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Trends in ecology & evolution (Amsterdam), 2015-11, Vol.30 (11), p.685-696
2015
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Autor(en) / Beteiligte
Titel
Emerging Technologies to Conserve Biodiversity
Ist Teil von
  • Trends in ecology & evolution (Amsterdam), 2015-11, Vol.30 (11), p.685-696
Ort / Verlag
England: Elsevier Ltd
Erscheinungsjahr
2015
Quelle
Access via ScienceDirect (Elsevier)
Beschreibungen/Notizen
  • Technologies to identify individual animals, follow their movements, identify and locate animal and plant species, and assess the status of their habitats remotely have become better, faster, and cheaper as threats to the survival of species are increasing. New technologies alone do not save species, and new data create new problems. For example, improving technologies alone cannot prevent poaching: solutions require providing appropriate tools to the right people. Habitat loss is another driver: the challenge here is to connect existing sophisticated remote sensing with species occurrence data to predict where species remain. Other challenges include assembling a wider public to crowdsource data, managing the massive quantities of data generated, and developing solutions to rapidly emerging threats. Conservation requires methods to identify species and to identify, locate, and track individual plants and animals. These methods have become better, faster, less intrusive, and cheaper. So, too, has remote sensing that now allows detailed and frequent assessments of species’ habitats and how human actions are changing them. Even the best technologies to mark individuals may pose unacceptable hazards for endangered species. Creative approaches find new, non-invasive alternatives. Crowdsourced data are becoming the dominant source of information on species’ distributions and new approaches are solving the problems of reliability. The most important trends are progress in technologies that are appropriate to the often remote and low-technology environments in which frontline conservation actions unfold and the inclusion of previously unused communities who might contribute essential data.
Sprache
Englisch
Identifikatoren
ISSN: 0169-5347
eISSN: 1872-8383
DOI: 10.1016/j.tree.2015.08.008
Titel-ID: cdi_proquest_miscellaneous_1735915848

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