Researchers have used remote sensing data to map out the functional diversity of the Peruvian Andes and Amazon basin, a technique that revealed hotspots for conservation. The prioritizing of conservation in the tropics is often hampered by the sparseness of ground data on biological diversity. Recent advances in airborne laser-guided imaging spectroscopy offer a means to gather sufficient data remotely, however, which can shed light on traits such as photosynthesis rates and foliar phosphorus and calcium levels, for example, which are indicative of species make up. Here, Gregory Asner and colleagues combined such spectroscopy data with computational machine learning to generate diversity maps for a large portion of the of the Peruvian Andes and Amazon basin. In total they identified 36 forest functional classes that could be further subcategorized into six forest functional groups (FFGs). Next they used government land allocation data determine the degree to which each group is affected by petroleum oil exploration and logging. Between 32 and 46% of each mapped FFG is currently protected, of which about two-thirds are under government control and one-third is on indigenous lands, the authors report. This work is highlighted in a Perspective by Valerie Kapos.
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Journal
Science