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The evolutionary time machine: using dormant propagules to forecast how populations can adapt to changing environments

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.
- Oklahoma City University United States
- Senckenberg Biodiversity and Climate Research Centre Germany
- Environmental Change Institute United Kingdom
- University of Koblenz and Landau Germany
- Oklahoma City University United States
Climate Change, Ice, Population Dynamics, Extinction, Biological, Adaptation, Physiological, Biological Evolution, Animals, Phylogeny, Environmental Monitoring
Climate Change, Ice, Population Dynamics, Extinction, Biological, Adaptation, Physiological, Biological Evolution, Animals, Phylogeny, Environmental Monitoring
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).120 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
