| Literature DB >> 28812589 |
Alex Bush1,2,3, Rahel Sollmann4, Andreas Wilting5, Kristine Bohmann6,7, Beth Cole8, Heiko Balzter8,9, Christopher Martius10, András Zlinszky11, Sébastien Calvignac-Spencer12, Christina A Cobbold13, Terence P Dawson14, Brent C Emerson15,7, Simon Ferrier3, M Thomas P Gilbert6,16, Martin Herold17, Laurence Jones18, Fabian H Leendertz12, Louise Matthews13, James D A Millington14, John R Olson19, Otso Ovaskainen20,21, Dave Raffaelli22, Richard Reeve13, Mark-Oliver Rödel23, Torrey W Rodgers24, Stewart Snape25, Ingrid Visseren-Hamakers26, Alfried P Vogler27,28, Piran C L White22, Martin J Wooster14,29, Douglas W Yu1,7.
Abstract
Understandably, given the fast pace of biodiversity loss, there is much interest in using Earth observation technology to track biodiversity, ecosystem functions and ecosystem services. However, because most biodiversity is invisible to Earth observation, indicators based on Earth observation could be misleading and reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing and modern ecological modelling to extract much more of the information available in Earth observation data. This approach is achievable now, offering efficient and near-real-time monitoring of management impacts on biodiversity and its functions and services.Year: 2017 PMID： 28812589 DOI： 10.1038/s41559-017-0176
Source DB: PubMed Journal: Nat Ecol Evol ISSN： 2397-334X Impact factor: 15.460