For
further information contact: GIS
Communications
 Put
simply, knowing where an organism is, why is it there, what
it does there, and what it is likely to do under future conditions
can be invaluable in our efforts to identify where wild plants
live and how cultivated plants perform. But very few locations
within the developing world provide enough information to
enable us to know. Thus we are obliged to use scientific principles
to lever information from the few sites we do know about to
guess what might happen at those for which we have insufficient
information.
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MarkSim
and FloraMap
MarkSim™ represents the culmination of over 25 years
of world-class research to solve this problem, by simulating
high-resolution, daily weather data for the entire pan-tropical
region. It does this on the basis of the statistical characterization
(Markov simulation) of data from 11,000 weather stations
worldwide, and estimating similar values for each 18-km
grid cell. The MarkSim method has been rigorously tested,
and has now been released as a Windows® commercial version
on CD-ROM with a 96-page users' manual.
FloraMap™
predicts the geographic distribution, or areas of possible
adaptation, of natural organisms when little or nothing
is known of their detailed physiology. FloraMap thus cuts
much of the guesswork, legwork, and costs typically involved
in tracking down species of plants and other organisms in
the wild. The Windows application is especially useful to
plant breeders, who increasingly look to wild species as
a source of new genetic material. It is based on the assumption
that the climatic characteristics of sites where the species
has already been collected are a good indicator of its environmental
range.
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Impact
of Climate Change on Agricultural Production
 We
are working on studies that allow the prediction of potential
impact of climate changes on agricultural production systems,
to focus the research to combat these effects, and to identify
the probable reaction of the agricultural and animal production
systems that face them.
An
example of this work is a study on maize in Africa and Latin
America, whose preliminary results present a complex image.
Although some areas benefit from climate change, they are
relatively small highland areas. Even though rainfall increases
in some areas, the lowland regions generally show a fall
in yields and greater yield instability. Some areas will
become almost completely unsuitable for growing maize.
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Biogeography
of Wild Peanut Genetic Resources
 This
analysis permits the development of stable strategies for
the conservation and use of this genetic resource, whose importance
derives from being the wild relative of a commercial crop.
The
conservation status of wild Arachis spp. is not well characterized
for its maintenance and possible future exploitation for the
improvement of cultivated peanut, Arachis hypogaea (L.).
Our
objectives were to use 2175 georeferenced observations of
wild peanut (Arachis spp.) to assess the conservation status
of the genus, and to biologically and geographically prioritize
future conservation actions.
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| Patterns
of Plant Diversity in Tropical Forests
CIAT
is participating in this project led by the HERB
Project from King's College
London, with the objective of understanding the drivers
behind the generation of plant diversity in tropical forests.
We are using spatial models, developed from ecological principles,
and aerial imagery to monitor and model the distribution of
diversity. It is hoped that methods for a priori diversity
analysis will help target inventory and in situ conservation
initiatives. These models are being developed in the cloud
forest of Reserva Tambito, Cauca, Colombia, and in the Amazonian
forest of Tiputini Biodiversity Reserve, Napo, Ecuador.
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Supporting
Ex Situ Collection of Wild Chilli in Paraguay: Using GIS
to Prioritize Areas to Visit
 This
research theme makes use of FloraMap to prioritize an ex
situ collection of germplasm of a rare wild chilli (Capsicum
flexuosum) in Paraguay. Climate was used to predict
the potential distribution based on the 19 observations
that have been made of this species. Only two of these are
germplasm collections, and the rest herbarium specimens.
The predicted distribution is further refined through use
of land cover data to locate forest edges where this wild
chilli is known to be found. The final map defines priority
locations along roads where USDA and IPGRI biologists may
find this species. A collecting mission was made based upon
these predictions in March 2002, and collected six new populations
of this species, all but one in areas where the GIS predictions
showed high priority. This increased the amount of germplasm
collections for this important species fourfold. We are
now analyzing these results in detail to further improve
our a priori distribution modeling of important species.
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Mapping
Adaptive Genetic Diversity
Understanding
the spatial distribution of genetic diversity within a species
range is of considerable importance to conservation and sustainable
wildlife management. Genetic diversity provides the basis
for both adaptation to changing environmental conditions and
to future evolutionary change. As such, its conservation is
an essential part of more general programs to protect biodiversity.
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