AMERICAN MUSEUM OF NATURAL HISTORY BIOLOGIST AND COLLEAGUES DEVELOP COMPUTER MODELS THAT ACCURATELY PREDICT WHERE REPTILE SPECIES LIVE IN MADAGASCAR

FINDING SHOWS SATELLITE DATA AND MUSEUM SPECIMENS CAN ACCELERATE EFFORTS TO COMPLETE SPECIES INVENTORIES, AID THE DESIGN OF FUTURE RESERVES, AND EVEN HELP FIND NEW SPECIES

January 2004—An American Museum of Natural History biologist and his colleagues have developed a modeling approach that uses satellite data and specimen locality data from museum collections and that successfully predicts the geographic distribution of 11 chameleon species in Madagascar. In an unanticipated result especially useful to conservation efforts, the models also correctly predicted the existence of previously unknown areas of chameleon distribution, which included 7 chameleon species new to science. This discovery suggests that for poorly explored regions, satellite data and data from museum collections can help identify promising places to survey for new species-an exciting development, especially beneficial to the conservation community.

Understanding the distribution of a species is one of the most important and basic requirements for both effective conservation and fundamental ecological and evolutionary research. Yet most tropical species have not yet been surveyed well enough to allow an accurate assessment using conventional methods, in which biologists visit a region in an intensive effort to locate and count species. The results of this study, led by Christopher J. Raxworthy, Associate Curator in the American Museum of Natural History's Division of Vertebrate Zoology, and six colleagues, demonstrate overall that existing museum collections and satellite measurements of Earth's surface and climate can be used to accurately predict species distributions anywhere on Earth—even in poorly known tropical regions. This study is the first to successfully predict the distribution of any species in Madagascar using satellite imagery and information from museum specimens, and 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 acquisition of detailed descriptions of exactly where Earth's rich biodiversity lives, species by species, requires decades of dedicated fieldwork. In Madagascar, teams of highly trained biologists visit often remote sites to do this work. A paucity of complete data on the regional distribution of species, especially in more remote areas, is one of the major factors that complicates and potentially delays conservation decisions that could save threatened flora and fauna if made in a timely manner. This new research by Dr. Raxworthy and his associates, published in a recent issue of the journal Nature, demonstrates conclusively that there is a technological solution that can speed up the process of regional species inventories and thereby prevent unnecessary loss of threatened animals, especially in tropical environments with diverse habitats and climates. The research also shows that 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 the most accurate biogeographic distribution predictions.

This new chameleon prediction study, described in the article by Dr. Raxworthy; Ned Horning, Program Manager of the Museum's Center for Biodiversity and Conservation's Remote Sensing/GIS Laboratory; and their co-authors, tested the accuracy of several distribution models based on information gathered from historical museum specimens collected prior to 1978 and on modern data from specimens collected after 1988 against other locality data that was set aside for testing purposes, and against recent inventories of 11 sites where chameleons were also surveyed. Although the historical data alone prove to be predictive in ways that are useful to conservation decision-makers (74.7 percent accuracy), and accuracy improved with the combination of modern and historical data (82.8 percent accuracy), the team found that modern data alone were the best predictor of where the 11 chameleon species live (85.1 percent accurate). This is probably because some historical collecting sites have been more recently cleared of forest, and so these sites now provide inaccurate information to modern satellites. All of the models rely on environmental data collected by several satellites and the Space Shuttle, provided by the National Aeronautics and Space Administration (NASA), U.S. Geological Survey, and National Oceanic and Atmospheric Administration (NOAA). Environmental data include land cover (as viewed from space), rainfall, cloud cover, average and seasonal temperatures, and topographic data, which were input into GARP (Genetic Algorithm for Rule-set Prediction), 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 Dr. Raxworthy and his colleagues examined the models, for 4 species they found overlapping areas of error where the models incorrectly predicted that the species lived. Examining their field data collected in two of these regions, they realized that these areas actually contained 7 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 critical conservation importance because they provide habitats for locally confined species that had been previously unrecognized. Identifying neglected areas with unique biodiversity currently has enormous value in Madagascar, because the Malagasy Government recently announced plans to expand the protected area network, thus providing a new opportunity to conserve species currently excluded from the island's existing reserves.

"Our results show that distribution models can help scientists and those who make conservation decisions determine areas with potential unrecognized biodiversity," Dr. Raxworthy said. "In many tropical areas on Earth, time is running out to make important conservation decisions for threatened species. This approach, combining old and recent museum specimen locality data and satellite technology, now gives us a fast-track way to obtain an informative biogeographic understanding of species distributions, which opens the door to more effective conservation planning, and allows biologists to better explore big questions in tropical ecology and evolutionary biology. The ability to predict areas with good potential for new species to science is especially exciting."

Dr. Raxworthy has nearly 20 years of experience conducting herpetological fieldwork in Madagascar, which includes a wide range of habitats and an exceptional diversity of species, many of which are found only on this large island. Although reserves are already in place to conserve Madagascar's biodiversity, current rates of deforestation underscore the urgent need to further expand the reserve network, which requires accurate distribution information that policy-makers can use to make informed and timely conservation decisions. As Dr. Raxworthy and his colleagues have demonstrated in this new paper with chameleons, continued modeling with many more species could significantly speed up and advance efforts to prevent the future loss of species and their habitats in Madagascar, despite the lack of detailed information on much of the country's biodiversity. Significantly, this same approach can also be applied to any other area worldwide. For poorly surveyed regions requiring urgent conservation action (unfortunately, typical for most tropical countries), existing museum specimens may thus represent a powerful resource for conservation planning.

Given the island's wealth of diverse animal species, several other Museum curators and scientists have conducted extensive fieldwork in Madagascar, including Eleanor Sterling (lemurs), Director of the Center for Biodiversity and Conservation (CBC), Ian Tattersall (lemurs), Curator in the Division of Anthropology, Melanie Stiassny (fish), Axelrod Research Curator in the Division of Vertebrate Zoology, Ross MacPhee (mammals), Curator in the Division of Vertebrate Zoology, Mark Siddall (leeches and crocodiles), Associate Curator in the Division of Invertebrate Zoology, John Sparks (fish), Assistant Curator in the Division of Vertebrate Zoology, and Howard Rosenbaum (whales), Conservation Associate with the CBC.

In 1998, the CBC established the Remote Sensing and Geographical Information Systems (RS/GIS) Facility and devoted it to biodiversity conservation. Using data from digital imagery, satellites, and other scientific instruments, scientists in these laboratories so far have identified potential survey sites, analyzed deforestation rates, studied vegetation cover, developed and implemented spatial and non-spatial databases, and created persuasive visual aids. This valuable technology helps scientists communicate with community members, resource managers, and government officials, and contribute to effective decision-making. Unlike conventional maps, GIS maps are easily updated as new data becomes available and can convey multiple levels of information at once. Along with this new chameleon prediction project by Dr. Raxworthy and his associates, Dr. Rosenbaum and his colleagues regularly use the lab to analyze data collected on the distribution of humpback whales in the ocean waters off Madagascar. Such an analysis can reveal if different classes of humpbacks have preferences for specific areas during the breeding season, findings which have implications for the whales' migratory patterns.

The chameleon prediction project was supported by NASA under award No. NAG5-8543 and by the Center for Biodiversity and Conservation at the American Museum of Natural History. NASA also provides support for the RS/GIS Facility.

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