Chameleon Conservation Project 

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National Aeronautics and Space Administration (NASA)

Remote Sensing Imagery: Moderate Resolution Imaging Spectroradiometer satellites (MODIS), National Oceanic and Atmospheric Administration satellites (NOAA), Shuttle Radar Topography Mapping Mission satellites; GIS software: ArcView, GARP

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Chameleon

Madagascar is one of 25 biodiversity hotspots. Researchers do not know for certain what species exist in remote areas of the tropics and lack the knowledge to pinpoint the best places to look for specific species. The aim is to use remote-sensing technology to understand relationships between species and their habitats, to make the search for important species and habitats quicker and easier and to be determined what areas of forest can be saved. To provide natural resource managers in Madagascar with guidance on where their conservation efforts would preserve the most biodiversity. To produce a tool to describe the island’s biodiversity more efficiently.

• The scientists started with a scattering of chameleon location data points from museum records and added the environmental characteristics to the habitats.
• The habitat of the area was chartered using data from a sensor on NASA’s Terra satellite: the Moderate Resolution Imaging Spectroradiometer (MODIS). Ideal as the sensor sees a large area at once and so smaller images do not need to be stitched together.
• The sensor’s near-daily coverage also allowed data from different seasons to be looked at - seasonal changes in vegetation helps to identify what kind of ecosystem is being viewed – and other environmental observations.
• MODIS land cover maps and environmental characteristic data were passed over to the GARP genetic algorithm (Genetic Algorithm for Rule-set Prediction) - a computer program that determines the environmental characteristics that influence where the species lives.
• GARP selected the ten of the best models that predicted where each species would and would not be found in Madagascar. The models predicted a 75% of the modern-day chameleons found at the 11 test sites.
• The scientists overlaid the results of the ten best models onto a single, shaded map that showed the species’ range. Four of the eleven chameleon species ranges over-lapped and the computer “over-predicted”  - saying a species of chameleon existed somewhere that scientists were sure that it didn’t. New species of chameleon specimens collected on a previous expedition to Madagascar were found to come from these over-lapping areas

• Remote sensing technology can be useful for ecological niche modelling—to predict the unique locations, or niches, where species or ecological communities exist.
• A time benefit was involved – it would take years to send out survey teams to areas to collect habitat descriptions. 
• Discovered a powerful new tool for identifying locations with a much-greater-than-average chance of being home to previously unknown species. These models could save time by helping field-workers to decide where in the country to go.
• In a more theoretical direction the models can help biologists go back in time and describe where a species might have lived at some point in the past.  They could be used to predict how the ranges and locations of today’s species will change with climate change, another factor to consider when planning parks and preserves.

Testing the conclusions with a much broader suite of species in Madagascar.

• Novel results can lead to a new way of seeing old problems, and provide unexpected insights to other unanticipated aspects of the study
• With distribution modelling, a key factor that must always be addressed, concerns model quality

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