globalchange  > 全球变化的国际研究计划
DOI: 10.1016/j.tree.2013.01.009
论文题名:
The evolutionary time machine: Using dormant propagules to forecast how populations can adapt to changing environments
作者: Orsini L.; Schwenk K.; De Meester L.; Colbourne J.K.; Pfrender M.E.; Weider L.J.
刊名: Trends in Ecology and Evolution
ISSN: 1695347
出版年: 2013
卷: 28, 期:5
起始页码: 274
结束页码: 282
语种: 英语
英文关键词: Adaptation ; Climate change ; Environmental genomics ; Evolution ; Network analysis ; Paleogenomics ; Resurrection ecology
Scopus关键词: ice ; adaptation ; climate change ; data set ; DNA ; evolution ; evolutionary theory ; genomics ; permafrost ; adaptation ; animal ; climate change ; environmental monitoring ; evolution ; genetics ; methodology ; phylogeny ; population dynamics ; review ; species extinction ; Adaptation, Physiological ; Animals ; Biological Evolution ; Climate Change ; Environmental Monitoring ; Extinction, Biological ; Ice ; Phylogeny ; Population Dynamics
英文摘要: Evolutionary changes are determined by a complex assortment of ecological, demographic, and adaptive histories. Predicting how evolution will shape the genetic structures of populations coping with current (and future) environmental challenges has principally relied on investigations through space, in lieu of time, because long-term phenotypic and molecular data are scarce. Yet, dormant propagules in sediments, soils, and permafrost are convenient natural archives of population histories from which to trace adaptive trajectories along extended time periods. DNA sequence data obtained from these natural archives, combined with pioneering methods for analyzing both ecological and population genomic time-series data, are likely to provide predictive models to forecast evolutionary responses of natural populations to environmental changes resulting from natural and anthropogenic stressors, including climate change. © 2013 Elsevier Ltd.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/67430
Appears in Collections:全球变化的国际研究计划
气候变化与战略

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作者单位: Laboratory of Aquatic Ecology, Evolution and Conservation, University of Leuven, Ch Deberiotstraat 32, 3000, Leuven, Belgium; Indiana University, The Center of Genomics and Bioinformatics, Myers Hall 915 E 3rd Street, Bloomingtonm, IN 47405-3700, United States; Institute for Environmental Sciences, University of Koblenz-Landau, 76829 Landau/Pfalz, Germany; Biodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25, 60325 Frankfurt am Main, Germany; Department of Biological Sciences, Eck Institute for Global Health and Environmental Change Institute, Galvin Life Science Center, Notre Dame, IN 46556, United States; Department of Biology, Program in Ecology and Evolutionary Biology, University of Oklahoma, Norman, OK 73019, United States; School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom

Recommended Citation:
Orsini L.,Schwenk K.,De Meester L.,et al. The evolutionary time machine: Using dormant propagules to forecast how populations can adapt to changing environments[J]. Trends in Ecology and Evolution,2013-01-01,28(5)
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