Population Genomics for Insect Conservation

Annu Rev Anim Biosci. 2023 Feb 15:11:115-140. doi: 10.1146/annurev-animal-122221-075025. Epub 2022 Nov 14.

Abstract

Insects constitute vital components of ecosystems. There is alarming evidence for global declines in insect species diversity, abundance, and biomass caused by anthropogenic drivers such as habitat degradation or loss, agricultural practices, climate change, and environmental pollution. This raises important concerns about human food security and ecosystem functionality and calls for more research to assess insect population trends and identify threatened species and the causes of declines to inform conservation strategies. Analysis of genetic diversity is a powerful tool to address these goals, but so far animal conservation genetics research has focused strongly on endangered vertebrates, devoting less attention to invertebrates, such as insects, that constitute most biodiversity. Insects' shorter generation times and larger population sizes likely necessitate different analytical methods and management strategies. The availability of high-quality reference genome assemblies enables population genomics to address several key issues. These include precise inference of past demographic fluctuations and recent declines, measurement of genetic load levels, delineation of evolutionarily significant units and cryptic species, and analysis of genetic adaptation to stressors. This enables identification of populations that are particularly vulnerable to future threats, considering their potential to adapt and evolve. We review the application of population genomics to insect conservation and the outlook for averting insect declines.

Keywords: conservation genomics; deleterious mutations; genetic adaptation; genome assembly; insect declines.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biodiversity
  • Conservation of Natural Resources* / methods
  • Ecosystem*
  • Endangered Species
  • Humans
  • Insecta / genetics
  • Metagenomics