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Adélie Penguin (Pygoscelis adeliae) Population Trends in
Cape Bird, Antarctica, 1956-2009: A Response to Climate
Change, Competitive Release and Commercial Fishing
Jessica Cardé

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Introduction
The Antarctic Peninsula has been found to be one of the fastest warming regions
on the planet, with average winter temperatures having increased by approximately 6°
Celsius in just 60 years (Stokstad, 2007). This increase has had significant impacts on
the Antarctic environment and its inhabitants (Boersma, 2008). Collapsing ice shelves,
decreasing sea ice, glacial retreat, and increasing precipitation are only some of the
impacts of climate change in Antarctica. While Antarctica and the Southern Ocean play
a crucial role in the global climate system, Antarctica is often overlooked in the public
debate over climate change.
Adélie penguins (Pygoscelis adeliae) are one of the five penguin species that live
on the Antarctic continent. While long-term data are non-existent for most of the
continent, some populations have been monitored in Antarctica for at least the last 60
years. With 3.79 million breeding pairs (Lynch and LaRue, 2014), the Adélie penguin is
one of the most abundant and widely distributed penguin species in Antarctica.
However, despite their increasing total abundance, regional metapopulations throughout
Antarctica are reacting differently to environmental changes, both biotic and abiotic. On
the Antarctic Peninsula, most populations are declining while populations in the south
near the Ross Sea are increasing. This is why it is important to assess populations at
the regional or continental scale rather than focus on individual populations. Adélie
penguins have been surveyed regularly since the 1980s, providing researchers with
valuable data that allow us to observe population trends over the past several decades.

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Changes in Adélie penguin abundance is a complex issue and despite
considerable study, the drivers of population change remain ambiguous. Adélie
penguins serve as bio-indicators for the health of the Antarctic ecosystem due to their
sensitivity to climate and environmental changes (Boersma, 2008). Because of this, the
Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR)
monitors the population at a few locations on a regular basis. While there are many
factors that can have an impact on the population dynamics of Adélie penguins, it is
impossible to pinpoint the exact cause and effect of a particular change due to complex
ecosystem interactions as well as the lack of data in the Antarctic system. However, it
is likely the case that a combination of factors including climate change, competitive
release, and commercial fishing play a crucial role in the interannual fluctuations and
long-term trends of Adélie penguin populations.
This study focuses solely on the Cape Bird colony (77°10′S 166°41′E), one of
three Adélie penguin colonies on Ross Island. Cape Bird is located on the northwest
coast of Ross Island and the rookeries are spread along approximately 6 miles of
coastline. The Cape Bird population can be divided into 3 separate rookeries: Northern
Rookery, Middle Rookery, and Southern Rookery. Southern colonies along the Ross
Sea have increased greatly since monitoring of the population began in the 1960s. The
Cape Bird colony in particular increased by 8% each year on average from 1983-1987
(Taylor and Wilson, 1990) resulting in an additional 13,931 breeding pairs according to
aerial census data during this time period (Taylor, Wilson, & Thomas, 1990).
Much of the research done thus far on trends of Adélie penguin populations has
pointed to climate change as the leading cause for changes in population dynamics

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over the past several decades. While climate change effects can manifest in many
different ways, the primary threats to Adélie penguins include decrease in sea ice cover
and thickness, glacial retreat, and increased snow and rainfall. As mentioned earlier,
these changes have impacted each Adélie penguin colony differently depending on the
region of Antarctica in which they are located. In Cape Bird, glacial retreat and a
decrease in sea ice led to an expansion of suitable habitat for Adélie penguins and
therefore facilitated an increase in population abundance. Optimal sea ice cover for
Adélie penguins is approximately 15% (Lyver et al., 2014) creating a sufficient resting
area as well as keeping a feasible distance to travel for foraging in the sea. Sea ice is
also an important habitat for Antarctic krill species as the underside supports the growth
of algae on which the krill feed. Therefore, sea ice is a key element to the productive
feeding grounds that support Antarctic wildlife.
In addition, warmer air temperatures have a greater capacity to hold moisture,
which has led to an increased amount of intense precipitation. This presents a great
threat to Adélie chicks who are not adapted for survival in a wet environment. Their
downy coats serve as a warm moisture barrier that allows them to withstand cold
temperatures and low levels of snowfall. However, heavy snow and rain cause their
down coats to become saturated which can lead to hypothermia and death (Boersma,
2008). Increased rain and snowfall do not pose as much of a threat to the juveniles and
adults as their feathers create a waterproof layer which keeps them insulated and
allows them to swim in the frigid Antarctic waters.
Adélie penguins are a high trophic level predator in the Antarctic and may have a
large effect on prey abundance locally. Antarctic krill (Euphausia superba) and the

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smaller Crystal krill (Euphausia crystallorophias) are one of the primary food sources of
Adélie penguins as well as baleen whales such as humpback whales (Megaptera
novaeangliae) and minke whales (Balaenoptera acutorostrata), which also inhabit the
Ross Sea. During the whaling era of the early to mid-20th century, whale populations
were massively depleted to 5-10% of their original levels prior to exploitation. This
resulted in 150 million tonnes more krill in the Southern Ocean each year (Croxall,
1992) and likely attributed to the increase of the Adélie penguin population during the
1950s and 1960s.
Antarctic silverfish (Pleuragramma antarctica) is another major food source for
top predators such as Adélie penguins and serves as a keystone species in the
Antarctic ecosystem. This creates considerable trophic competition between predator
species; of particular interest is the Antarctic toothfish (Dissostichus mawsoni), a
primary consumer of silverfish. Since commercial fishing of Antarctic toothfish in the
Ross Sea began in 1996, the population has become depleted, causing an increase in
silverfish availability for Adélie penguins and other consumers. The timing of this event
correlates with the rapid population increase of Ross Sea Adélie penguins observed
since 2000 (Lyver et al., 2014).
In 1946, the U.S. Navy began surveying Antarctica using a technique known as
trimetrogon aerial photography or TMA. This method requires the use of three cameras
placed side-by-side making it possible to capture full 180° panoramic views of the
Antarctic landscape. Recently, new TMA photographs from the United States Antarctic
Resource Center (USARC) archive of Cape Bird, Antarctica have been found dating

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back to the 1950s. In this study, we have analyzed these historic images and compared
colony sizes and shifts to those of present day.
Methods
Images from the years 1956, 1957, 1966, and 1983 from the United States Antarctic
Resource Center (USARC) archive were considered in this analysis. ArcGIS 10.1
software was used to count individual Adélie penguins from the 1983 aerial images of
Cape Bird, Antarctica (Figure 1). Each individual appeared as a black dot, and those
that were separate from the breeding area were considered outliers and therefore not
counted. While aerial images provide a great overhead view of entire colonies, it can
sometimes be difficult to identify penguins. This is especially true in high density
colonies as well as in areas of rocky terrain. In addition, penguins that appeared to be
lying down had a more oblong shape than the typical “dot”, this further complicated the
counting process since it was not always clear if these oblong shapes were in fact
penguins. For these reasons, the counts represented in this study are conservative.
Historic photos from the years 1956, 1957, and 1966 were also analyzed using
ArcGIS 10.1. However, due to low resolution, it was impossible to count individuals.
Instead, a polygon shapefile was created in order to outline the guano-stained areas of
each colony. These images (in addition to the images from 1983) were then
georeferenced onto the 2009 high resolution image in order to create a multi-decadal
time series (Figure 2). This allowed for the observation of any changes in the colonies
such as increase/decrease in size, shifts in colony distribution, and the appearance of
new or disappearance of existing colonies. In addition, calculations of polygon areas

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using the ArcGIS 10.1 software were used to determine amounts of increase or
decrease of guano-stained areas.
These historic photographs are possibly the only data we have on Adélie
penguins in this particular area of Antarctica prior to major changes in the Earth’s
climate. Therefore, this analysis may help us better understand the effects that climate
change has on Adélie penguin populations and may also help us project future
population trends.
For a more detailed explanation of the methods used in this study, please refer to the
Appendix at the end of this paper.
Results 1983 Individual Counts of
Breeding Pairs
The Northern Rookery was the largest of
the three with 26,378 individuals, followed
by the Southern Rookery with 10,761
individuals and finally the Middle Rookery
with 1,882 individuals. This gives a total count of 39,021 individuals. In comparison,
the air census data from 1983 published by Taylor, Wilson, & Thomas (1990) shows
greater counts for each rookery and represents the number of breeding pairs (Table 1).
Due to reasons explained in the methods, and as confirmed by the comparison with
Taylor et al. (1990), these counts are conservative. Breeding Adélie penguins typically
come ashore to incubate their eggs from late November to early December. During this
Table 1
1983 Number of
Breeding Pairs
1983 Number of
Breeding Pairs
(Taylor, Wilson,
and Thomas,
1990)
Rookery Count
North 26,378 31,878
Middle 1,882 2,237
South 10,761 11,711
Total 39,021 45,826

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time, their mates and other non-breeding individuals are offshore foraging (Taylor,
Wilson, & Thomas, 1990). Since the images analyzed in this study are dated from
December 9th 1983, this is what was likely occurring.
Comparison of Northern, Middle, and Southern Rookeries
The following images were analyzed through the comparison of the amount of
guano staining.
Northern Rookery
Images of the Northern Rookery were dated from the years 1957, 1966, 1983,
and 2009 (Figure 3). Comparison of these images suggest an increase in population as
well as expansion of the breeding grounds in some areas. These findings coincide with
published data by Coats (2010), who estimated that the Northern Rookery population
reached approximately 40,000 breeding pairs in 2010.
Middle Rookery
Images of the Middle Rookery were dated from the years 1957, 1966, 1983, and
2009 (Figure 4). While this is the smallest of the rookeries, comparison of these images
show possibly the largest relative increase in size as well as expansion to the
surrounding area. In the 1957 image, the rookery appeared to consist of several small
clusters scattered around the area; however, the 1966 image shows just three large
clusters. The 1983 image shows the first appearance of three new tiny clusters along
the coastline towards the northwest. These tiny clusters seem to have persisted and
expanded over the years and are still visible in the 2009 image.

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Southern Rookery
Images of the Southern Rookery were dated from the years 1956, 1957, 1983,
and 2009 (Figure 5). Comparison of these images proved difficult to interpret. While it
appears that many of the clusters in the middle area have shrunken in size, the
southern-most cluster has more than doubled according to area calculations based on
polygon size (1956 polygon area = 4,318.29 m2; 2009 polygon area = 10,556.65 m2). In
addition, an expansion of the small clusters beyond the river to the north appears to
have occurred (Figure 6). The expansion of the southern-most cluster as well as the
expansion of the smaller clusters to the north could possibly represent densely-packed
areas. Based on a visual assessment alone, it is difficult to say whether the population
at this rookery has increased or decreased. However according to published data, the
Southern Rookery population increased from 1983 (11,711 BP ± 5%) to 1987 (15,232
BP ± 5%) (Taylor, Wilson, & Thomas, 1990) followed by an eventual decrease to
approximately 13,000 breeding pairs by 2010 (Coats, 2010). This represents a small
but noticeable increase in abundance (~11%) for the southern Rookery over the last 30
years. Conversely, quantitative analysis of the sum of the total area of the Southern
Rookery shows a decrease in guano stained area from 1956 (38,468.80 m2) to 2009
(31,945.91 m2). However, since individual birds are not visible in either of these
images, it is impossible to take a proper census.
Discussion
The use of ArcGIS software makes it possible to remotely quantify colony size and
location providing a cost-effective, non-invasive method of surveying populations. In
addition, digitizing the images created a convenient way to perform qualitative analyses

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of the colonies and compare changes over time. This method also opens up new doors
making it possible to evaluate historic satellite imagery that would otherwise be difficult
to analyze.
Older images typically had poor contrast which made it difficult to distinguish
“penguin dots” from the background. Furthermore, it was not always clear where the
guano-stained areas started and ended which likely caused a greater margin in error.
Differentiating between guano-stained areas and other light colored areas, like snow,
proved to be difficult as well. This is likely a more prevalent issue in black and white
images.
Georeferencing is an excellent tool when analyzing images that lack spatial
reference, however it is not perfect. This is especially true when analyzing images of
Antarctica, a place that is constantly changing and where the few identifiable features
that exist are covered in snow and ice. Other factors that added to the complexity
included image quality and working with many layers, both raster and vector. As a
result, the images were slightly off from one another which had to be taken into account
when examining shifts in penguin colonies. However, since the nesting density of
Adélie penguins is fairly consistent and estimated from previous studies (Lynch and
LaRue, 2014; LaRue et al. 2014), georeferencing makes it possible to calculate
abundance estimates in older images where individuals may not be visible. This
provides a way to not only qualitatively measure colonies, but a way to quantify them as
well.
If this method is to be used in future research, it is important that a standardized
method be created in order to ensure that counts are conducted the same way each

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time by anyone doing so. Accuracy can also be improved by having multiple individuals
perform counts rather than a single person. This will create a more accurate and
replicable method that can be easily compared with future studies. Moreover, this
method can be used to survey other wildlife species as well.
Conclusion
Climate warming in Antarctica is an ongoing threat that has impacted the landscape
and inhabiting wildlife. For the last few decades, Adélie penguins have served as great
indicators of climatic change due to their sensitivity to changes in their environment.
Adélie penguins throughout the continent have been affected differently depending on
their location. While the colonies of the Western Antarctic Peninsula have been
declining or extirpated, many colonies near the Ross Sea have been thriving. However,
that is not to say that the Ross Sea colonies are not affected. This is a complex issue
and there are likely several interacting factors that are playing a role in the population
fluctuations of the Ross Sea colonies.
The overall trend of the Adélie penguin population in the Ross Sea area has been
increasing since at least the 1950s, which pre-dates the major changes in climate we’re
seeing today. This means that there must be another explanation for the population
increase. We know that the depletion of baleen whales due to commercial whaling in
the mid-20th century led to a massive prey release of Antarctic krill species. This event
likely attributed to the increase of Adélie penguins from the 1950s to the 1970s.
However, when minke whales began to recover in the 1990s, the Adélie penguin
population did not decrease to the levels before whaling, suggesting that the population
was being influenced by other factors as well. Concurrently, the increased availability of

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Antarctic silverfish due to the commercial Antarctic toothfish fishery led to another rapid
population increase of Adélie penguins in the early 2000s.
If these conditions persist, a continuing increase of the Ross Sea colonies could
eventually lead to density dependent issues. As food and other resources become
limited, both interspecific and intraspecific competition can become a greater threat.
Since Adélie penguins depend on their fatty stores to survive the harsh winters, limited
food availability could potentially cause an increase in mortality. Currently, climatic
warming is already having a negative impact on krill abundance due to loss of sea ice,
which in turn can alter the entire Ross Sea food web. In addition, increased levels of
precipitation pose a great threat to Adélie penguins and their chicks. More snow could
delay the reproduction process causing a mismatch in hatching times and prey
availability leading to smaller, unfit chicks (Boersma, 2008). Moreover, increased snow
makes traveling to productive foraging grounds more difficult.
The population trends of Adélie penguins and the factors affecting them is a complex
issue that remains unanswered. It is hard to say how the populations will be affected in
the future if climatic warming in the Antarctic continues. It is possible that the already
declining population along the Western Antarctic Peninsula could disappear entirely due
to the rapid warming of that region. And while the Ross Sea colonies are currently
increasing, it is uncertain how a continued increase in precipitation, loss of sea ice and
anthropogenic threats will affect them in the future.
There is no one factor that is responsible for these population changes, rather it is a
complex interaction of climate change, commercial fishing and competitive release. It is
essential that we continue to monitor the Adélie penguin population trend as it is an

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integral part in understanding the complexities of the changes of the Antarctic
ecosystem.

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Appendix
Figure 1: Close up of a portion of the Southern Rookery showing the individual counts

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Figure 2: Aerial view of Cape Bird with 1983 images georeferenced to the 2009 high resolution image

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Figure 3: Northern Rookery. Clockwise from the top left: 1957, 1966, 1983, and 2009. Note:
White and black areas of the 1983 image represent actual locations of Adélie Penguins

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Figure 4: Middle Rookery. Clockwise from the top left: 1957, 1966, 1983, and 2009. Note: White
and black areas of the 1983 image represent actual locations of Adélie Penguins

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Figure 5: Southern Rookery. Clockwise from the top left: 1956, 1957, 1983, and 2009. Note: White
and black areas of the 1983 image represent actual locations of Adélie Penguins, Gold areas
represent possible abandoned nests. Dark blue outlines of the 2009 image represent an outline of
lightly stained guano area

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Figure 6: “Northern Clusters” of the Southern Rookery. Clockwise from the top left: 1956, 1957,
1983, and 2009. Note: White and black areas of the 1983 image represent actual locations of Adélie
Penguins.

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Detailed Methods
* Image formats were a combination of JPEG and TIFF formats.
*ArcGIS 10.1 software, specifically ArcMap 10.1 and ArcCatalog 10.1, were used for the
entirety of this study
1983 Individual Counts
Each 1983 image was analyzed individually using ArcMap 10.1. Corresponding
point shapefiles were created in ArcCatalog 10.1 for each image and then added
as a new layer over the 1983 image. Point symbols were formatted to appear as
hollow colored circles so the “penguin dot” was still visible once marked. Once
an editing session was enabled for the point shapefile, the “Create Features” tool
was used to mark each penguin which appeared as black dots. Total counts can
be viewed in the Attribute Table when finished.
*From here on, all images were edited in a single ArcMap file.
Georeferencing
A high resolution multispectral satellite image from 2009 was used as the
geographical reference for this process. Since none of the images prior to 2009
had spatial reference, they each had to be georeferenced onto the 2009 high
resolution image. The spatial references used for the 2009 image included a
Projection Coordinate System (Stereographic_South_Pole) and a Geographic
Coordinate System (GCS_WGS_1984). The 2009 image was used as the base
layer and consisted of 8 bands. In addition, this layer was set to display as a

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RGB composite (Red=Band 8, Green=Band 7, Blue=Band 4) in order to make
the guano stained areas appear more vibrant.
Using the Georeferencing toolbar, control points were added to the unreferenced
image in order to properly line up the images. Each image was carefully
analyzed for natural features (rivers, lakes, ridges, coastline, etc.) that could be
used in order to match the images. Larger images required more control points
(51 control points were used for the largest image), this ensured a more accurate
fit.
*It should be noted that vector layers, including shapefiles, cannot be
georeferenced. Therefore all editing of shapefiles should be done after all the
images have been georeferenced.
Creating Polygons
Due to lack of visibility of individual penguins (1956, 1957, 1966, and 2009
images), guano-stained areas representing Adélie penguin breeding grounds
were highlighted through the use of polygons. Using ArcCatalog 10.1, polygon
shapefiles were created to represent each year and added as new layers to the
ArcMap file containing all of the georeferenced images. Once an editing session
was enabled and the proper polygon shapefile was selected for a particular
image year, polygons could then be created. This was done by using the
freehand tool under “Create Features”. Each polygon shapefile was given a
different color to distinguish between years. In addition, since individual
penguins were visible for the 1983 images, additional polygons were created to

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outline the guano-stained areas as well as the areas where the penguins actually
resided. Guano-stained areas that appeared to be abandoned nests were
marked as a different color as well (this only applies to the 1983 images).
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