AN ASSESSMENT OF SURVEY METHODOLOGY, CALLING ACTIVITY, AND
HABITAT ASSOCIATIONS OF WOOD FROGS (RANA SYLVATICA) AND BOREAL
CHORUS FROGS (PSEUDACRIS MACULATA) IN A TUNDRA BIOME
R. Nicholas Mannan, B.S.
A Thesis
In
WILDLIFE SCIENCE
Submitted to the Graduate Faculty
of Texas Tech University in
Partial Fulfillment of the Requirements for
the Degree of
MASTER OF SCIENCE
Gad Perry
Chair
David E. Andersen
Co Chair
Clint W. Boal
Co Chair
Fred Hartmeister
Dean of the Graduate School
May, 2008
Texas Tech University, Robert N. Mannan, May, 2008
ACKNOWLEDGEMENTS
All work was conducted under ACUC permit number 06021-05 and Parks Canada
research permit number Wap-2005-518. I thank Parks Canada, Wapusk National Park;
Texas Tech University Department of Natural Resources Management; the U.S.
Geological Survey, Texas Cooperative Fish and Wildlife Research Unit; and the U.S.
Geological Survey, Minnesota Cooperative Fish and Wildlife Research Unit for
providing funding and logistical support. The Eastern Prairie Population Canada Goose
Committee of the Technical Section of the Mississippi Flyway Council provided
logistical support for this project through the Nestor One field research camp, and M.
Gillespie (Manitoba Conservation) coordinated camp support. M. Reiter, C. Henneman,
G. Lundie, W. Souer, B. Olson, M. Jones, S. Maxson, B. Luebke, M. Miller, B. Nack, T.
Bishop, J. Huener, J. Lawrence, B. McCardle, and M. Roell assisted with data collection.
Gad Perry, David E. Andersen, and Clint W. Boal provided guidance and demonstrated
unending patience. David B. Wester provided integral statistical support. Finally, I thank
my family and office mates for their support in all matters.
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Texas Tech University, Robert N. Mannan, May, 2008
TABLE OF CONTENTS
ACKNOWLEDGEMENTS
ii
LIST OF TABLES
v
LIST OF FIGURES
vii
CHAPTER
I.
OVERVIEW
1
II.
AN ASSESSMENT OF ANURAN SURVEY METHODOLOGY IN A
TUNDRA BIOME
III.
5
Abstract
5
Introduction
6
Study Area
8
Methods
9
Results
14
Discussion
16
FACTORS AFFECTING CALLING ACTIVITY OF BOREAL CHORUS
FROGS (PSEUDACRIS MACULATA) AND WOOD FROGS (RANA
SYLVATICA) NEAR CAPE CHURCHILL, MANITOBA
28
Abstract
28
Introduction
29
Study Area
30
Methods
31
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Texas Tech University, Robert N. Mannan, May, 2008
IV.
Results
33
Discussion
34
HABITAT ASSOCIATIONS OF BOREAL CHORUS FROGS (PSEUDACRIS
MACULATA) AND WOOD FROGS (RANA SYLVATICA) IN A TUNDRA
BIOME
43
Abstract
43
Introduction
44
Study Area
46
Methods
47
Results
53
Discussion
55
LITERATURE CITED
72
APENDIX A
77
AUTOMATED RECORDER COMPONENTS
iv
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Texas Tech University, Robert N. Mannan, May, 2008
LIST OF TABLES
3.1
Results of a regression analysis of a linear mixed effects model
used to model wood frog call activity, near Cape Churchill,
Manitoba, Canada, 2007.
3.2
41
Results of a regression analysis of a linear mixed effects
model used to model boreal chorus frog call activity, near Cape
Churchill, Manitoba, Canada, 2007.
4.1
42
Mean values of habitat variables at detection and non-detection
sites for wood frogs and boreal chorus frogs near Cape
Churchill, Manitoba, 2006-2007.
4.2
60
Mean values of percent cover, vegetation height, tallest piece
of vegetation, pH, and TDS of triangulation locations and
corresponding breeding sites near Cape Churchill, Manitoba,
2006-2007.
4.3
61
Number of sites with and without anuran detections that
contained evidence of goose herbivory near Cape Churchill,
Manitoba, 2006-2007.
62
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Texas Tech University, Robert N. Mannan, May, 2008
4.4
Correlation coefficients and P-values (in parentheses) of
measured habitat variables at potential breeding sites of
boreal chorus frogs and wood frogs near Cape Churchill,
Manitoba 2006-2007 (n = 204).
4.5
63
Eigenvalues of a correlation matrix and the % variation of
habitat variables explained in models of habitat associated
with anuran locations near Cape Churchill, Manitoba,
2006-2007.
4.6
64
Results of a post-hoc MANOVA test for within-model
significance when predicting anuran presence near Cape
Churchill, Manitoba, 2006-2007 (n = 202).
4.7
65
Loading scores of the variables within components of
habitat models describing anuran locations near Cape Churchill,
Manitoba, 2006-2007.
68
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LIST OF FIGURES
2.1
Study plots near Cape Churchill, Manitoba, where anuran
surveys were conducted in 2006 and 2007.
2.2
22
The change in the numbers of Rana sylvatica detected
before and after broadcasting advertisement calls near
Cape Churchill, Manitoba, 2006-2007.
2.3
23
The change in the number of Pseudacris maculata detected
before and after broadcasting advertisement calls near
Cape Churchill, Manitoba, 2006-2007.
2.4
24
Difference in the number of Rana sylvatica detections made
by observers and using automated recorders near Cape
Churchill, Manitoba, 2006-2007.
2.5
25
The discrepancy between Pseudacris maculata detections
made by observers and using automated recorders near Cape
Churchill, Manitoba, 2006-2007.
26
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Texas Tech University, Robert N. Mannan, May, 2008
2.6
The percentage of broadcasts detected by automated recorders
conducted at 20 m increments along transects beginning at
automated recorders and traveling at bearings of 0, 90, 180
and 270 degrees, near Cape Churchill, Manitoba, 2006-2007.
3.1
Study plots near Cape Churchill, Manitoba, where anuran
surveys were conducted in 2007.
3.2
27
38
Mean and standard deviation of the number of anurans
detected as a function of (A) date, (B) time of day,
(C) temperature, and (D) relative humidity near Cape
Churchill, Manitoba, Canada, 2007 (□ = Wood frogs,
▲=Boreal chorus frogs).
4.1
39
Study plots near Cape Churchill, Manitoba, where
anuran surveys were conducted in 2006 and 2007.
4.2
59
The negative relationship between component one and
wood frog presence, depicted by a logistic regression line
near Cape Churchill, Manitoba, 2006-2007.
viii
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Texas Tech University, Robert N. Mannan, May, 2008
4.3
The negative relationship between component one and
wood frog presence, depicted by a logistic regression line
near Cape Churchill, Manitoba, 2006-2007.
4.4
67
Means and 95% confidence intervals of (A) average
vegetation height, (B) % cover by sedge and willow,
(C) average height of tallest vegetation, (D) TDS, and
(E) pH, with respect to evidence of goose herbivory near
Cape Churchill, Manitoba, 2006-2007.
5.1
Diagram of automated recorder components near
Churchill, Manitoba, 2006-2007.
5.2
78
Photograph of automated recorder components near
Cape Churchill, Manitoba, 2006-2007.
5.3
69
79
Control board for automated recorder near Cape Churchill,
Manitoba, 2006-2007.
80
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CHAPTER I
OVERVIEW
Two species of anurans, the boreal chorus frog (Pseudacris maculata) and
wood frog (Rana sylvatica), inhabit the tundra biome near Cape Churchill, Manitoba, and
potentially are susceptible to changes in vegetative structure and composition, caused
primarily by foraging geese and changes in climate. Both species of frogs have extensive
distributions. The wood frog inhabits areas within much of Canada and Alaska, but also
exists along the northeastern seaboard of the United States, through the Great Lakes
region and into the northern Midwest states (Stebbins 1951, USGS 2002). The boreal
chorus frog is the northernmost of the chorus frogs with a range extending from areas in
Arizona and New Mexico through the Midwest, north into Alberta, Ontario,
Saskatchewan, Manitoba, and parts of the Northwest Territories (Koch and Peterson
1995, USGS 2002).
Both species are common within their ranges and much is known about their life
histories (e.g., see Heatwole 1961, Berven 1990). However, both wood frogs and boreal
chorus frogs show considerable morphological and behavioral variation across their
respective ranges (Pettus and Spencer 1964, Berven 1990), and this variation may
influence the way they react to changes in climatic and other environmental
perturbations. For example, in contrast to other areas in which boreal chorus frogs and
wood frogs are found, there are few plants that provide cover or grow very tall in the
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tundra biome in northern Manitoba. Sedges (Carex aquatilis, C. rupestris, and C.
glacialis) and small willows (Salix planifolia, S. herbacea and S. brachycarp) are the
only plants that may provide the shelter and structure important to reproduction in frogs.
Thus, factors that affect tundra vegetation likely affect anurans inhabiting this region.
Two of the factors most likely to affect tundra vegetation along the west coast of the
Hudson Bay are changing climate and increased herbivory by geese.
Along the west coast of Hudson Bay, geese feed heavily on sedges. Over the past
two decades, mid-continent light geese [snow geese (Chen caerulescens) and Ross’s
geese (Chen rossii)] populations have increased at an annual rate of 5-7% (Batt 1997,
Jefferies and Rockwell 2002). Increased grazing has altered vegetation production as well
as the overall vegetative composition in some areas (Cargill and Jefferies 1989, Jefferies
and Rockwell 2002). Removal of sedges by foraging geese may impact anurans by
altering wetland structure and water quality. Reduction of sedges may remove the
necessary cover and tall vegetative structure integral for anurans to complete their life
cycle. Also, the removal of sedges may lower pH of the water at potential breeding sites,
a hydrological characteristic important to the survival of both wood frogs and chorus
frogs (Corn et al. 1989, Wikberg and Mucina 2002). Currently, the effects of goose
herbivory on anuran-habitat associations are unknown.
To assess anuran population status and monitor changes in anuran populations
inhabiting the tundra, efficient survey methodology is necessary. Established survey
methods for anurans include road-side surveys, listening stations, repeated surveys at
selected breeding areas, and counts of egg masses (Shirose et al. 1997, Crouch and Paton
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2000, USGS 2001, Weir et al. 2005). However, because most tundra landscapes are
relatively isolated and experience extreme climatic conditions, many standard anuran
survey methods are not be feasible or effective there. Both the relatively short time period
during which surveys can be conducted and the difficulty in reaching and supporting field
operations are two factors that complicate surveying anurans in the tundra.
Survey efforts in tundra ecosystems might be made more efficient in several
ways. The first is to increase the detectability of anuran species. Males of some anuran
species increase calling frequency after broadcasts of conspecific advertisement calls
(Wells and Greer 1981, Sullivan 1985). A positive response to broadcasted conspecific
advertisement calls could increase the efficiency of surveys, thus decreasing the number
of surveys necessary to accurately assess presence or absence. No information exists
regarding how wood frogs or boreal chorus frogs respond to broadcasted advertisement
calls.
Another possible approach to increase the effectiveness of anuran surveys is to
maximize the area surveyed. There are few roads in most subarctic and arctic tundra
landscapes, rendering roadside counts impractical. However, automated audio recorders
(hereafter automated recorders) have been used at anuran breeding locations to record
call activity (Penman et al. 2005); it may be possible to use a series of automated
recorders, placed at potential anuran breeding locations, to detect anuran presence and
effectively survey large areas.
Finally, high-latitude tundra landscapes experience extensive daylight during
short summers, providing a brief annual period for anurans to breed. Environmental
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Texas Tech University, Robert N. Mannan, May, 2008
variables such as light intensity have been suggested to affect the calling patterns of
anurans (Oseen and Wassersug 2002). Effective survey protocols should take advantage
of peak periods of calling, but currently it is unclear how weather and time of day affect
calling activity of anurans in the subartic and arctic tundra (e.g., see Andersen et al.
2005).
The following chapters address the issues discussed above. In Chapter I, I
evaluate the possibility of soliciting calls from non-calling anurans by manually
broadcasting conspecific advertisement calls as well as the use of automated recorders to
increase survey coverage. In Chapter II, I describe factors affecting the calling patterns of
anurans in a tundra biome. Finally, in Chapter III, I examine habitat selection and
associations of tundra-dwelling anurans with regard to vegetation, water quality, and
patches of vegetation affected by goose herbivory.
Throughout this thesis terminology remains consistent, but is redefined in each
chapter because each chapter is structured to stand alone as an independent manuscript.
This allows readers to understand individual chapters without reading the whole thesis.
All references are presented in a single section at the end of the manuscript.
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Texas Tech University, Robert N. Mannan, May, 2008
CHAPTER II
AN ASSESSMENT OF ANURAN SURVEY METHODOLOGY IN A TUNDRA
BIOME
Abstract
The tundra biome near Cape Churchill, Manitoba is being influenced by global
climate change and herbivory from an increasing population of light geese. These
environmental changes may impact anuran populations, although little is known about
population trends in anurans in the region. The isolation of the region may render
traditional anuran survey methods ineffective. I tested two methods of surveying for two
anuran species, boreal chorus frogs (Pseudacris maculata) and wood frogs (Rana
sylvatica). I solicited calls from non-calling anurans by manually broadcasting
conspecific advertisement calls, and I used automated audio recorders to increase survey
coverage. I detected 0.38 additional wood frogs per survey when broadcast calls were
employed, compared to surveys without broadcasts. I was unable to detect additional
boreal chorus frogs by broadcasting conspecific advertisement calls. Using automated
audio recorders, I was able to identify anuran presence in a radius of 100 m, but
detections of wood frogs were low compared to manual surveys. I suggest that broadcasts
of wood frog advertisement calls be implemented into surveys for wood frogs in the
tundra biome, and that additional research is necessary to determine whether solicitation
can be used to increase detection of other anuran species.
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Introduction
Surveys are integral to wildlife science and are applied in both research and
management in a variety of systems. Because of their wide applications, survey protocols
must be appropriate for the system under investigation. Design of survey protocols
should incorporate considerations of detection efficiencies as well as other abiotic and
biotic constraints within a particular region. Survey protocols should also be: (1)
consistent through time; (2) effective; (3) efficient; and if possible (4) comparable to
other surveys conducted in the same area or of the same species. Because of the diversity
of the applications and conditions under which surveys are conducted, survey protocols
are ideally regionally and species-specific.
The design of an ideal survey protocol is complicated. Often, particular protocol
attributes represent a trade-off between information quality and quantity. For example,
increasing survey intensity will likely yield a more accurate estimate of the abundance of
the species under investigation, but will also increase the time or funds needed to conduct
the survey. Ultimately, increasing survey intensity usually leads to a decrease in the total
area surveyed. Limitations of particular survey protocols create a demand for new or
improved protocols where the need for “trade offs” is minimized.
Increasing species detection probability is one approach to reducing the trade off
between quality and quantity. An increase in detection probability reduces the number of
survey repetitions needed to yield accurate estimates of species numbers (MacKenzie et
al. 2002). One approach to increasing detection probability of cryptic species is inducing
a response from the animals being surveyed. Biologists often broadcast avian calls to
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Texas Tech University, Robert N. Mannan, May, 2008
solicit conspecific calls from individuals that would have otherwise gone undetected
(e.g., see Conway and Simon 2003).
Another approach to reducing the trade-off between quality and quantity is
increasing the efficiency of the surveyor. Automated audio recorders (hereafter
automated recorders) may be used to detect any vocal species allowing a single person to
collect data across a large area. Also, automated recorders have a good chance of
detecting cryptic vocal species that call intermittently, thereby reducing the need for
multiple surveys. Audio recorders have been placed at anuran breeding locations to
record call activity (e.g., see Penman et al. 2005). However, the use of automated
recorders as a surveying method is relatively new and is still being developed.
Recent work has identified two species of anurans, the boreal chorus frog
(Pseudacris maculata) and wood frog (Rana sylvatica), inhabiting the tundra biome near
the coast of the Hudson Bay in Manitoba (e.g., see Boal and Andersen 2003, Andersen et
al. 2005, Reiter et al. in review). Both species occupy the tundra across a gradient from
coastal tundra through interior sedge meadow/wetland to the tundra-boreal forest
interface. The subarctic tundra in northern Manitoba is covered in snow for most of the
year. However, for four months during the summer, the tundra becomes a marsh
providing nesting grounds for many bird species as well as breeding habitat for the boreal
chorus frog and the wood frog (Boal and Andersen 2003, Parks Canada 2007).
The tundra offers a unique set of challenges for anuran surveys rendering most
traditional methods inappropriate. Traditional survey methods for anurans include roadside surveys, listening stations, repeated surveys at selected breeding areas, and counts of
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Texas Tech University, Robert N. Mannan, May, 2008
egg masses (Heyer et al. 1994, Crouch and Paton 2000). Much of the tundra in North
America is roadless and summer travel is limited to helicopters or distances that can be
walked (Parks Canada 2007). This renders roadside surveys impossible and repeated
visits to listing stations and egg mass counts, if conducted with helicopters, expensive or,
if walked, time intensive. Also, in Wapusk National Park where I conducted the study, a
local population of polar bears (Ursus maritimus) makes camping and nighttime surveys
unsafe and requires that all daytime work be conducted in pairs, doubling the expense of
survey efforts. Currently, no anuran survey protocol has been created for the tundra
biome.
In 2006 and 2007, I expanded upon previous work (Boal and Andersen 2003,
Andersen et al. 2005, Reiter et al. In review) and conducted anuran surveys in Wapusk
National Park near Cape Churchill, Manitoba to: (1) evaluate the response of boreal
chorus frogs and wood frogs to broadcasted conspecific advertisement calls; and (2)
compare the effectiveness of automated recorders and manual surveys for detecting
anuran presence in the subarctic tundra biome.
Study Area
Wapusk National Park is located on the southwest side of Hudson Bay, Manitoba,
Canada. The park boundary is 35 km southeast of the town of Churchill, and the park
covers approximately 11,475 km2. The study area is located inside the park in the
subarctic tundra biome, which encompassed a matrix of small upland ridges and lowland,
sedge-dominated marshes and included a mix of semi-permanent and permanent water
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Texas Tech University, Robert N. Mannan, May, 2008
bodies throughout. Permafrost occurs near the surface, rendering most water bodies very
shallow. Winter temperatures are as low as -50 C with an average of -26 C and summer
temperatures range from -10 to 35 C with an average of 11 C (Parks Canada 2007). The
town of Churchill, located approximately 65 km northwest of Nestor One, the research
camp within the park, receives, on average, 436.1 mm of precipitation a year
(Environment Canada 2004). Most recreational uses are restricted in the park, except for
traditional uses such as hunting, trapping, fishing, and egg-collecting by local residents
and First Nations members.
I conducted field work primarily in the area surrounding Nestor One, a goose
research station located approximately two km from the Hudson Bay coastline south of
Cape Churchill (Easting: 0489270, Northing: 6502207; NAD 27). I collected data within
two 12.6 km2 study plots extending from near the coast of the Hudson Bay inland. The
study plots were situated 8 km apart and each had a diameter of 4 km (Fig. 1.1). All work
was conducted under the Texas Tech University Animal Care and Use Committee permit
number: 06021-05 and the Parks Canada research permit number: Wap-2005-518.
Methods
Surveys with broadcasted calls
In the summers of 2006 and 2007, I conducted anuran surveys at potential
breeding sites to evaluate the response of boreal chorus frogs and wood frogs to
broadcasted conspecific advertisement calls. To select potential breeding sites, I created
two 12.6 km2 circular study plots: a northern study plot established in 2006 and a
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Texas Tech University, Robert N. Mannan, May, 2008
southern study plot established in 2007. These study plots were located approximately 4
km from Nestor One to avoid disturbance to goose nests under observation as part of
Canada goose (Branta canadensis interior) monitoring activities. Study plots began at the
coast of the Hudson Bay and had a diameter of 4 km that extended inland (Fig. 1.1). I
used ARCGIS [version 9.1] (ESRI, Redlands, Calif., USA; use of trade names does not
imply endorsement by the U.S. Geological Survey, the University of Minnesota, or Texas
Tech University) to randomly select 57 locations within the northern plot and 60
locations within the southern plot. Buffer zones ensured locations were not closer than
200 m from each other and the number of survey locations was dictated by the time and
logistical support available for survey activities. On the first visit to each random
location, I walked to the nearest potential anuran breeding site to establish locations for
surveys (described below). Because water bodies with depths ≤10 cm were likely to dry
up within two weeks, I defined potential anuran breeding sites as water bodies deeper
than 10 cm.
Between 30 May and 18 June 2006, I conducted three broadcast surveys
(described below) at each breeding site at ~ 6 day intervals. Between 31 May and 11 July
2007, I repeated surveys at 27 of the randomly selected potential breeding sites surveyed
in 2006 and conducted surveys at 60 additional potential breeding sites in my southern
study plot (Fig. 1.1). I surveyed the 27 potential anuran breeding sites in my northern
study area in both 2006 and 2007 to assess annual variation in habitat use by anurans, and
to account for potential changes in vegetation between years. Whether individual frogs
reuse the same breeding locations between years on my study site is not known. For the
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Texas Tech University, Robert N. Mannan, May, 2008
purpose of this paper, in my analyses, I assumed that results obtained at the same survey
location (n = 27) were independent between years.
During each survey, I stood 5 m from the edge of the potential breeding site and
allowed one minute for anurans to acclimate to my presence. I then recorded the number
and species of anurans detected during a three-minute listening period. Following the
listening period, I conducted one of two treatments or a control. Treatments were
comprised of one minute of advertisement calls of either a boreal chorus frog or a wood
frog. The control was one minute with the absence of any broadcast (hereafter null
broadcasts). Following the treatment or control, I conducted another three-minute
listening period during which I recorded number and species of all anurans detected.
I used a random number generator to select which broadcast type would be used
in each survey. In 2006, I obtained recorded anuran calls from the U.S. Geological
Survey Amphibian Research and Monitoring Initiative [ARMI; USGS Upper Midwest
Environmental Science Center webpage (http://www.umesc.usgs.gov), last accessed 26
August 2006]. During 2007, I recorded and broadcasted calls from local anurans. I
broadcasted wood frog and boreal chorus frog advertisement calls with a megaphone
rotating in a circle and at an average of 67 (range = 64 – 71) and 78 (range = 71 – 80) dB,
respectively. I used sound levels slightly louder than naturally occurring advertisement
calls to ensure that broadcast stimuli reached all nearby anurans. All advertisement
broadcasts used during this study were comprised of two to three advertising males of
either wood frogs or boreal chorus frogs. Anurans sometimes call at the same time,
creating call overlap. Some anurans avoid this by calling sequentially (Fellers 1979,
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Texas Tech University, Robert N. Mannan, May, 2008
Sullivan 1985, Swartz 1987). To minimize the likelihood that broadcasting overlapping
calls acted as a call deterrent, the broadcasts I used contained no call overlap.
To supplement the number of surveys at potential breeding sites occupied by
anurans, in 2007 I also systematically searched both study plots for presence of anurans. I
repeatedly walked (>2 times) eight transects located at 1-km intervals spanning study
plots. When I detected anurans, I walked to the breeding site from which the anurans
were calling and marked the location. I returned to 11 of these locations and conducted <
3 broadcast surveys in the same fashion described above.
Comparison between audile surveys and automated recorders
In 2006 and 2007, I placed 11 automated recorders at locations I thought likely to
contain anurans based on characteristics of vegetation and water body. Recorders were
separated from each other by > 200 m, and were programmed to record ambient sounds
for three minutes. I chose three minutes because most anuran species are detected within
the first 3 minutes of a survey (Shirose et al. 1997).
In 2007, after the end of the anuran calling season, I tested the capability of
automated recorders to detect broadcasted calls at different distances from four
directions. I broadcasted wood frog mating calls at 20 m increments from the recorder out
to 160 m along four transects. Transects began at the recorders and traveled away from
the recorders at bearings of 0, 90, 180 and 270 degrees. I then reviewed the recordings
and identified positive detections at increasing distances. All broadcasts were at an
average of 67 (range = 64 – 71) dB and conducted when wind speeds were below 10 km.
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Texas Tech University, Robert N. Mannan, May, 2008
Statistical analysis
To compare the mean number of anurans of each species detected during the
three-minute listening period before and after broadcasts I conducted Wilcoxon matchedpairs tests because my anuran count data were not normally distributed (Conover 1999). I
also conducted a Wilcoxon matched-pairs test to compare the mean number of anurans of
each species detected three minutes before and after null broadcasts. Finally, I conducted
a Mann-Whitney U test to compare the mean number of anurans detected during the
initial listing period of broadcast surveys and null broadcast surveys. Tests included data
only from sites where I knew anurans were present (based on previous detections of
calling anurans). I assumed for these tests that breeding sites were independent and frogs
did not move among sites between surveys, a common assumption in anuran surveys
(Heyer et al. 1994). I also treated surveys at the same site in different years as
independent. I only included the first survey of each treatment type from sites in the
analyses to avoid pseudoreplication. Anuran calls periodically overlapped, occasionally
making an accurate estimate of anuran numbers difficult. In such cases (n = 2), I recorded
a range of frogs present (e.g., 6-8). For analyses, I used the lowest number in each range
to reduce overestimation.
To compare the effectiveness of automated recorders and audile surveys for
detecting anuran presence, I conducted 25 simultaneous audile surveys at five sites
during a subset of the automated recorded surveys. My count data were not normally
distributed, therefore, I conducted Wilcoxon matched-pairs tests to compare the mean
number of anurans of each species detected by automated recorders and audile surveys. I
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Texas Tech University, Robert N. Mannan, May, 2008
report means and standard deviations in the results. I made the assumption that each
recorder functioned with the same detection efficiency. This was not an unreasonable
assumption, as all recorders were assembled from the same parts at the same time.
Results
Surveys with broadcasted calls
I conducted 432 broadcast surveys at 144 randomly selected sites, and 14 surveys
at 11 sites identified while walking transects over the course of the two field seasons. I
detected >1 anuran at 47 of the 155 sites surveyed. Broadcast types were randomly
selected and sometimes a broadcast type was repeated at a site. To avoid duplication of a
broadcast type from the same location, I used 99 of the 155 surveys conducted at sites
where anurans were present in my analysis. I conducted 41 broadcast surveys and 24 null
broadcast surveys at locations where wood frogs had previously been detected. I
conducted 18 broadcast surveys and 16 null broadcast surveys at locations where boreal
chorus frogs had previously been detected.
There was no difference in the number of wood frogs detected before ( x= 0.541 ±
0.931) and after null broadcasts ( x = 0.625 ± 1.13; z = 0.00, P > 0.999). Likewise, there
was not a significant difference in the number of boreal chorus frogs detected before ( x =
1.06 ± 1.80) and after null broadcasts ( x = 1.13 ± 1.74; z = 0.00, P > 0.999). Similarly,
there was no apparent difference in detections of boreal chorus frogs pre broadcast ( x =
0.889 ± 1.37) and post broadcast ( x = 1.00 ± 1.53; z = 0.00, P = 0.999; Fig. 1.3). In
contrast, wood frogs responded positively to the broadcasting of conspecific
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Texas Tech University, Robert N. Mannan, May, 2008
advertisement calls. The mean number of wood frogs detected pre broadcast ( x = 0.824 ±
1.38) increased (t = 12.00, z = 2.73, P = 0.006; Fig. 1.2) to 1.24 ± 1.51 post broadcast.
There was no difference in the number of wood frogs detected during the initial
listing period of broadcast surveys ( x = 0.824 ± 1.38) and null broadcast surveys ( x=
0.541 ±0.931; adjusted z = 0.938, P = 0.348). Similarly, there was no difference in the
number of boreal chorus frogs detected during the initial listing period of broadcast
surveys ( x = 0.889 ± 1.37) and null broadcast surveys ( x = 1.06 ± 1.80; adjusted z =
0.00, P > 0.999)
Comparison between audile surveys and automated recorders
I conducted 25 audile surveys simultaneously with automated recorders over two
field seasons. Automated recorders ( x = 0.600 ± 0.867) detected significantly fewer
wood frogs compared to audile surveys ( x =0.960 ± 1.27, z = 2.20, P = 0.0277; Fig. 1.4).
In contrast, there was no difference between the number of chorus frogs detected with
automated recorders ( x = 1.72 ± 1.31) compared to audile surveys ( x = 1.44 ± 1.45; z =
3.30, P = 0.0009; Fig. 1.5).
I tested the capability of four automated recorders to detect broadcasts.
Automated recorders detected 100 percent of all broadcast up to 100 m (Fig 1.6). No
automated recorders detected broadcasts at 160 m (Fig 1.6).
15
Texas Tech University, Robert N. Mannan, May, 2008
Discussion
The subartic tundra is experiencing habitat changes due to a variety of factors, but
changes in plant communities resulting from herbivory by geese have recently received
considerable attention (Batt 1997, Jano et al. 1998). The mid-continent light goose (lesser
snow geese [Chen caerulescens] and Ross’s geese [Chen rossi]) population has increased
5-7% percent annually over the past 20 years and altered much of the vegetation in the
coastal and interior wetlands in the vicinity of Cape Churchill, Manitoba, Canada and
western and southern Hudson and James Bays (Batt 1997, Jefferies and Rockwell 2002).
Increased grazing has altered vegetation production and the overall vegetative
composition in some areas (Cargill and Jefferies 1984, Jefferies and Rockwell 2002). As
goose populations grow and the extent of vegetation change increases, it becomes
important to monitor local anuran populations and document potential influences of
habitat change. Increasing anuran detectability by soliciting calls from non calling
anurans and placing automated recorders at anuran breeding locations will aid in the
development of appropriate anuran survey methodology in the tundra biome.
Surveys with broadcasted calls
Anuran calls are important in territoriality, species identification, mate location,
and mate choice (Wells 1977, Wells and Greer 1981, Gerhardt 1982, Ryan 1985,
Gerhardt et al. 2000). Call overlap is often avoided to maintain the integrity of
information transmitted through vocal broadcasts (Fellers 1979, Sullivan 1985, Swartz
1987) and many anuran species avoid calling simultaneously with nearby conspecifics to
16
Texas Tech University, Robert N. Mannan, May, 2008
reduce call overlap. Broadcasting conspecific advertisement calls has been documented
to increase call frequency in already calling anurans (Wells and Greer 1981, Benedix and
Narins 1999, Gerhardt et al. 2000), but until now, there has been no evidence that
broadcasting advertisement calls could increase the number of anurans detected in field
surveys.
In my study, using broadcasted advertisement calls slightly increased the number
of wood frogs detected per survey but did not effectively elicit calls from boreal chorus
frogs. Because of the importance of calls and the information within them, it is not
surprising that an audile stimulus simulating potential intra-specific competition resulted
in a response by one of the species I tested. Which attributes of broadcasted calls cued
responses is unknown, and boreal chorus frogs might also respond to a broadcast call if
call attributes, such as call volume, call frequency, or pitch, were different from the ones
I used.
Detecting a change in the number of calling anurans in a field experiment is
difficult, primarily because the size of the chorus under observation can affect the
precision at which abundances are estimated. In studies conducted in areas with high
densities of frogs and large choruses, numbers of calling anurans are sometimes
estimated as ranges. For example, the North American Amphibian Monitoring Program
(NAAMP) uses call index values (CIV) to estimate numbers of chorusing anurans in
three ranges: 1; single calling anuran, 2; multiple calling anurans with no call overlap, 3;
multiple calling anurans with call overlap. The number of anurans each CIV value
represents is species specific (e.g., wood frogs CIV 2 = 3-5 frogs). Representing numbers
17
Texas Tech University, Robert N. Mannan, May, 2008
of calling anurans in ranges renders rough estimates, which makes detections of small
changes in anuran numbers difficult. The density of anurans in the tundra landscape in
which I worked is low (Andersen et al. 2005), allowing me to estimate anuran numbers
without using ranges. Estimating anuran numbers, as opposed to ranges, likely
contributed to my ability to detect an increase of roughly 0.4 wood frogs per survey.
My results suggest that the decision of male wood frogs to call is affected by the
presence of intra-specific competition. The function of the anuran advertisement calls is
thought to be primarily mate attraction and location. Female anurans often choose mates
that call more often or with more volume (Ryan 1985). My call broadcasts simulated an
increase in local calling activity. Increased calling activity may serve as an indicator of
the presence of potential mates, and initiating calling in the presence of potential mates
would be advantageous. My results support previous work that suggested that part of the
decision of wood frogs to call is based in the perception of intra-specific competition
(Wells and Greer 1981, Burmeister et al. 1999).
Comparison between audile surveys and automated recorders
The estimated number of calling wood frogs detected by automated recorders and
audile surveys differed. Automated recorders collapsed the three-dimensional aural world
into a single dimension, which may help explain the discrepancy between the numbers of
wood frogs detected by audile surveys and automated recorders. The ability to pinpoint
the source of calls likely contributed significantly to the ability of a human estimating the
number of calling anurans. Wood frogs make a series of single-note chirps resembling the
18
Texas Tech University, Robert N. Mannan, May, 2008
sound of boiling water, but with a higher pitch. During a chorus, wood frogs do not
always avoid call overlap. Without pinpointing wood frog locations, call overlap makes it
difficult to distinguish among individual frogs on a recording.
Although I did not detect a statistical difference in the number of detections made
during audile surveys and by automated recorders, more chorus frogs were detected by
automated recorders than were detected by observers during five of 25 simultaneous
surveys. Boreal chorus frogs usually call with no overlap, or in tandem pairs. In a chorus,
if one frog changes frequency others shift frequency to avoid call overlap (Schwartz
1987). Without pinpointing the source of calls it is difficult to distinguish between boreal
chorus frogs shifting frequency and new frogs joining the chorus. Shifts in frequency may
have acted as false positives, inflating the number of boreal chorus frogs I detected by
recorders.
Using automated recorders in my study did not result in accurate assessment of
the number of calling wood frogs, suggesting that use of automated recorders for
acquisition of specific count data of anurans must be done with caution. The automated
recorders did reliably detect anurans up to 100 m in any direction. Therefore, it may be
possible to use counts acquired from automated recorders as indices and derive and apply
species-specific correction factors to estimate counts. However, such a correction would
require knowledge or estimation of region- and species-specific bias in counts.
Automated recorders would also likely be effective in monitoring sites for
presence or absence, which could be used to monitor frog distribution. Also, because the
detection probability for anurans is likely <1, repeated visits to a site may be necessary to
19
Texas Tech University, Robert N. Mannan, May, 2008
accurately determine anuran presence or absence (e.g., see MacKenzie et al. 2002).
Automated recorders, if left active for an appropriate amount of time, would likely detect
all present anuran species. This would alleviate the need for observers to survey a site
multiple times.
Although automated recorders did not accurately assess exact numbers of calling
anurans it is possible to assess overall changes in numbers of anurans calling. This
information would be useful in assessing changes in calling activity across seasons and
over time as climate changes.
Management implications
Several studies have documented increased call frequency of anurans following
call broadcasts (Wells 1977, Wells and Greer 1981, Gerhardt 1982, Gerhardt et al. 2000).
My study demonstrates that it is possible to solicit a vocal response from non-calling
anurans of some species in the field. In situations where single-species surveys are to be
implemented, broadcasting conspecific mating calls may be a useful tool for increasing
detection levels, especially in areas containing low densities of anurans. In this study only
25% of the sites visited contained anurans. An increase in detection levels decreases the
necessary number of survey repetitions thereby decreasing the effort required to survey a
particular region with no loss to data quality. A decrease in required survey effort would
create more economical survey protocols and facilitate studies encompassing larger areas.
However, broadcasting should not be implemented in all anuran surveys. It is
likely that in large anuran choruses, where a small number of additional anurans calling
20
Texas Tech University, Robert N. Mannan, May, 2008
will not change estimates of abundance, broadcasting advertisement calls may prove
ineffective. Furthermore, it is unclear how broadcasting advertisement calls would affect
anuran calling patterns during surveys designed to gather information about an array of
species.
In this study, using automated recorders did not result in accurate assessment of
specific numbers of one species of calling anuran. Therefore, automated recorders in
subarctic tundra landscapes should be used for count data with caution, but are likely
suitable for documenting anuran presence. Automated recorders function without the
presence of an observer, which makes them especially useful for documenting anuran
presence or absence in isolated regions where repeated visits are logistically difficult.
While this study focused on the use of automated recorders for detecting anurans,
the use of automated recorders are not limited to anurans. For example, automated
recorders may be useful in avian studies. Avian and anuran surveys use similar methods,
such as point counts. Use of automated recorders in avian surveys would offer all the
same benefits and drawback that use of automated recorders in anuran surveys offer.
21
Texas Tech University, Robert N. Mannan, May, 2008
Figure 2.1. Study plots near Cape Churchill, Manitoba, where anuran surveys were
conducted in 2006 and 2007.
22
Texas Tech University, Robert N. Mannan, May, 2008
28
26
24
22
Number of observations
20
18
16
14
12
10
8
6
4
2
0
-4
-3
-2
-1
0
1
2
3
4
The numbers of R. sylvatica detected after broadcasting minus the number of R. sylvatica detected before
broadcasting
Figure 2.2. The change in the numbers of Rana sylvatica detected before and after
broadcasting advertisement calls near Cape Churchill, Manitoba, 2006-2007.
23
Texas Tech University, Robert N. Mannan, May, 2008
Figure 2.3. The change in the number of Pseudacris maculata detected before and after
broadcasting advertisement calls near Cape Churchill, Manitoba, 2006-2007.
24
Texas Tech University, Robert N. Mannan, May, 2008
20
18
16
Number of observations
14
12
10
8
6
4
2
0
-4
-3
-2
-1
0
1
2
3
4
Number of R. sylvatica detections made by the observer minus the number of R. sylvatica detections
made by the automated recorders
Figure 2.4. Difference in the number of Rana sylvatica detections made by observers and
using automated recorders near Cape Churchill, Manitoba, 2006-2007.
25
Texas Tech University, Robert N. Mannan, May, 2008
20
18
16
Number of observations
14
12
10
8
6
4
2
0
-4
-3
-2
-1
0
1
2
3
4
Number of P. maculata detections made by the observer minus the number of P. maculata detections
made by the automated recorders
Figure 2.5. The discrepancy of Pseudacris maculata detections made by observers and
using automated recorders near Cape Churchill, Manitoba, 2006-2007.
26
Texas Tech University, Robert N. Mannan, May, 2008
Figure 2.6. The percentage of broadcasts detected by automated recorders conducted at
20 m increments along transects beginning at automated recorders and traveling at
bearings of 0, 90, 180, and 270 degrees, near Cape Churchill, Manitoba, 2006-2007.
27
Texas Tech University, Robert N. Mannan, May, 2008
CHAPTER III
FACTORS AFFECTING CALLING ACTIVITY OF BOREAL CHORUS FROGS
(PSEUDACRIS MACULATA) AND WOOD FROGS (RANA SYLVATICA) NEAR
CAPE CHURCHILL, MANITOBA
Abstract
Little information exists regarding wood frogs (Rana sylvatica) and boreal chorus
frogs (Pseudacris maculata) in the tundra biome, where environmental conditions differ
from most of the rest of their breeding ranges. Understanding anuran calling patterns is
essential to most anuran survey methodology. During the summer of 2007, I placed
automated audio recorders at anuran breeding locations and recorded number of calling
anurans near Cape Churchill, Manitoba. I used data loggers and automated call recorders
to document date, time of day, temperature, and relative humidity. Automated recorders
detected wood frogs between 30 May and 2 July 2007, and boreal chorus frogs between
11 June and 5 July 2007. Calling activity of both wood frogs and boreal chorus frogs was
influenced by temperature and day of the year (DOY). Calling activity of boreal chorus
frogs was also influenced by time of day and relative humidity. Understanding calling
patterns with respect to weather patterns will facilitate future monitoring.
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Texas Tech University, Robert N. Mannan, May, 2008
Introduction
Both boreal chorus frogs (Pseudacris maculata) and wood frogs (Rana sylvatica)
have extensive distributions across North America that extend into subarctic tundra in
northern Manitoba (USGS 2002, Stebbins 1951). Both species are common within their
ranges and much is known about their life histories (e.g., see Heatwole 1961, Berven
1990). However, little information exists regarding either of these species in the tundra
biome, where environmental conditions differ from most of the rest of their respective
breeding ranges (Boal and Andersen 2003, Andersen et al. 2005, Reiter et al. In review).
Tall trees, commonly associated with the breeding sites of both species, are lacking in the
tundra and northern latitudes have relatively short summers, long day lengths, and cold
temperatures, compared to other breeding habitats of wood frogs and boreal chorus frogs.
Both species of frogs show considerable morphological and behavioral variability across
their respective ranges and populations occurring in tundra biomes may differ
behaviorally in response to the extreme conditions present in the tundra (Pettus and
Spencer 1964, Berven 1990).
One behavior that may change in response to conditions in the tundra is calling
activity. In more temperate regions, both wood frogs and boreal chorus frogs are
considered explosive breeders (Oseen and Wassersug 2002, USGS 2002) because all
breeding takes place over a relatively short time interval. During this short breeding
season, environmental factors have little effect on calling activity. For example, in New
Brunswick, Canada, temperature and humidity had little effect on the calling activity of
wood frogs (Oseen and Wassersug 2002). However, temperature, humidity, and light
29
Texas Tech University, Robert N. Mannan, May, 2008
intensity affect calling patterns of anurans that exhibit a non-explosive breeding strategy
(Oseen and Wassersug 2002). Because anurans are poikiothermic, it is possible that
temperature would affect calling activity of anurans in the tundra, where summer freezes
are not uncommon.
No information exists regarding calling activity of boreal chorus frogs or wood
frogs in the tundra biome. Many ecological questions about anurans are addressed using
information derived from surveys, and most anuran surveys are rooted in detecting calls.
Therefore, understanding factors that affect calling activity in tundra anurans should
increase the effectiveness of research and monitoring efforts. Herein, I describe diurnal
and seasonal calling activity and the effects of temperature, humidity, and time of day on
calling activity of boreal chorus frogs and wood frogs in a tundra biome.
Study Area
Wapusk National Park, Manitoba, Canada is located on the southwest side of
Hudson Bay. The park boundary is 35 km southeast of the town of Churchill and the park
covers approximately 11,475 km2. The study area is located inside the park in the
subarctic tundra biome, and encompassed a matrix of small upland ridges and lowland,
sedge-dominated marshes and included a mix of semi-permanent and permanent water
bodies throughout. Permafrost occurs near the surface, rendering most water bodies very
shallow. Winter temperatures are as low as -50 C with an average of -26 C and summer
temperatures range from -10 to 35 C with an average of 11 C (Parks Canada 2007). The
town of Churchill, located approximately 65 km northwest of Nestor One, the research
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Texas Tech University, Robert N. Mannan, May, 2008
camp within the park, receives, on average, 436.1 mm of precipitation a year
(Environment Canada 2004). Few recreational uses occur in the park, except for
traditional uses such as hunting, trapping, fishing, and egg-collecting by local residents
and First Nations members.
I conducted field work primarily in the area surrounding Nestor One, a goose
research station located approximately 2 km from the Hudson Bay coastline south of
Cape Churchill (Easting: 0489270, Northing: 6502207; NAD 27). I collected data within
two 12.6 km2 study plots extending from near the coast of the Hudson Bay inland. The
study plots were situated 8 km apart and each had a diameter of 4 km (Fig. 2.1). All work
was conducted under Texas Tech University Animal Care and Use Committee permit
06021-05 and Parks Canada research permit: Wap-2005-518.
Methods
Eleven automated recorders were positioned at locations likely to contain anurans
based on characteristics of vegetation and water body. All recorders were situated >200
m apart. Each recorder was programmed to record ambient sounds for 3 minutes at 1.5hour intervals. I chose three minutes because most anuran species are detected within the
first 3 to 5 minutes of a survey (e.g., see Shirose et al. 1997). I also placed HOBO data
loggers (Onset Computer, Pocasset, Mass., H08-030-08; use of trade names does not
imply endorsement by the U.S. Geological Survey, the University of Minnesota, or Texas
Tech University) at each automated recorder site to record temperature and humidity in
concert with audio recordings.
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Texas Tech University, Robert N. Mannan, May, 2008
Each automated recorder was left active for three days. On the third day, I
collected automated recorders in the evening, reviewed recordings, and then replaced
recorders the following morning. During review, I listened to each recording and noted
the species and number of anuran calls. At the end of the field season, I collected HOBO
data loggers and downloaded data on temperature, relative humidity, time, and day of
year (DOY) that corresponded with each 3-minute recording interval.
In order to extract anuran count data from the loggers, I assumed that the
automated recorders accurately depicted anuran calling activity. In Chapter I
demonstrated that anuran count data obtained by automated recorders and audile surveys
conducted by an observer differed for some species (Mannan et al., unpublished).
However, count data obtained from recorders was species specifically biased, suggesting
that count data obtained from recorders can be used as an accurate index to calling
activity, but not absolute abundance (Mannan et al., unpublished). My study focuses on
the effects of weather and seasonal variables on anuran calling activity not exact anuran
numbers. Therefore, for the purposes of this study I treated anuran count data obtained
from the automated recorders as an index to calling activity.
Statistical Analysis
My count data were regarded as Poisson-distributed random variables (e.g., see
Fitzmaurice et al. 2004). Variability among locations was not of interest in this study and
therefore the location effect was included in the model as a random nuisance variable.
Because of logistical considerations, data from the automated recorders were not
32
Texas Tech University, Robert N. Mannan, May, 2008
necessarily collected on the same days of the year. The resulting data set, therefore, was
analyzed using the methods of longitudinal data analysis (Fitzmaurice et al. 2004). I used
a linear mixed effects model to model anuran count data with a log link function, and
included location as a random nuisance variable, and day of year, relative humidity,
temperature, and time of day as independent variables. Data were analyzed with the
GLIMMIX procedure of SAS.
Results
In 2007, I placed 11 recorders at potential anuran-calling locations, and three of
these failed following a severe storm. I obtained data related to diurnal and seasonal
anuran calling patterns from the remaining eight recorders. Count data were collected at
eight locations from 30 May (DOY=150) to 9 July 2007 (DOY=190). Automated
recorders detected wood frogs between 30 May (DOY=150) and 2 July 2007
(DOY=183), and boreal chorus frogs between 11 June (DOY=162) and 5 July
(DOY=186) 2007 (Fig. 2.2). Both species exhibited calling patterns consistent with
explosive breeding behavior. Peak calling activity for boreal chorus frogs followed peak
calling activity for wood frogs by 12 days. Both species called 24 hours a day throughout
their breeding season, although peak calling times were afternoon and early morning (i.e.,
1200hrs – 0230 hrs; Fig. 2.2). Wood frogs called in temperatures ranging from -2.4 - 29.5
C. calling activity reassembled a normal distribution with lowest calling activity
occurring during temperature extremes (Fig. 2.2). Wood frogs called in relative humidity
ranging from 0% to 100% (Fig. 2.2). Increased calling activity was skewed towards lower
33
Texas Tech University, Robert N. Mannan, May, 2008
levels of humidity. Boreal chorus frogs called in temperatures ranging from -1.5 - 31.1C,
(Fig. 2.2). Calling activity increased as temperature increased. Boreal chorus frogs called
in relative humidity ranging from 0% to 100%, with peak calling activity occurring
during low levels of relative humidity (Fig. 2.2). Temperature and DOY explained a
significant amount of variation within the calling patterns of wood frogs (Table 2.1).
Relative humidity, temperature, DOY, and time of day explained a significant amount of
variation within the calling patterns of boreal chorus frogs (Table 2.2).
Discussion
Both wood frogs and boreal chorus frogs in my tundra study site exhibited calling
behavior consistent with an explosive breeding strategy. However, unlike other studies
conducted on explosive breeding anurans, in my study, colder temperatures were
associated with reduced calling activity of both species within the breeding season (e.g.,
see Oseen and Wassersug 2002). During late May and June, temperatures in northern
Manitoba can drop well below 0 C. Anurans are poikiothermic, and therefore cannot
remain active in all temperatures. The inability to remain active in low temperatures may
explain the association of calling activity of anurans and temperature on my study area.
Despite the positive association between wood frog calling activity and
temperature, I documented wood frogs calling during intervals when air temperature was
below freezing (Fig. 2.2). This may be attributed to a difference between air and water
temperature. Wood frogs spend a great deal of time in the water (Conant and Collins
34
Texas Tech University, Robert N. Mannan, May, 2008
1991). Water temperatures may have remained high enough to support anuran activity
during intervals when air temperature dropped below freezing.
For this study, DOY was designed to account for the effect of seasonal cues such
as day length or other unknown factors perceivable by anurans. A day is a fluctuating set
of environmental conditions occurring during a time interval. Within this varying set of
conditions are known (e.g., temperature) and unknown cues that trigger the start and stop
of anuran calling (e.g., see Conant and Collins 1991, Oseen and Wassersug 2002), which
should be especially important in explosive breeding anurans. While we cannot identify
specific factors causing the stat and stop of wood frog or boreal chorus frog breeding
seasons, the importance of DOY representing a seasonal effect on calling activity in my
study is consistent with the explosive breeding strategy of both anuran species.
One possible confounding factor related to the association between DOY and
calling patterns is that the automated recorders detected wood frogs on the first day of
recording. Therefore, it is likely that wood frog calling began before I was able to place
automated recorders in the field. If recorders were not in place to capture the beginning of
the calling season, then the first day of the recording interval would appear to be an
exaggerated abrupt beginning to the wood frog calling season. Therefore, some of the
variation in wood frog calling activity explained by DOY may have been an artifact of
the timing of the recorder placement. However, it is unlikely that calling began long
before automated recorders were activated. When recorders were activated there was still
snow around anuran breeding ponds. While wood frogs are known to call before the
complete thaw of breeding ponds, it is unlikely that calling began long before my arrival
35
Texas Tech University, Robert N. Mannan, May, 2008
(USGS 2002, Stebbins 1951). Also, wood frogs are known to begin breeding abruptly
throughout their breeding range and it seems likely that they began abruptly at my study
site as well (USGS 2002, Stebbins 1951).
Relative humidity and time of day also accounted for variation in the calling
pattern of boreal chorus frogs. The lowest detection levels of boreal chorus frogs began
around sunrise (0400 hrs) and continued through 1000 hrs (Fig. 2.2). Peak calling
occurred in the afternoon (1400 hrs and continued through the evening. These results
suggest that light intensity, related to time of day, may influence calling activity of boreal
chorus frogs, a common pattern among anurans (e.g., see Bridges and Dorcas 2000,
Oseen and Wassersug 2002). Avoidance of predators and thermoregulation have been
suggested as ultimate causes of the effect of light intensity on anuran calling activity.
Several bird species occurred in my study site during summer that likely prey on frogs,
including sandhill cranes (Grus canadensis), and many of those forage more vigorously
during morning hours (Iverson et al. 1985), a time when calling generally was
suppressed. Thus, predator avoidance seems a plausible explanation for reduced anuran
calling during morning hours in northern Manitoba.
There was a negative association between the calling activity of boreal chorus
frogs and humidity. Peak calling rate was at a relative humidity of about 30%. Peak
calling at low humidity levels is unusual for anurans (e.g., see Fogarty and Viella 2001,
Stevens et al. 2002). However, high humidity often accompanies precipitation. There are
several reasons for the boreal chorus frog to avoid calling during a precipitation event.
First, precipitation can interfere with sound transmission negating any reproductive
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Texas Tech University, Robert N. Mannan, May, 2008
advantage to calling (Henzi et al. 1995). Second, in the tundra, summer precipitation can
come in the form of sleet and is often accompanied by large temperature swings. It may
be disadvantageous or physiologically impossible to call during such conditions. High
levels of humidity may cue a suppression of calling.
Management implications
Calling activity of anurans, and thus the ability to detect them in surveys, varies
across regions and within seasons (Bridges and Dorcas 2000). Surveys of anurans in a
given region should, therefore, be timed according to local patterns. My results suggest
that breeding seasons of boreal chorus frogs and wood frogs overlapped, which would
facilitate monitoring both species simultaneously. Within the breeding season,
temperature influenced the calling activity of both species and time of day was related to
calling activity of boreal chorus frogs. Thus, conducting surveys during the evening and
in warmer temperatures may maximize survey efficiency. However, because the call
activity of the two species differed in their response to some climatic variables (e.g.,
relative humidity), species-specific surveys may result in higher detection levels for
individual species.
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Texas Tech University, Robert N. Mannan, May, 2008
Figure
3.1. Study plots near Cape Churchill, Manitoba, where anuran surveys were conducted in
2007.
38
Texas Tech University, Robert N. Mannan, May, 2008
A.
3.0
Mean number of anurans detected per site
2.5
2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
30-M ay
4-Jun
9-Jun
15-Jun
20-Jun
25-Jun
1-Jul
6-Jul
1-Jun
7-Jun
12-Jun
17-Jun
23-Jun
28-Jun
3-Jul
9-Jul
Date
Figure 3.2. Mean and standard deviation of the number of anurans detected as a function
of (A) date, (B) time of day, (C) temperature, and (D) relative humidity near Cape
Churchill, Manitoba, Canada, 2007 (□ = Wood frogs, ▲=Boreal chorus frogs).
39
Texas Tech University, Robert N. Mannan, May, 2008
B.
3.0
Mean number of anurans detected per site
2.5
2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
0:00 1:35 3:11 4:47 6:23 7:59 9:35 11:11 12:47 14:23 15:59 17:35 19:11 20:47 22:23 23:59
Time
C.
2.2
2.0
Mean number of anurans detected per site
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-4.3
-2.0
0.4
2.8
5.1
7.5
9.9
12.2 14.6 16.9 19.3 21.7 24.0 26.4 28.8 31.1
Temp (C)
Figure 3.2. Continued
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Texas Tech University, Robert N. Mannan, May, 2008
D.
3.0
Mean number of anurans detected per site
2.5
2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5
-1.6
5.4
12.5 19.5 26.6 33.6 40.6 47.7 54.7 61.8 68.8 75.8 82.9 89.9 97.0 104.0
Relative humidity
Figure 3.2. Continued
Table 3.1. Results of a regression analysis of a linear mixed effects model used to model
wood frog call activity, near Cape Churchill, Manitoba, Canada, 2007, (n= 1383).
Covariate
Standard Error
F
P
RH (%)
0.00326
0.64
0.4250
Temp (C)
0.01300
12.95
0.0003
Day of Year
0.00703
123.81
<0.0001
Time
0.2193
1.49
0.2219
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Texas Tech University, Robert N. Mannan, May, 2008
Table 3.2. Results of a regression analysis of a linear mixed effects model used to model
boreal chorus frog call activity, near Cape Churchill, Manitoba, Canada, 2007 (n= 1383).
Covariate
Standard Error
F
P
RH (%)
0.00317
6.59
0.0103
Temp (C)
0.01192
6.72
0.0096
Day of Year
0.00955
0.0011
0.0011
Time
0.2250
0.0214
0.0214
42
Texas Tech University, Robert N. Mannan, May, 2008
CHAPTER IV
HABITAT ASSOCIATIONS OF BOREAL CHORUS FROGS (PSEUDACRIS
MACULATA) AND WOOD FROGS (RANA SYLVATICA) IN A TUNDRA BIOME
Abstract
Anuran populations in the subarctic tundra biome in northern Manitoba are being
impacted by multiple factors, including vegetation changes resulting from foraging
pressure by an increasing population of light geese. During the summers of 2006 and
2007, I surveyed 204 potential anuran breeding locations in two study plots in the tundra
biome within Wapusk National Park, Manitoba, Canada to assess anuran habitat
associations. I examined habitat selection and associations of wood frogs (Rana
sylvatica) and boreal chorus frogs (Pseudacris maculata) with regard to vegetation and
water quality. Both wood frogs and boreal chorus frogs selected sites where vegetation
was taller and had a higher composition of sedge (Carex spp.) and willow (Salix spp.).
Both species also selected sites with relatively low pH and conductivity (TDS). An index
of goose herbivory was negatively correlated with vegetation height and cover by sedge
and willow and positively correlated with pH and conductivity. Both wood frogs and
boreal chorus frogs were found more commonly in sites with less evidence of recent
goose herbivory.
43
Texas Tech University, Robert N. Mannan, May, 2008
Introduction
Tundra landscapes are being altered by both biological and physical factors. Over
the past two decades, mid-continent light geese [snow geese (Chen caerulescens) and
Ross’s geese (Chen rossii)] populations in northern Manitoba have increased at an annual
rate of 5-7% (Batt 1997, Jefferies and Rockwell 2002). Recently, the effects of this
population increase on tundra vegetation have received some attention. Increased grazing
has altered vegetation production as well as the overall vegetative composition in some
areas (Cargill and Jefferies 1989, Jefferies and Rockwell 2002). As goose populations
continue to grow and the extent of vegetation change increases, the potential for impacts
on other species in the tundra and their habitats also increases r (e.g., Sammler 2001).
Two anuran species, boreal chorus frogs (Pseudacris maculata) and wood frogs
(Rana sylvatica), are among species that may be negatively affected by goose herbivory
in the tundra biome. The range of wood frogs extends into Canada and Alaska, along the
northeastern seaboard in the United States, through the Great Lakes region and into the
northern Midwest states (USGS 2002, Stebbins 1951). The boreal chorus frog is the
northernmost of the chorus frogs with a range extending from portions of Arizona and
New Mexico through the Midwest, north into Alberta, Ontario, Saskatchewan, Manitoba,
and parts of the Northwest Territories (Koch and Peterson 1995, USGS 2002). Because
both species exist across a wide geographical range, specific habitat relationships in
many regions are unknown. However, both species use vegetation for cover and as
anchors for egg mass deposition, making attributes of vegetation likely important habitat
characteristics (Conant and Collins 1991, Crouch and Paton 2000).
44
Texas Tech University, Robert N. Mannan, May, 2008
In the tundra biome, there are few plants that grow very tall and that would
provide potential breeding vegetation for anurans. In tundra landscapes in northern
Manitoba, sedges (Carex aquatilis, C. rupestris, and C. glacialis) and small willows
(Salix planifolia, S. herbacea, and S. brachycarp) are the only plants that may provide the
shelter and structure needed for anuran egg mass deposition. Geese in some of these
tundra landscapes feed heavily on sedges, and the reduction and removal of sedges by
foraging geese may alter a tundra biome in three notable ways. First, both wood frogs and
boreal chorus frogs attach egg masses to aquatic vegetation, and reduction of sedges may
remove the cover and tall vegetative structure necessary for anuran egg mass deposition.
Second, removal of sedges may increase water pH at potential breeding sites; pH level is
a hydrological characteristic important to the survival of both wood frogs and chorus
frogs (Corn et al. 1989, Moore and Klerks 1998, Wikberg and Mucina 2002). Third,
foraging geese also potentially increase Total Dissolved Solids (TDS) in the water by
disturbing the substrate as they feed, or by removing vegetation and, thereby, altering the
filtration processes facilitated by wetland vegetation (Noller et al. 1994). Currently, the
influences of goose herbivory in tundra landscapes on anuran habitat associations are
unknown.
In 2006 and 2007, I conducted anuran surveys in a tundra landscape in northern
Manitoba to evaluate associations between anuran presence and vegetative structure,
water body depth, and environmental conditions [pH and TDS]. I also created an index
based on evidence of goose herbivory and evaluated associations between this index and
45
Texas Tech University, Robert N. Mannan, May, 2008
vegetation height, cover, and water quality. Finally I evaluated associations between
anuran presence and this index of goose herbivory.
Study Area
Wapusk National Park is located on the southwest side of Hudson Bay, Manitoba,
Canada. The park boundary is 35 km southeast of the town of Churchill and the park
covers approximately 11,475 km2. The study area is located inside the park in the
subarctic tundra biome, and encompassed a matrix of small upland ridges and lowland,
sedge-dominated marshes and included a mix of semi-permanent and permanent water
bodies throughout. Permafrost occurs near the surface, rendering most water bodies very
shallow. Winter temperatures are as low as -50 C with an average of -26 C and summer
temperatures range from -10 to 35 C with an average of 11 C (Parks Canada 2007). The
town of Churchill, located approximately 65 km northwest of Nestor One, the research
camp out of which I conducted this study within the park, receives, on average, 436.1
mm of precipitation a year (Environment Canada 2004). Few recreational uses occur in
the park, except for traditional uses such as hunting, trapping, fishing, and egg-collecting
by local residents and First Nations members.
I conducted field work primarily in the area surrounding Nestor One, a goose
research station located approximately 2 km from the Hudson Bay coastline south of
Cape Churchill (Easting: 0489270, Northing: 6502207; NAD 27). I collected data within
two 12.6 km2 study plots extending from near the coast of the Hudson Bay inland. The
study plots were situated 8 km apart and each had a diameter of 4 km (Fig. 3.1). All work
46
Texas Tech University, Robert N. Mannan, May, 2008
was conducted under Texas Tech University Animal Care and Use Committee permit
06021-05 and the Parks Canada research permit Wap-2005-518.
Methods
In the summers of 2006 and 2007, I conducted anuran surveys at potential
breeding sites to evaluate associations between anuran occurrence and vegetative
structure and environmental conditions [pH and TDS] (see below). To select potential
breeding sites, I created two 12.6 km2 circular study plots; a northern study plot
established in 2006 and a southern study plot established in 2007. These study plots were
located approximately 4 km from Nestor One to avoid disturbance to goose nests under
observation as part of Canada goose (Branta canadensis interior) monitoring activities.
Study plots began at the coast of the Hudson Bay and had a diameter of 4 km that
extended inland (Fig. 3.1). I used ARCGIS [version 9.1] (ESRI, Redlands, Calif., USA;
use of trade names does not imply endorsement by the U.S. Geological Survey, the
University of Minnesota, or Texas Tech University) to randomly select 57 locations
within the northern plot and 60 locations within the southern plot. Buffer zones ensured
locations were not closer than 200 m from each other and the number of survey locations
was dictated by the time and logistical support available for survey activities. On the first
visit to each random location, I walked to the nearest potential anuran breeding site to
establish locations for surveys (described below). Because water bodies with depths ≤10
cm were likely to dry up within two weeks, I defined potential anuran breeding sites as
water bodies deeper than 10 cm.
47
Texas Tech University, Robert N. Mannan, May, 2008
To describe potential breeding sites, I first used a local coordinate system to select
two sample locations within each site. To create a local coordinate system, I estimated the
width and length of the water body that comprised the breeding site. I then used these
estimated distances as the axes of a hypothetical grid, with 1 m cells, that encompassed
the entire water body plus 0.5 m beyond the water body’s edge. I used a random number
generator to identify two grid intersections, which served as sample locations within each
potential breeding site. Some lakes in my study area lacked vegetation beyond the
shoreline and I never observed anurans calling from beyond the shoreline of these lakes.
Therefore, if the coordinates of a sample location fell in open water within a lake that
contained no vegetation beyond 1 m of the shoreline, all habitat variables (described
below) were measured from the point on the shoreline closest to the grid intersection. At
each sample location, I dropped a 1x1 m quadrat (constructed of rigid polyvinyl chloride
tubing) at my feet. In the case of a shoreline location, half of the quadrat was placed on
the shore and half in the lake. Within each quadrat, I measured pH, TDS, water depth at
two opposite corners of the quadrat, vegetation height at the four corners of the quadrat,
and the tallest vegetation within the quadrat. I chose these variables based on their
biological importance to anuran habitat selection and/or survival (Pierce et al. 1984, Corn
et al. 1989, Moore and Klerks 1998, Anderson et al. 1999, Crouch and Patton 2000, Kopp
and Eterovick 2006). For each potential breeding site, I used the two sample locations to
calculate an arithmetic mean of pH, TDS, vegetation height, and tallest vegetation, and
used these means in statistical analyses.
48
Texas Tech University, Robert N. Mannan, May, 2008
I also took a digital photo from 1.5 m directly above the quadrat to estimate
vegetation composition. Using Microsoft® Paint (Microsoft 2002; use of trade names
does not imply endorsement by the U.S. Geological Survey, the University of Minnesota,
or Texas Tech University), I placed a grid with 100 intersections on each photo. Using
Johnson (1987) as a key, I identified vegetation at each grid intersection to genus, and
estimated percent cover as the number of times a genus occurred under an intersection
divided by the total number of intersections. For each potential breeding site, I used the
photos from each sample location (n = 2) to calculate an arithmetic mean vegetation
composition by percent cover.
At every potential anuran breeding site, I also visually surveyed the entire site for
evidence of goose herbivory, and evaluated herbivory based on evidence of goose
foraging (Kerbes et al. 1990). I quantified evidence of goose herbivory into two foraging
types: “shoot pulling” and “grubbing”. “Shoot pulling” was evidenced by the presence of
uprooted sedges with the base of the plant removed. This is caused when geese uproot
vegetation, eat the basal tissue, and leave the rest of the plant. Shoot pulling was
separated into two groups; recent, or “new shoot pulling” and past, or “old shoot pulling”,
based on the color and condition of the uprooted vegetation. I classified uprooted floating
vegetation as new shoot pulling, and classified older and decomposing vegetation as old
shoot pulling. I similarly assessed grubbing in the substrate. Grubbing is characterized by
overturned small chunks of substrate, about the size of a goose bill. These measures of
goose foraging were designed to be correlated with grazing pressure. New shoot pulling
indicated only recent grazing and thus the smallest amount of grazing pressure. Old shoot
49
Texas Tech University, Robert N. Mannan, May, 2008
pulling represented a history of grazing, thus indicating heavier grazing pressure.
Grubbing normally occurs in areas lacking vegetation emergent from the substrate. I
assumed that in areas with no vegetation, above-ground vegetation had previously been
removed by geese, and therefore grubbing indicated the highest amount of grazing
pressure.
To document anuran presence or absence at each potential breeding site, I
conducted three surveys at ~ 6 day intervals. During each survey, I stood 5 m from the
edge of the potential breeding site and allowed one minute for anurans to acclimate to my
presence. I then recorded the number and species of anurans detected during a 3-minute
listening period. Following the 3-minute listening period I broadcasted anuran mating
calls in an attempt to increase detection rates (described below). I conducted all surveys
at each site from the same location. When I detected anurans during a survey, I
triangulated the position of the first detected anuran when calling continued long enough
for observers to estimate a bearing to the frog. Two observers standing ≥5 m apart
estimated the direction from which they heard the anuran and then walked in that
direction until their paths crossed at the estimated location from which the anuran called
(referred to as the triangulation location). I then measured vegetation in a quadrat
centered on the triangulation location, as described above. I used the triangulation
locations to represent habitat characteristics selected for by calling anurans within each
site.
In 2007, to supplement information on the characteristics of randomly located
potential breeding sites occupied by anurans, I -systematically searched both study plots
50
Texas Tech University, Robert N. Mannan, May, 2008
for presence of anurans. I repeatedly walked (>2 times) eight transects located at 1-km
intervals spanning study plots. When I detected anurans, I walked to the breeding site
from which the anurans were calling and triangulated an estimated calling location, as
described above. I then estimated the same habitat characteristics at the triangulation
location and at two random locations as I did for randomly located breeding sites
occupied by anurans.
I conducted surveys in two study plots (Fig. 3.1) during the course of the study. In
2006, between 30 May and 18 June, I conducted surveys at 57 random locations in Study
Plot One, established in 2006 north of Nestor One. In 2007, between 31 May and 11 July,
I repeated surveys at 27 randomly selected potential breeding sites surveyed in 2006, and
conducted anuran surveys at an additional 60 potential breeding sites in Study Plot Two,
established south of Nestor One. I conducted transect surveys (on both study plots) only
in 2007. Little empirical evidence exists about the rate at which vegetation is changing in
my study site, and although it is possible that anurans present and detected during surveys
in 2006 were present at some of the 27 sites resurveyed in 2007, I assumed my surveys
between years to be independent in statistical analyses.
Statistical Analysis
I evaluated anuran habitat associations at two levels; breeding site and within
breeding site. At the site level, I used t-tests to compare habitat characteristics of
unoccupied and occupied sites. To conduct this comparison, I used only data collected
from the two random sample locations of each site. To evaluate within-site associations,
51
Texas Tech University, Robert N. Mannan, May, 2008
from sites occupied by anurans, I used paired t-tests to compare habitat characteristics of
triangulation locations to the mean value of habitat characteristics of the two random
sample locations. I also used Fisher’s exact tests to further examine relationships between
presence of anurans and evidence of goose herbivory.
The variables I measured exhibited high levels of inter-correlation. Because my
variables were correlated and it is unclear which variables would be appropriate to
eliminate from my analysis, I used Principal Components Analyses (PCA) to assess
associations (McGarigal et al. 2000). I used PCA (STATISTICA [release 7]; StatSoft,
Tulsa, Okla., USA; use of trade names does not imply endorsement by the U.S.
Geological Survey, the University of Minnesota, or Texas Tech University) to extract
components from my data and identify characteristics associated with breeding sites
occupied by anurans. I selected components with eiganevalues above one to test for effect
on anuran presence (McGarigal et al. 2000) and conducted a multivariate analysis of
variance (MANOVA) to examine the associations between the selected components and
the presence of anurans at potential breeding sites. I then used a MANOVA to test for
within-model component significance.
I used PCA loading scores to evaluate the importance of variables within
components. The absolute value of the loading score of each variable within a component
indicates how strongly the component is associated with that variable (McGarigal et al.
2000). The higher the absolute value of a loading score, the stronger the association. As
the value chosen to warrant investigation or suggest importance to a component is
52
Texas Tech University, Robert N. Mannan, May, 2008
arbitrary, I used 0.5, a common value used to assess variable importance within a
component (McGarigal et al. 2000).
Results
Across both study plots and years, I detected anurans at 36 (25%) of 144 random
potential anuran breeding sites. I detected anurans at an additional 60 breeding sites by
walking transects through study plots. Using both methods, I detected a combined total of
48 potential breeding sites where I detected only wood frogs, 18 potential breeding sites
where I detected only boreal chorus frogs, and 30 potential breeding sites where I
detected both species.
For both wood frogs and boreal chorus frogs, sites where I detected frogs
contained taller vegetation and higher percent cover of vegetation than sites where I did
not detect frogs (Table 3.1). Occupied sites also contained lower pH and TDS than
unoccupied sites (Table 3.1). In addition, boreal chorus frogs were present at sites with
more cover and taller vegetation than wood frogs (Table 3.1). At the scale of location
within occupied sites, both anuran species were detected in areas with taller vegetation
and a higher percent composition of sedge and willow (Table 3.2). Both species were
detected more frequently at areas without evidence of goose herbivory; boreal chorus
frogs were negatively associated with all three measures of goose herbivory, whereas
wood frogs were significantly negatively associated with sites that had evidence of old
shoot pulling or grubbing (Table 3.3).
53
Texas Tech University, Robert N. Mannan, May, 2008
Most habitat variables were highly intercorrelated (Table 3.4). Therefore, I
extracted 10 components from the variables percent cover by sedge and willow, pH,
TDS, water depth, tallest vegetation, average vegetation height, new shoot pulling, old
shoot pulling, grubbing, and year. Based on eigenvalues >1, I selected components one
through four to test for effect on anuran presence. Approximately 69 percent of the
variation across breeding sites was incorporated in these four components (Table 3.5). A
model containing these four components was associated with both wood frogs
(MANOVA; Wilks’ Lambda = 0.75; F4,204 = 16.4, P < 0.001) and boreal chorus fogs
(MANOVA; Wilks’ Lambda = 0.70; F4,204 = 21.1, P < 0.001). Within-model significance
indicated that components one, three, and four were related to wood frog presence and
component one was related to boreal chorus frog presence (Table 3.6). Wood frog and
boreal chorus frog presence was negatively associated with component one (Fig. 3.2 and
Fig. 3.3).
Component one was associated with five variables; tallest vegetation received the
heaviest loading score followed by average vegetation height, TDS, percent cover by
sedge and willow, and pH. Component three was associated only with average vegetation
height. Component four was associated with new shoot pulling and with percent cover by
sedge and willow; new shoot pulling received the heaviest loading score (Table 3.7).
Sites with new and old shoot pulling or grubbing were negatively associated with
vegetation height and percent cover by sedge and willow, and positively associated with
pH and TDS (Fig. 3.4). When goose herbivory indices were modeled to represent
increasing levels of grazing pressure (i.e., no evidence of goose herbivory, presence of
54
Texas Tech University, Robert N. Mannan, May, 2008
only new shoot pulling, presence of new and old shoot pulling, and grubbing), increased
grazing pressure was negatively associated with average vegetation height (F3,204 = 13.1,
P < 0.001), tallest piece of vegetation (F3,204 = 22.4, P < 0.001), percent cover by sedge
and willow (F3,204 = 4.2, P = 0.006), and positively associated with pH (F3,204 = 2.70, P =
0.047) and TDS (F3,204 = 7.19, P < 0.001) (Fig. 3.4).
Discussion
On my study, boreal chorus frogs and wood frogs were positively associated with
percent cover of vegetation and vegetation height, although boreal chorus frogs tended to
favor areas with slightly taller vegetation than wood frogs. Both wood frogs and boreal
chorus frogs deposit egg masses on aquatic vegetation (Conant and Collins 1991) and
aside from sparse willows, sedge is the tallest vegetation offering structure appropriate
for egg mass deposition. Other species of chorus frogs also are associated with tall
vegetation (Anderson et al. 1999). Wood frogs are described as canopy generalists,
breeding in ponds that are both covered and not covered by tree canopy (Werner and
Glennemeier 1999), although associations between tree cover and ground cover have not
been assessed. In addition to providing appropriate structure for reproduction, higher
cover may also reduce predation risk from birds such as arctic terns (Sterna paradisaea)
or sandhill cranes (Grus canadensis). More extensive and higher cover may provide
better concealment.
The effect of pH on survival of anurans is population-dependant (Pierce 1985). In
my study area I found negative relationships between anurans and pH, but all pH levels
55
Texas Tech University, Robert N. Mannan, May, 2008
were within the tolerance ranges of wood frogs and other chorus frogs (Pierce et al. 1984,
Corn et al. 1989). Wikberg and Mucina (2002) demonstrated that in sedge-dominated
aquatic environments, removal of sedge results in an increase in water pH. On my study
area, it may be that anurans are associated with high levels of vegetative cover, which
may have lower pH, rather than being associated with lower pH itself.
Both Canada geese and light geese return annually to the tundra around Cape
Churchill to nest. Light goose numbers are increasing (Batt 1997, Jefferies and Rockwell
2002), and large numbers of light geese migrating to more northerly breeding areas
forage in the tundra near Cape Churchill (Jefferies and Rockwell 2002). Goose herbivory
has had dramatic effects on tundra vegetation near Cape Churchill, and in some areas, has
resulted in almost complete removal of vegetation (Jefferies and Rockwell 2002).
Currently there are no standard indices for goose herbivory in a tundra biome. The
indices to goose herbivory that I used are based on the pattern of impacts on tundra
vegetation from goose foraging described in Krebs et al. (1990). Sites with only evidence
of new goose herbivory should display the least severe effects of grazing, and have been
impacted least by geese. Sites that contained evidence of old shoot pulling likely had a
longer history of grazing and the effects of grazing should be more severe. Grubbing
occurs in areas with extensive goose foraging activity because grubbing usually occurs in
areas with little above-ground vegetation. This categorization of the extent and history of
goose herbivory appeared to reasonably depict grazing intensity, as sites with old shoot
pulling, and presumably a longer history of grazing, contained shorter vegetation and
higher pH values than sites with no evidence of goose herbivory. Sites with evidence of
56
Texas Tech University, Robert N. Mannan, May, 2008
grubbing contained less cover and shorter vegetation than sites with old shoot pulling.
Taller vegetation at sites with new shoot pulling may indicate that geese have only
recently begun to use these areas, or that grazing pressure has not been high enough to
result in measurable effects on vegetation. The patterns of vegetative cover and pH that I
observed, suggest that the index I used to quantify goose herbivory reasonably reflects
past levels of grazing pressure.
Presence of both wood frogs and boreal chorus frogs was negatively related to
evidence of goose herbivory. Because vegetation height and cover are important to both
frog species, it is not surprising that there were fewer frogs where there was evidence of
more extensive herbivory. Prolonged and heavy grazing by geese can significantly alter
the structure and composition of the vegetation that anurans select for breeding sites
(Jefferies and Rockwell 2002). Specifically, increased foraging by geese may reduce the
amount of sedge, leading to an alteration or loss of habitat important for wood frogs and
boreal chorus frogs.
One surprising result was the relationship between new shoot pulling and wood
frog presence suggested by the PCA analysis. However, given the strong negative
association between wood frogs and goose herbivory, it is unlikely new shoot pulling
attracts wood frogs. Instead, new shoot pulling likely occurs in sites where sedges are still
relatively abundant, and these areas may already be occupied by wood frogs when new
shoot pulling takes place.
I also observed a negative association between anuran presence and higher levels
of conductivity (TDS). Reasons for the association are unclear. However, higher
57
Texas Tech University, Robert N. Mannan, May, 2008
conductivity is correlated to increased grazing pressure, which is associated with
decreases in extent of vegetative cover. Vegetation in wetlands filters inorganic and
organic substances from water. A decrease in vegetation may hinder these processes,
increasing inorganic material in the water, and resulting in higher levels of conductivity
(TDS). Therefore, it’s likely that the negative association between anuran presence and
increasing TDS is an artifact of the loss of vegetation due to goose herbivory.
Management implications
Vegetation is important to both anuran species present in the tundra landscape in
northern Manitoba and elsewhere (Anderson et al. 1999, Werner and Glennemeier 1999).
Wood frogs and boreal chorus frogs appear to select for sites with taller vegetation and
higher percent vegetative cover. Increased foraging pressure from goose herbivory may
negatively impact both species of anuran inhabiting the tundra biome near Cape
Churchill, Manitoba. The extent of effects of goose foraging in this landscape, especially
in the freshwater sedge-meadow habitats, has not been adequately assessed. However, it
is likely that as grazing pressure increases the number of sites suitable for anuran
breeding will also decrease.A more through examination of resulting vegetation damage
from grazing pressure must be conducted. I also recommend that sticker population
management actions be taken regarding light geese.
58
Texas Tech University, Robert N. Mannan, May, 2008
Figure 4.1. Study plots near Cape Churchill, Manitoba, where anuran surveys were
conducted in 20067 and 2007.
59
Texas Tech University, Robert N. Mannan, May, 2008
Table 4.1. Mean values of habitat variables at detection and non-detection sites for wood
frogs and boreal chorus frogs near Cape Churchill, Manitoba, 2006-2007.
(Bolded values indicate statistical difference between detection and non-detection sites at
the 0.05 alpha level: t-tests. a Indicates values are significantly different between species
at the 0.05 alpha level; t-tests.).
Wood Frog
Boreal Chorus Frog
Variable
Wood Frog
(n = 78)
Non-detection
(n = 126)
Boreal
Chorus Frog
(n = 48)
Non-detection
(n = 156)
Percent
Composition
of Sedge
and Willow
74.0
46.3
72.5
52.1
pH
7.6
8.0
7.6
7.9
137.6
178.1
110.2
178.7
36.2 a
24.3
49.4a
22.5
9.0 a
4.7
15.2 a
3.6
TDS (Total
Dissolved
Solids)
Tallest
Vegetation
(cm)
Average
Vegetation
Height (cm)
60
Texas Tech University, Robert N. Mannan, May, 2008
Table 4.2. Mean values of percent cover, vegetation height, tallest piece of vegetation,
pH, and TDS of triangulation locations and corresponding breeding sites near Cape
Churchill, Manitoba, 2006-2007. (Bolded numbers indicates statistical difference at the
0.05 alpha level; t-tests.)
Wood Frog
Boreal chorus frog
Variable
Triangulation
Location
(n = 48)
Breeding Site
(n = 48)
Triangulation
Location
(n = 38)
Breeding Site
(n = 38)
Percent
Composition
of Sedge
and Willow
87.5
77.5
89.2
80.0
pH
7.5
7.5
7.6
7.7
126.0
123.7
116.55
107.2
51.3
34.4
84.4
54.2
14.8
7.7
31.4
17.9
TDS (Total
Dissolved
Solids)
Tallest
Vegetation
(cm)
Average
Vegetation
Height (cm)
61
Churchill, Manitoba, 2006-2007.
No
Evidence
Evidence
of New
of New
Shoot
Shoot
Pulling
Pulling
Wood
Frog
Detections
54
Fischer’s
Fischer’s
Fischer’s
No
Exact
Evidence
Exact
No
Exact
Evidence
Evidence
Test
Test
of Old
Test
Evidence
of Old
of New
Results
Shoot
Results
of
Results
Grubbing
Shoot
Pulling
(P(PGrubbing
(PPulling
value)
value)
value)
24
14
64
24
54
62
Texas Tech University, Robert N. Mannan, May, 2008
Table 4.3. Number of sites with and without anuran detections that contained evidence of goose herbivory near Cape
0.66
0.0005
0.003
No Wood
Frog
Detections
85
41
51
75
64
62
Boreal
Chorus
frog
Detections
23
25
6
42
7
62
No Boreal
Chorus
Frog
Detections
116
0.0007
40
0.0006
58
97
<0.0001
81
75
chorus frogs and wood frogs near Cape Churchill Manitoba 2006-2007 (n= 204).
Habitat
Variables
Percent
Cover
pH
0.09
-0.27
(0.216) (<0.001)
0.17
-0.19
Veg. Height
(0.017)
(0.007)
0.29
-0.25
Tallest Veg.
(<0.001) (<0.001)
Water
0.08
-0.05
Depth
(0.233)
(0.440)
0.11
-0.22
Grubbing
(0.117)
(0.002)
Old Shoot
-0.24
0.17
Pulling
(0.001)
(0.017)
New Shoot
0.03
0.03
Pulling
(0.722)
(0.677)
-0.29
0.29
TDS
(<0.001) (<0.001)
-0.39
pH
X
(<0.001)
Percent
X
Cover
Year
TDS
-0.34
(<0.001)
-0.26
(<0.001)
-0.33
(<0.001)
-0.05
(0.453)
0.18
(0.008)
0.28
(<0.001)
0.17
(0.013)
X
New
Shoot
Pulling
0.07
(0.344)
-0.13
(0.067)
-0.17
(0.015)
-0.05
(0.482)
0.32
(<0.001)
0.22
(0.002)
X
Old
Shoot
Pulling
-0.35
(<0.001)
-0.13
(0.066)
-0.17
(0.013)
0.12
(0.088)
0.02
(0.772)
X
Grubbing
0.26
(<0.001)
-0.18
(0.010)
-0.26
(<0.001)
-0.31
(<0.001)
X
Water
Depth
Tallest
Veg.
Veg.
Height
-0.44
(<0.001)
0.10
(0.174)
0.12
(0.094)
0.11
(0.133)
0.84
(<0.001)
0.09
0.204
X
X
X
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Texas Tech University, Robert N. Mannan, May, 2008
Table 4.4. Correlation coefficients and P-values (in parentheses) of measured habitat variables at potential breeding sites of boreal
Texas Tech University, Robert N. Mannan, May, 2008
Table 4.5. Eigenvalues of a correlation matrix and the % variation of habitat variables
explained in models of habitat associated with anuran locations near Cape Churchill,
Manitoba, 2006-2007.
Component
Eigenvalue
1
2.75
% Total
Variation
Explained
28.5
2
1.86
18.6
46.1
3
1.18
11.6
57.9
4
1.15
11.5
69.4
64
Cumulative %
Variation
Explained
28.5
Texas Tech University, Robert N. Mannan, May, 2008
Table 4.6. Results of a post-hoc MANOVA test for within-model significance when
predicting anuran presence near Cape Churchill, Manitoba, 2006-2007 (n = 202).
Wood Frog
Intercept
Component
1
Component
2
Component
3
Component
4
Degrees
of
F
Freedom
1
163.87
1
41.09
1
0.07
1
6.67
1
18.87
Boreal Chorus Frog
P
<0.0001
Intercept
Component
<0.0001
1
Component
0.785923
2
Component
0.0109
3
Component
<0.0001
4
65
Degrees
of
F
Freedom
1
87.21
P
<0.0001
<0.0001
1
80.53
1
0.319 0.667791
1
0.00
0.241743
1
2.57
0.270363
Texas Tech University, Robert N. Mannan, May, 2008
Wood frog presence
1
0
-4
-3
-2
-1
0
1
2
3
Component one
Figure 4.2. The relationship between component one and wood frog detection, depicted
by a logistic regression line near Cape Churchill, Manitoba, 2006-2007.
66
Texas Tech University, Robert N. Mannan, May, 2008
Boreal Chorus frog presence
1
0
-4
-3
-2
-1
0
1
2
3
Component one
Figure 4.3. The relationship between component one and wood frog presence, depicted
by a logistic regression line near Cape Churchill, Manitoba, 2006-2007.
67
Texas Tech University, Robert N. Mannan, May, 2008
Table 4.7. Loading scores of variables within Principal Components of habitat models
describing anuran locations near Cape Churchill, Manitoba, 2006-2007.Bolded numbers
indicate loading scores of absolute value >0.5.
Variable
Component 1
Component 2
Component 3
Component 4
Percent
Sedge and
Willow
-0.558303
0.028580
0.287488
0.503835
pH
0.545991
-0.187277
-0.213056
-0.458068
TDS
0.649573
-0.179072
-0.215902
0.019466
0.317061
0.244211
-0.360346
0.702940
0.461116
-0.392509
-0.336038
0.295282
0.401067
0.595045
-0.338211
0.095668
-0.124618
-0.711388
0.138510
0.276933
-0.796087
-0.178313
-0.493451
-0.070232
-0.708621
-0.171146
-0.616651
-0.116700
-0.311491
0.810436
-0.030130
-0.055378
New
Shoot
Pulling
Old Shoot
Pulling
Grubbing
Average
Water
Depth
Tallest
Piece of
Vegetation
Average
vegetation
Height
Year
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Texas Tech University, Robert N. Mannan, May, 2008
Figure 4.4. Means and 95% confidence intervals of (A) average vegetation height, (B) %
cover by sedge and willow, (C) average height of tallest vegetation, (D) TDS, and (E)
pH, with respect to evidence of goose herbivory near Cape Churchill, Manitoba, 20062007.
69
Texas Tech University, Robert N. Mannan, May, 2008
Figure 4.4. Continued.
70
Texas Tech University, Robert N. Mannan, May, 2008
Figure 4.4. Continued.
71
Texas Tech University, Robert N. Mannan, May, 2008
LITERATURE CITED
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Texas Tech University, Robert N. Mannan, May, 2008
APPENDIX A
AUTOMATED RECORDER COMPONENTS
Components in the automated loggers I used included a digital voice recorder
(Olympus vn-2000), digital timer (American Deer Hunter 30556), microphone (Olympus
me-15), 12-volt battery (Panasonic LC-R121R3P), and a solar panel (Sun Force 77796).
(Fig. 4.1 and Fig. 4.2) All components except the solar panel and microphone were
housed inside of a metal box. The microphone protruded from the box through a hole. A
chicken wire frame encompassed the entire the box, to reduce mammalian disturbance.
The solar panel was fixed to a chicken wire frame. Circuitry was constructed at Texas
Tech University (Fig. 4.3).
Automated recorders were originally programmed to broadcast advertisement
calls after the 3-minute recording interval and then conduct another 3-minute recording
interval. However, the speakers failed to function properly and automated recorder
broadcasts were never conducted in the field.
77
Texas Tech University, Robert N. Mannan, May, 2008
Figure 5.1. Diagram of automated recorder components near Churchill, Manitoba, 20062007.
78
Texas Tech University, Robert N. Mannan, May, 2008
Figure 5.2. Photograph of automated recorder components near Cape Churchill,
Manitoba, 2006-2007.
79
Texas Tech University, Robert N. Mannan, May, 2008
Figure 5.3. Control board for automated recorder near Cape Churchill, Manitoba, 20062007.
80
Texas Tech University, Robert N. Mannan, May, 2008
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