NASA supported biologists developed a modeling approach
that uses satellite data and specimen locality data from
museum collections to predict successfully the geographic
distribution of 11 known chameleon species in Madagascar. The
model also helped lead to discovery of 7 additional chameleon
species new to science.
The discovery suggests for poorly explored regions, NASA
satellite data and data from museum collections can help
identify promising places to survey for new species of life,
while locating areas likely to be of conservation importance.
The results of this NASA-funded study, led by American Museum
of Natural History biologist, Christopher J. Raxworthy,
Associate Curator, division of Vertebrate Zoology, and six
colleagues, demonstrated existing museum collections and
satellite measurements of Earth’s surface and climate hold
great promise for the accurate prediction of species
distributions.
The findings, published in the latest issue of the journal
Nature, demonstrate an approach for speeding up the process
of regional species inventories, especially in poorly known
tropical environments with diverse habitats and climates. The
research also shows, both historical and modern field data
can be extremely useful for predicting chameleon species
distribution in Madagascar, although contemporary field data
used in concert with satellite data provides more accurate
biogeographic distribution predictions.
This study is the first to successfully predict the
distribution of any species in Madagascar using satellite
imagery and information from museum specimens. It is also the
first to evaluate the predictive usefulness of historical
museum specimens in collections (dating back to the 1800s)
versus recently collected field data from Madagascar.
The island nation, with a terrain of narrow coastal plain,
high plateau and central mountains, is home to an
extraordinary diverse group of species, making it an
excellent location for this type modeling.
This work is consistent with a new element of the NASA Earth
Science applications program focusing on ecological
forecasting. The program uses Earth observation data and
models to forecast species distributions and how
environmental change might affect them.
This new chameleon prediction study tested the accuracy of
several distribution models. The models, based on information
gathered from historical museum specimens collected prior to
1978 and on modern data from specimens collected after 1988,
were compared against other locality data that was set aside
for testing purposes, and against recent inventories of 11
sites where chameleons were also surveyed.
All of the models rely on environmental data collected by
several NASA satellites, a Space Shuttle radar mapping
mission, U.S. Geological Survey and National Oceanic and
Atmospheric Administration data sets. Environmental data
included land cover (as viewed from space), rainfall, cloud
cover, average and seasonal temperatures, and topographic
data, which were input into the Genetic Algorithm for Rule-
set Prediction (GARP), a software package for biodiversity
and ecology research that allows users to predict species
distributions.
The intriguing result that ended up predicting where to
locate chameleon species previously unknown to science arose
unintentionally. When the researchers examined the models for
four species, they found overlapping areas of error about
where the models predicted that the species lived.
Examining their field data collected in two of these regions,
they realized these areas actually contained seven other
closely related species that are new to science. The areas
that initially seemed to represent “error” in the models
pointed to regions that are of importance, because they
provide habitats for locally confined species that had been
previously unrecognized. Through careful evaluation of their
model, the researchers made this serendipitous discovery.
“Our results show that distribution models can help
scientists and those who make conservation decisions
determine areas with potential unrecognized biodiversity,”
Raxworthy said.
The research was funded in part by NASA’s Earth Science
Enterprise, a long-term research effort dedicated to protecting
and understanding of our home planet, while inspiring the next
generation of explorers.
