Cloud atlas uses satellite data to predict where species live

Adam Wilson By Jane Palmer Want to save a species? Look to the skies. Patterns in the clouds can be used to decipher the complex patterns of ecosystems on Earth, predicting where species live more accurately than the methods currently used by conservationists. Adam Wilson of the University at Buffalo in New York and his team have developed a technique that uses clouds to map ecosystems in fine resolution. The tool could prove helpful when deciding how best to protect a species or ecosystem, providing a cheaper and easier way to gather habitat data about hard-to-reach locations. Scientists have traditionally predicted all the habitats contained within a region by taking a sample of ground-based measurements, and using these to make a statistical estimate across the whole area. “But imagine how the conditions can vary over mountains and valleys,” says Wilson. “These statistical models aren’t able to capture the fine-grained variability of the environment that can determine where a particular species can survive.” But clouds are different. Because they affect the amount of sunlight and rainfall that reaches the ground, as well as the temperature, clouds help determine what plants can photosynthesise in an area and the animals that can thus survive there. “Sunlight drives almost every aspect of ecology,” says Wilson. “So when you put something in between the sun and plants, that is going to have implications on the amount of energy they are receiving, soil moisture, leaf wetness, and humidity – almost everything that is important.” To map ecosystems using clouds, the researchers took data from NASA’s Terra and Aqua satellites that orbit the Earth. From this information, they built a database of two images a day of cloud cover for nearly every square kilometre of the planet from 2000 to 2014. When they analysed the frequency and timing of cloudy days over those 15 years, they found a pattern that clearly correlated with the different biomes lying below. Adam Wilson To test this correlation, the researchers then picked two species with habitats that are well-known, and used the data to guess where they lived. They did this for the montane woodcreeper, a South American songbird, and the king protea, a South African shrub. The model they had built from the data predicted the distribution of these species better than conventional methods, honing in on a range that was 43 per cent smaller for the woodcreeper, and an area 18 per cent smaller for the shrub. Adam Wilson “This is potentially huge – it’s the first time you have global cloud information at the appropriate grain size of 1 kilometre and from actual observations rather than being interpolated data from weather stations,” says Woody Turner of NASA’s Ecological Forecasting programme. “It could be a great contribution to the field.” Journal reference: PLoS Biology, DOI: 10.1371/journal.pbio.1002415 More on these topics:
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