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					                                                                          Princess Gilbert
                                                                               803115990
                                                                   UP206a- Final Write Up

            A Spatial Analysis of Factors Impacting Chameleon Diversity in Madagascar

                                        Introduction

The Central Problem
“The central problem of speciation is understanding the origin of those isolating barriers
that actually prevent or potentially prevent gene flow in sympatry. This problem is
conceptually simple, but its solution involves two formidable tasks. First, one must
determine which reproductive barriers were involved in the initial reduction of gene flow
between populations. Second, one must understand which evolutionary forces produced
these barriers…” (Coyne and Orr 2004).
If the above is true for the study of speciation which involves two or more species, such a
methodology can be adapted and applied to the study of diversification at the
intraspecific level. This dissertation proposal seeks to do just that by: (1) identifying the
initial reduction of gene flow within one species; (2) determining the barriers which are
involved in this reduction; and (3) elucidating how selection acts upon the genome of that
species and partially reduces gene flow.

Why Madagascar?
Madagascar presents an ideal natural setting for the study of evolutionary processes.
Isolated from any other land mass for roughly 88 million years, the flora and fauna of
Madagascar have evolved in complete isolation. Such insular isolation allows one to
compare a simpler microcosm with the seemingly infinite complexity of continental and
oceanic biology (MacArthur and Wilson 1967).
Madagascar is exceedingly rich in endemic species. Ninety-five percent of the reptile
species, 99% of the amphibian species, and 100% of the primate species are endemic
(Yoder and Nowak 2006). This increases the ease with which one can study
diversification.
Madagascar is also diverse in habitats and climate (see figure 1). Madagascar contains 6
unique biomes which evolved under differing paleogeographic regimes. Following its
                                                                                         o
separation from Gondwana, India-Madagascar moved into the subtropical arid belt 30
below the equator. This resulted in the formation of the arid spiny bush and dry
deciduous forest biomes 88 Mya (Wells 2003). 66-58 Mya, during the late
Paleocene/early Eocene, the combination of Madagascar’s movement northward into the
equatorial tropical belt and the onset of southeasterly trade winds from the India Ocean,
created the eastern evergreen rainforest via orographic precipitation. The northwestern
Sambirano rainforest formed most recently (8Mya) following the initiation of the
Indian monsoons. The formation of montane ericoid thicket and central highlands are
yet to be resolved.
Why Chameleons?
Within the unique island of Madagascar, chameleons present a wonderful taxa for the
study of diversification. Three genera within the Old World family Chamaeleonidae are
endemic to Madagascar: Brookesia, Calumma and Furcifer (Klaver and Bohme 1986).
The Furcifer genus are inhabitants of arid regions in the west, however, two species
(lateralis and oustaleti) are found in western evergreen rainforests (Glaw and
Vences 1994). The characteristically slow movement of chameleons also makes for easier
sample collection.
Furcifer oustaleti is an extremely widespread species. It specializes in dry wooded
habitats and, with the exception of lateralis, is the only chameleon adapted to the dry
environments of the south as well as the highlands and humid eastern evergreen
rainforest. It is the largest known chameleon (males up to 685 mm TL)(Glaw and Vences
1994). This makes Furcifer oustaleti an ideal species to study phylogeography.
According to their distribution, F. oustaleti should be found in all 6 major biomes
allowing for cross-habitat comparisons and sample replicates

Integration with UP206a
         I am a PhD student in the Ecology and Evolutionary Biology Department and Dr.
Estrada has graciously allowed me to enroll in this urban planning course. Because the
nature of my dissertation deals with evolutionary processes in Madagascar my midterm
and final project were on this geographical location. I created maps of Madagascar at
multiple levels illustrating its landscape ( i.e. forest cover, major rivers), administrative
provinces, ecoregions (6), a human index grid, human footprint grid, “Last of the Wild”
vector data, and deforestation/fires data which affected resea rch areas of interest for my
study species.
    For the midterm project I sought to introduce Madagascar & its major provinces,
locate provinces in which my species occurred, illustrate areas of expected low gene flow
and I sought to show how fires are an increasing threat to chameleon habitats and pristine
areas. For the final project I wanted to illustrate Madagascar’s global position using
satellite images, give a deeper explanation of my sampling regime, give a description of
my study sites, habitats and biological ecoregions, illustrate the impact of crop lands on
chameleon habitats and show a deeper exploration of daily occurring fire data with
Spatial Clustering Analysis.
    My current hypothesis is that the genetics of the individuals from my populations will
indicate a phylogeographic pattern. The most prevalent hypothesis in the literature is that
rivers have played a large role in the prevention of gene flow between populations
historically. For the “original data” requirement of the final project, I incorporated the
actual GPS locations and place names where my samples were collected by staff
members of the Henry Doorly Zoo ( Omaha, Nebraska). Layouts including this data will
be identified in the following description of final project.
                                   Layout Descriptions

                                        Layout 1




As stated in my introductory section, I wanted to illustrate Madagascar’s global position
using satellite images I acquired from
http://landsat.usgs.gov/gallery_view.php?category=nocategory&thesort=mainTitle
In the layout above I geocoded the Madagascar file so that it would have the correct
geographical position spatially in the world and correctly align with the “Continents”
shape file I acquired from UCLA’s Map Share website. I turned on major city names for
labeling which were included in the attribute table and changed the font colors and sizes
so that they would be more visible on this high resolution map. I also included a key, for
which I altered the fonts and text colors to match.

                                         Layout 2
        Layout 3 was my favorite layout of the project because it illustrated the biological
story behind project. As shown above, the sites in which my samples were collected are
represented by the small “reptile” icon. Rivers are shown in light grey lines and bodies of
water are in blue. I used symbology to turn each ecoregion into a different color shade of
green. This emphasizes the fact that my study species does in fact occur in many types of
habitats found in Madagascar. This is exciting because one would expect these varying
populations to have varying genetic structures due to their differing environments. This
map is also exciting because it shows that my samples were collected from all parts of the
island. This will allow me to look for indications of genetic difference due simply to
isolation by distance and such a finding would be meaningful when juxtaposed to
competing theories which offer explanations of island diversity.
        Again, all shape files were geocoded so that size and distances could be measured
correctly.
                                          Layout 3
Layout 3 is my most complex layout because it included a wealth of information with
regards to sampling. The first satellite image used in Layout 1 appears here again, but this
time I added my sample collection sites. I also included the major rivers and I used the
“Select by Attribute” feature to highlight rivers which were in within a 5 mile distance of
my collection sites. Those rivers are highlighted in orange. As shown in the inset, at least
two of my collection sites overlap with a river ( Tsimanpetsotsa and Masoarive). Future
sampling would need to insure populations on both sided of the rivers were sampled to
compare genetic histories at the fine scale level. Overall, for the rivers highlighted, both
sides of the river seem to be sampled which really allows me look for indications of
unique genetic history ( I’m very excited about this finding).
        For the bottom maps, I wanted to emphasize sample sizes. As the legend
indicates, two image sizes were used for collection sites; those with less that two samples
( or individuals) and those with more than 2. The main thing I wanted to show was that
most of my sites have been under sampled. This simply illustrates the need for more
sampling at these sites so statistical conclusions can be made about those data coming
these sites. This is something I hope to personally accomplish in the 2009.

                                         Layout 4
Layout 6 illustrates how crops and agriculture might be impacting the habitats of my
chameleons. I also layered this map with a forested area shape file I found on MapShare
and I included rivers and lakes for reference. As emphasized in the inset maps, multiple
sites are in close proximity to crop lands. This means that the pristine habitats in which
these populations might evolved is being lost and this can lead to a number of genetic
consequences for the species who live in these places. This layout really shows the need
for conservation of pristine lands and habitats. It’s difficult to say what the genetic impact
of such activity might be on my chameleon study. But the existence of an anthropogenic
impact at all can be viewed as a negative.

                                          Layout 7
         Layout 7 is in the same theme as layout 6 in that it illustrates the impact of human
activity on my study as well as Madagascar as a whole. In this layout I picked the
heaviest day of recorded fire incidences ( December 1, 400 fires) and selected locations
based on their brightness indices ( information that was provided in the attribute table). I
made the sizes of the dots reflective of the brightness of the fire. Colleagues in my
laboratory believe that brightness is an indication of the size of the fire picked up by the
satellite. I wanted to know if city proximity had any emphasis on the size of the fire, but
the largest fires appeared to occur far away from major cites; in rural areas. Sadly, an
abundance of fires are occurring in forested areas. This most likely illustrates the
prevalence of slash and burn agriculture. For more information on this fire database
please see:
http://images.google.com/imgres?imgurl=http://www.maildogmanager.com/pics/hotspots
/35img2.jpg&imgrefurl=http://maildogmanager.com/page.html%3Fp%3D000001XDDtj
KFP98UZkgchujPw4uhcMNdgVqw%3D&usg=__zFkVVZH0xLiaDIH49uKjBoOi_jk=
&h=133&w=200&sz=10&hl=en&start=213&sig2=W8IJoQv-
VPG9jSugCzwo2g&um=1&tbnid=TbfIsVEK_dEo3M:&tbnh=69&tbnw=104&ei=qgE3S
fffDYXaNdnarbYP&prev=/images%3Fq%3DMadagascar%2Bshapefiles%26start%3D19
8%26ndsp%3D18%26um%3D1%26hl%3Den%26client%3Dfirefox-
a%26rls%3Dorg.mozilla:en-US:official%26sa%3DN
.
                                           Layout 8
Because I was able to acquire fire data from everyday in the month of November I
decided to see if there were any statistical patterns that could be concluded. To do so, I
conducted a multi-distance spatial cluster analysis. This ArcGIS utility tool looks for
clustering of fire incidences. It assumes that all points are random and tells you if the
incidences are not random and by how much. Here we see that the y do cluster because
the observed k is much greater that the upper confidence interval. If the obs. k falls
between lower and upper confidence intervals the data is random. A special thanks goes
Dr. Henri Thomassen, a post-doc in Dr. Tom Smith’s lab who helped me with this
endeavor.
                                         Conclusions
Human Impact on Chameleon Genetics
         Future work requires that I investigate the time scale of human impacts versus
that of environmental variables on my dissertation study. It is assumed that genetic
differences which might arise from human hab itat alterations are not detected by
mitochondrial analysis. That level or resolution of disturbance is at too short a time frame
to tremendously impact living or extant species. But whether this truly the case remains
to be proven.
Dispersal Ability
         Genetic dispersal distances are critical to establishing any real or meaningful
hypothesis about diversifying processes. The strongest determin ing factor which will
affect gene flow is my chameleon’s ( any other taxa’s) ability to disperse and
subsequently mate. “Low-dispersing” taxa are expected to be most impacted by rives for
this reason. But dispersal ability does play a tremendous role and I would have liked to
have incorporated that into this analysis.
Conservation
         Conservation appears to be the most necessary step. The biodiversity of
Madagascar is unlike that of any other place in the world. I was drawn to evolutionary
biology in Madagascar because it presents the ideal location to study the results of strong
diversifying processes. Selection pressures in combination with separation have created
unique populations which have, overtime, diverged and evolved into different species
uniquely adapted for their environments. As a young scientist who would like to trace
this process in reverse; from present to past, conserving the stability of these processes is
paramount and critical to my understanding of the underlying forces at work. At an even
more grim level, none of this work or knowledge, is valuable if the areas these species
live in and have evolved in are lost. Loss of habitat unravels the stabilizing processes
which have created and maintained the beautiful diversity which exists today.

				
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