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Molecular Ecology
Article . 2023 . Peer-reviewed
License: CC BY NC
Data sources: Crossref
https://doi.org/10.22541/au.16...
Article . 2023 . Peer-reviewed
Data sources: Crossref
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Temporal collections to study invasion biology

Authors: Amy S. Kim; Julia M. Kreiner; Fernando Hernández; Dan G. Bock; Kathryn A. Hodgins; Loren H. Rieseberg;

Temporal collections to study invasion biology

Abstract

AbstractBiological invasions represent an extraordinary opportunity to study evolution. This is because accidental or deliberate species introductions have taken place for centuries across large geographical scales, frequently prompting rapid evolutionary transitions in invasive populations. Until recently, however, the utility of invasions as evolutionary experiments has been hampered by limited information on the makeup of populations that were part of earlier invasion stages. Now, developments in ancient and historical DNA technologies, as well as the quickening pace of digitization for millions of specimens that are housed in herbaria and museums globally, promise to help overcome this obstacle. In this review, we first introduce the types of temporal data that can be used to study invasions, highlighting the timescale captured by each approach and their respective limitations. We then discuss how ancient and historical specimens as well as data available from prior invasion studies can be used to answer questions on mechanisms of (mal)adaptation, rates of evolution, or community‐level changes during invasions. By bridging the gap between contemporary and historical invasive populations, temporal data can help us connect pattern to process in invasion science. These data will become increasingly important if invasions are to achieve their full potential as experiments of evolution in nature.

Keywords

Biological sciences, Biochemistry & Molecular Biology, Evolutionary Biology, Science & Technology, Ecology, Museums, DNA, Life Sciences & Biomedicine, Biology

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
21
Top 10%
Average
Top 10%
Green
hybrid