  The effects of climate change, urbanisation and agriculture are changing the
way insects occupy habitats. Some species may utilise anthropogenic
microhabitat features for their existence, either because they prefer them to
natural features, or because of no choice. Other species are dependent on
natural microhabitats. Identifying and analysing these insects' use of natural
and anthropogenic microhabitats is important to assess their responses to a
changing environment, for improving pollination and managing invasive pests.
Traditional studies of insect microhabitat use can now be supplemented by
machine learning-based insect image analysis. Typically, research has focused
on automatic insect classification, but valuable data in image backgrounds has
been ignored. In this research, we analysed the image backgrounds available on
the ALA database to determine their microhabitats. We analysed the
microhabitats of three insect species common across Australia: Drone flies,
European honeybees and European wasps. Image backgrounds were classified as
natural or anthropogenic microhabitats using computer vision and machine
learning tools benchmarked against a manual classification algorithm. We found
flies and honeybees in natural microhabitats, confirming their need for natural
havens within cities. Wasps were commonly seen in anthropogenic microhabitats.
Results show these insects are well adapted to survive in cities. Management of
this invasive pest requires a thoughtful reduction of their access to
human-provided resources. The assessment of insect image backgrounds is
instructive to document the use of microhabitats by insects. The method offers
insight that is increasingly vital for biodiversity management as urbanisation
continues to encroach on natural ecosystems and we must consciously provide
resources within built environments to maintain insect biodiversity and manage
invasive pests.
