Abstract
Biological control—the use of organisms (e.g., nematodes, arthropods, bacteria, fungi, viruses) for the suppression of insect pest species—is a well-established, ecologically sound and economically profitable tactic for crop protection. This approach has served as a sustainable solution for many insect pest problems for over a century in North America. However, all pest management tactics have associated risks. Specifically, the ecological non-target effects of biological control have been examined in numerous systems. In contrast, the need to understand the short-and long-term evolutionary consequences of human-mediated manipulation of biological control organisms for importation, augmentation and conservation biological control has only recently been acknowledged. Particularly, population genomics presents exceptional opportunities to study adaptive evolution and invasiveness of pests and biological control organisms. Population genomics also provides insights into (1) long-term biological consequences of releases, (2) the ecological success and sustainability of this pest management tactic and (3) non-target effects on native species, populations and ecosystems. Recent advances in genomic sequencing technology and model-based statistical methods to analyze population-scale genomic data provide a much needed impetus for biological control programs to benefit by incorporating a consideration of evolutionary consequences. Here, we review current technology and methods in population genomics and their applications to biological control and include basic guidelines for biological control researchers for implementing genomic technology and statistical modeling.
Original language | English |
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Article number | 462 |
Pages (from-to) | 1-21 |
Number of pages | 21 |
Journal | Insects |
Volume | 11 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2020 |
Bibliographical note
Publisher Copyright:© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Funding
Funding: This work was funded by USDA grant #2017-06423 to Drs. George Vourlitis and Arun Sethuraman. AS was also supported by NSF ABI Development grant #1564659.
Funders | Funder number |
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NSF ABI Development | 1564659 |
U.S. Department of Agriculture | 2017-06423 |
Keywords
- Biological control
- Demographic models
- Pest management
- Population genomics
ASJC Scopus subject areas
- Insect Science