Image background assessment as a novel technique for insect microhabitat identification
Sesa Singha Roy, Reid Tingley, Alan Dorin

TL;DR
This study introduces a novel computer vision approach to classify insect image backgrounds as natural or anthropogenic microhabitats, providing insights into insect habitat use amid urbanization and climate change.
Contribution
It presents a new method for analyzing insect microhabitats using image background classification, supplementing traditional insect classification techniques.
Findings
Flies and honeybees are found mainly in natural microhabitats.
Wasps are predominantly seen in anthropogenic microhabitats.
Insects adapt well to urban environments, influencing management strategies.
Abstract
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…
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Taxonomy
TopicsPlant and animal studies · Insect and Arachnid Ecology and Behavior · Insect behavior and control techniques
