alabama and
east-central Mississippi was the most heavily used area in these states. Twenty-one
percent of tagged, fledged birds used this waterway in 2002. Construction and filling of
lakes along the Tenn-Tom during the 1970s and 1980s destroyed almost 14,000 ha of
bottomland hardwood forests (McClure and Connell 2001), which may explain the
relatively low use of this area by juvenile storks in Ogden' s study. The first large
concentrations of storks noticed by Tenn-Tom biologists in this area were during the late
1980s, after maj or construction on the waterway was completed (G. Houston unpubl.
data). The US Army Corps of Engineers undertook additional wildlife habitat mitigation
and replanting efforts in the mid 1990s however, including the acquisition of 35,000 ha
within and surrounding the Tenn-Tom. Many of these habitats are now being exclusively
managed for wildlife. It is very likely that stork movements in Alabama and Mississippi,
and particularly along the Tenn-Tom, have increased dramatically in recent years in
response to the land-use changes (Richardson 2003).
Until recently, storks sighted in Mississippi in summer months were assumed to
have originated from the Mexican population (Coulter et al. 1999). My study documents
heavy use of the area by the population breeding in the southeastern U. S. This area in
eastern Mississippi appears to be an important summering location for Wood Storks,
where birds spent up to '/ of their year. I recommend modifying the United States Fish
and Wildlife Recovery Plan for the Wood Stork to include Mississippi in its list of
southeastern states where storks are protected under Federal Law.
The longevity and easy detectability of stork colony locations make preservation of
nesting sites a good conservation strategy for the species (Frederick and Ogden 1997).
However, based on their extensive use of a wide variety of landscapes across the
southeastern United States during much of the year, concentrating recovery efforts solely
on colony locations may not offer adequate protection to the species. Additional
strategies for identifying and protecting important stork habitats outside the breeding
season have proven more difficult to determine. The heavy-use areas, movement
patterns, and migratory behavior of juvenile storks have now been partially identified in
my study, although the inaccuracies involved in the type of satellite telemetry used here
have made it difficult to identify which specific wetlands should be targeted for
Additional satellite transmitters equipped with GPS location capabilities were
deployed on juvenile storks in the spring of 2004 by the University of Florida. These 45
gram solar-powered GPS satellite transmitters (Microwave Telemetry, Inc., Columbia,
MD, USA.) are accurate within 18 m of the true location, which will offer significantly
better quality location information than the transmitters used in my study (1 km
accuracy). This is a necessary next step for determining stork movement patterns and
habitats needs. Identifying specific parcels of land used by tagged storks will allow for
the development of a predictive habitat model for the species.
The storks' heavy use of landscapes dominated by cultivated lands offers a
challenging conservation problem. Foraging within flooded agricultural lands or along
drainage ditches may pose serious health risks to the birds (Parsons et al. 2000). Most of
these agricultural lands are privately owned, making it more difficult to implement and
enforce broad conservation initiatives. Once exact foraging locations within agricultural
landscapes are identified via improved telemetry data, potential health hazards should be
Additional comparisons of juvenile and adult stork movement patterns should be
conducted to identify whether the patterns observed in my study were unique to juveniles,
or if adult storks also undergo predictable seasonal migrations. By June 2004, 10 storks
from the 2002 cohort and 1 from the 2003 cohort remained alive. The transmitters used
in my study are guaranteed to last at least three years and possibly more, so there is good
potential to obtain information on adult movement behavior within the next few years
using these same individuals.
Further analyses of movement patterns of storks hatched outside the Everglades
system are necessary for establishing better conservation and management plans for the
entire U.S. population. The broad differences between movement behaviors by the 2002
and 2003 cohorts demonstrated the necessity of monitoring stork movements over
multiple years. Continued monitoring of these animals will allow managers to assess the
full range of stork movements and allow for further hypothesis testing.
Occasional favorable years of high productivity are assumed to compensate for
species, like Wood Storks, which may face many years of poor nesting success (Saether
et al. 1996). The numbers of nesting attempts by storks have risen in the past decade,
indicating some level of recovery for the U.S. population (Ogden 2002). Although the
species' long lifespan may offset the lengthy investment (four months) of raising young
and the infrequency of successful nesting, it may also hinder our abilities to identify
gradual perturbations to the overall population. My study indicated that in a fairly
successful year (2003, Gawlik and Crozier 2003), in which the storks faced high
abandonment rates but a portion of young did fledge, none of those birds are likely to
survive to reproduce. Even in what is generally considered a highly successful breeding
year (2002, Oberhofer and Bass 2002), where most nests survived to fledge young, I
estimated that only 17% may make it to breeding age. Relying solely on nesting attempt
records or numbers of fledged young, factors that will be used for delisting this federally
endangered species (U. S. Fish and Wildlife Service 1997), may grossly overestimate the
success of the species. A greater understanding of postfiedging survival rates and their
role in population regulation is therefore needed.
In both years of the study, mortality rates were highest in the first months following
fledging. Young storks in the 2003 cohort were largely unable to practice important
foraging skills prior to fledging due to high water levels. This inexperience probably
contributed significantly to the 60% mortality rates observed during the first month after
fledging. Good management for storks in the Everglades should include maintaining
adequate foraging conditions (e.g., shallow and declining depths, open sparsely vegetated
habitat) within 60km of colony sites throughout the nesting season, especially leading up
to and including the time of fledging.
The ability of storks to move across large tracts of largely unsuitable habitat is
probably an adaptation to living in a highly variable environment where resources are
patchily distributed and unpredictable. Storks may spend up to four years away from
colony sites prior to breeding, and half of the year away once they reach reproductive
age. Based on their extensive use of a wide variety of landscapes across the southeastern
United States during much of the year, concentrating recovery efforts solely on colony
locations may not offer adequate protection to the species. Additional comparisons of
juveniles and adult stork movement patterns should be conducted to identify whether the
movement patterns observed in my study were unique to juveniles, or if adult storks also
undergo predictable seasonal migrations. Further analyses of movement patterns of
storks born outside the Everglades system are also necessary for establishing better
conservation and management plans for the entire SE population.
The storks' heavy use of landscapes dominated by cultivated lands offers a
challenging conservation problem, as foraging within flooded agricultural lands or along
drainage ditches may pose serious health risks to the birds (Parsons et al. 2000). The
private ownership of most agricultural lands may also make implementation and
enforcement of broad conservation initiatives difficult.
The large variation in survival rates, effects of health on survival, and movement
patterns between years demonstrated the necessity of monitoring this species over
multiple years. Continuing similar research with juvenile storks will enable us to fully
understand the interannual variability in survival rates and the factors affecting survival.
Conducting similar studies with adult storks would also provide much needed
information on longevity, age at first breeding, and variability in survival rates. Long
term monitoring and a functional demographic model will allow managers and biologists
to understand the population dynamics of Wood Storks, enabling the development of
better conservation strategies.
HARNESS DESIGN AND EFFICACY OF USING SATELLITE TRANSMITTERS
Larry Bryan of Savannah River Ecology Lab developed a backpack harness for
satellite transmitter placement on adult Wood Storks in which he attached four pieces of
Teflon ribbon to a satellite transmitter, fitted each harness to the exact dimensions of the
bird in hand, and secured the ribbon pieces on the bird's chest with a metal grommet (L.
Bryan, unpubl. data). I modified Bryan's design by sewing two pieces of Teflon ribbon
to the transmitter prior to having the bird in hand. Each satellite transmitter had three
points of attachment: one centrally located on the anterior end of the transmitter away
from the antenna, and two located posteriorly on either side of the transmitter (Figure
A-1). Each end of a 43 x 1 cm piece of ribbon was looped through the anterior hook,
overlapping 3 cm on itself, and sewn using 2-gauge Nylon thread. A second ribbon, 45 x
1 cm, was looped through a side attachment hook and secured by doubling and sewing
(as above). All ends of ribbon and stitchings were further strengthened with a drop of
Dritz Fray Check (Prym-Dritz Corporation, Spartanburg, SC, USA), a liquid anti-raveling
agent. The harness dimensions were obtained from maximum body measurements of
adult male and female captive Wood Storks at Homosassa Spring Wildlife State Park,
The storks being tagged were not fully grown, presenting the problem of creating
a harness that would fit firmly on both adults and juveniles. Although juveniles approach
adult size by 4-6 weeks, they are noticeably smaller than adults, with culmen length at
fledging 50 mm shorter than those of adults (Clark 1978), and their pectoralis mass has
not developed fully due to relatively little opportunity for flight. To accommodate
growth of juveniles, I designed an adjustable backpack harness that would fit adults and
juveniles. The flexible harness concept was developed for White Ibises by J. Semones
(2003). For storks, I stitched a single '/ inch knit polyester elastic thread (56% polyester,
44% rubber) along the length of each Teflon ribbon. When stretched taut, the ribbon
easily expanded to its full length, however when relaxed, the elastic resulted in a mild
bunching along the length of the ribbon that held the transmitter in place more firmly on
With the hooded bird in hand, the anterior Teflon neck loop was slipped over the
bird's head and neck so that the transmitter rested centrally on the bird's mid-back
(Figure A-1). The unattached end of the side ribbon was then drawn under one wing,
looped once through the neck loop on the chest, and brought across the chest and under
the opposite wing. After ensuring flight feathers were not obstructed, I smoothed body
feathers around the harness, checked that the ribbon was lying flat on the bird's body,
looped the free end of the ribbon through the remaining unused side attachment point on
the transmitter, and stitched the free end closed in the manner previously described.
After minor adjustments for central placement of the transmitter on the back of the bird,
the point at which the two ribbons overlapped on the chest of the bird was also stitched to
ensure a better fit and prevent unnecessary sliding of the transmitter along the back until
the bird reached full size. New stitchings were further strengthened using a drop of liquid
anti-raveling agent. Each harness was double checked to ensure proper fit for the bird,
Figure A-1. A satellite (30g PTT) and radio (10g VHF) transmitter attached to a juvenile
Wood Stork using a Teflon harness. The neck loop was attached to the
anterior end of the transmitter away from the antenna (A), while the posterior
loop attached to the sides of the transmitter passed under one wing, through
the neck loop, and under the opposite wing (B). Elastic thread sewn in the
Teflon ribbons (C) allowed for an expandable yet snug fit to the bird until it
attained adult size.
after which I removed the hood from the bird and returned it to its nest. Each bird was
handled for approximately 45 minutes. Upon replacement in the nest, birds were visually
monitored to ensure they had adequately recovered to sit or stand in the nest.
Efficacy of Teflon Harnesses
Prior to fledging, storks were visually monitored on subsequent visits to ensure
that harness fit was not hampering movements or agility of the birds. There were no
indications that the harnesses altered behavior or movements or caused chafing, and
approximately 25 tagged individuals were observed flying in an apparently normal
fashion when disturbed from their nest or roost. There were no signs of wear on any
retrieved carcasses, although most were reduced to bones and feathers by the time of
retrieval due to high decomposition rates.
The Teflon harness functioned very well for affixing transmitters to sub-adult
storks. The mild elasticity of the harness allowed for additional growth of the juvenile,
provided a closer fit, and prevented the transmitter from sliding. Although the color of
recovered harnesses appeared moderately faded, the Teflon ribbons did not appear to be
damaged or to have lost their resilience in any way. Although several transmitters
recovered in the colony had torn or missing harnesses, I assumed these had been ripped
apart by vultures, not by the storks themselves. All transmitters recovered on carcasses
appeared fully intact and had caused no noticeable harm to the wearer (i.e., no body limbs
or foreign materials caught or abrasions on the body).
Efficacy of Satellite Transmitters
In 2002, three grounded VHF transmitters were detached from the PTT when
vultures scavenged the carcass, and these PTTs were not recovered. Despite taking
additional precautions to secure each VHF to its PTT with two machine screws in 2003,
in two known cases the VHF transmitters were detached from the PTT by scavengers. In
another case, a VHF transmitter was detached in the colony while the PTT remained on
the bird (unknown cause); I continued to receive PTT data for this bird for 14 months
As of 15 January 2004, I had relocated 7 PTT and 9 VHF grounded transmitters
deployed in 2002 and 15 PTTs and 18 VHF grounded transmitters deployed in 2003.
Three sets of transmitters in 2002 and nine sets of transmitters in 2003 were taken off
birds that died in sufficient time to be refitted with new harnesses and placed on
additional birds. The success rate of relocating grounded transmitters within the colony
was much higher in both years (2002: 67%, n = 6; 2003: 57%, n = 21) than relocating a
transmitter from a fledged bird (2002: 20%, n = 15; 2003: 38%, n = 16). Mortalities of
prefiedged birds were verified much more quickly while under daily monitoring in the
colony via VHF signals than those of fledged birds, where lengthy gaps between
transmissions of satellite data increased the uncertainty of mortality events. Overall for
both years, I recovered 25 of 55 grounded transmitters (45%).
I received location information on each bird an average of 7.0 times per week
(range 2. 1 19.2, SE = 1.4, n = 32) for 2002 birds and 9. 1 times per week (range 2.3 -
17.5, SE = 1.2, n = 28) for 2003 birds. I received fewer locations early in the season
prior to fledging, presumably due to poorer transmitting and battery recharging
conditions at nest sites beneath the tree canopy. These periods were also coincident with
the onset of the rainy season, which is particularly cloudy. I also received fewer good
quality fixes when birds remained in landscapes dominated by cypress forests for
In summary, the solar-powered 35g satellite transmitters used on all 72 birds were
ideally suited for this large, wetland species that spends much of its time foraging in open
waters or roosting in treetops. The additional attachment of a 10g VHF transmitter was
invaluable for retrieving the expensive PTTs from stork carcasses. Although I retrieved
only 45% of all transmitters from suspected mortalities, reusing recovered transmitters
increased my sample sizes by 10% in 2002 and 30% in 2003. Retrieving and
refurbishing 22 satellite and 27 VHF transmitters dramatically reduced overall costs.
REFERENCE MEASUREMENTS, MASS, MERCURY LEVELS, AND
HEMATOLOGY OF JUVENILE WOOD STORKS
Table B-1. Reference body measurements, mercury levels, and hematology of juvenile Wood Storks.
White Blood Cells (cells/mm3 x 103)
Heterophils (cells/mm3 x 103)
Eosinophils (cells/mm3 x 103)
Basophils (cells/mm3 x 103)
Lymphocytes (cells/mm3 x 103)
Monocytes (cells/mm3 x 103)
Heterophil/Lymphoevte ratio (H/L)
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Rebecca (Becky) Hylton developed her love of the outdoors while growing up in
rural Virginia, with her home nestled deep in the Blue Ridge Mountains. Her interest in
biology was encouraged and fostered by her unconventional high school biology teacher,
Barbara Kolb, who was the first to expect her to think, explore, and question as a
scientist. With the help and advice of her high school teachers, Becky achieved her
dream of attending college by receiving a 4-year scholarship to Hollins College in
Roanoke, Virginia, where she received a Bachelor of Arts degree in 1997. Her
charismatic undergraduate advisor, Dr. Renee Godard, was responsible for placing
binoculars in her hands, and introducing her to the wonders of avian ecology. Becky's
undergraduate internship at the University of Texas Marine Biomedical Lab in Texas and
her undergraduate honors thesis working with Indigo Buntings were instrumental in
guiding her future career choices. Upon graduation, Becky dove head first into the life of
field biology, working for nonprofit avian research organizations and universities across
the country, with her resume reading like a roadmap across the United States. Becky
j oined the Everglades wading bird proj ect in 2000, and began working on her Master of
Science degree with the University of Florida in the fall of 2001. Her love of birds and
dedication to avian conservation have only increased over time, and she is looking
forward to the new adventures awaiting her upon graduation.