Research horizons for invasive marine species detection with eDNA/eRNA
The global marine ecosystem is changing rapidly as the result of biogeochemical cycles and ecosystem structure being altered by industrial civilization. Invasive marine species (IMS) are one of the most damaging regional consequences of human activity, and one of the most easily attributable to spec...
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Veröffentlicht in: | Biological invasions 2024-11, Vol.26 (11), p.3715-3731 |
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Sprache: | eng |
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Zusammenfassung: | The global marine ecosystem is changing rapidly as the result of biogeochemical cycles and ecosystem structure being altered by industrial civilization. Invasive marine species (IMS) are one of the most damaging regional consequences of human activity, and one of the most easily attributable to specific processes. This makes IMS introduction one of most tractable threats for management by appropriate policies. Once established, a different set of policies are required either to restrict IMS spread, or to attempt local eradication. The key ecosystem management tool for IMS damage mitigation is rapid, widely deployable IMS detection. Environmental Nucleic Acids (eNA), combining environmental DNA (eDNA) and environmental RNA (eRNA) analyses, have emerged as valuable tools for sensitive, cost-effective and readily deployable detection of IMS. Methods for IMS detection by eNA are still being developed through a widespread and active research community, so identifying the limitations of current processes will help prioritise eNA-based IMS detection research. We analysed and synthesised the opinions of expert marine ecosystem managers and researchers in Australia and New Zealand about the knowledge gaps and research needs for eNA-based IMS detection. This synthesis was placed in context with current research literature on what eNA technologies are currently providing as an IMS management tool; what problems exist with the current technology; and what could be done to improve this general approach. Our analyses produced a list of priorities that chart a path towards the best possible systems for IMS detection by eNA. |
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ISSN: | 1387-3547 1573-1464 |
DOI: | 10.1007/s10530-024-03406-2 |