Data Mining for Global Trends in Mountain Biodiversity

Thanks to advances in electronic archiving of biodiversity data and the digitization of climate and other geophysical data, a new era in biogeography, functional ecology, and evolutionary ecology has begun. In Data Mining for Global Trends in Mountain Biodiversity, Christian Korner, Eva M. Spehn, and a team of experts from the Global Mountain Biodiversity Assessment of DIVERSITAS explore two of the hottest subjects in science and technology: biodiversity and data mining. They demonstrate how to harness the scientific power of biological databases for furthering ecological and evolutionary theory.Expert contributors address two aspects of the Global Mountain Biodiversity Assessment. They cover how to link biodiversity data with geophysical data and how to use biodiversity data to substantiate evolutionary and ecological theory. The text provides different methodological approaches and examples of successful mining of geo-referenced data in mountain regions on various scalesIt includes: * Elevational and latitudinal gradients in plant diversity * E-mining trends in diversity of Lepidoptera, beetles, and birds * Niche modeling to explain past trends and predict future trends in mountain biodiversity * Sharing biodiversity data with the Global Biodiversity Information Facility