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Revolutionary quantitative photography unveiled for measuring marine plastic pollution
Machine learning can quickly and efficiently identify the colour and shape of plastic debris.
- New technology aims to identify marine plastic pollution
- Machine learning can quickly and efficiently identify the colour and shape of plastic debris
- Birds continue to suffer from plastic ingestion
A new study by Dr Joseph (Joby) Razzell Hollis, Marie Curie Fellow on the PLASTISCAN project at the Natural History Museum, London has unveiled a new and innovative method that promises a game-changing approach to measuring and understanding marine plastic pollution.
Plastics have inundated our environment for decades and pose a critical challenge for researchers due to the arduous and unreliable nature of assessing their impact. This novel method, described in the paper, provides a cutting-edge solution to these hurdles by introducing a systematic approach to capturing detailed data on plastic pollution.
To create a standardised and automated process for assessing the size, shape, and color of individual plastic fragments, the research team developed an automated image analysis system with a remarkable 98% success rate in detecting individual plastic fragments across multiple samples. By employing this new method, researchers were able to collect substantially higher quality data in a more efficient manner which they hope will provide greater insights into plastic pollution's impact on ecosystems and wildlife.
To test the system, the team utilised the analysis on plastic fragments collected from Flesh-footed Shearwater fledglings in 2021 and 2022 on Lord Howe Island, New South Wales, Australia. The collection process involved the removal of material from the birds' stomachs through flushing living birds’ stomachs with seawater as well as removal of fragments from collected deceased birds. In 2023 this species was the first reported to suffer from ‘plasticosis’, a new disease caused by ingesting plastic.
Using the new photographic system the team were able to categorize 3,793 fragments of plastic from the stomachs of 129 individual birds. For validation, fragment counts were compared to the original counts taken in the field and were largely comparable proving the image analysis an accurate and efficient way to analyse this material in the future.
Dr. Joseph Razzell Hollis, the lead scientist on the project, said, ‘Our new image analysis system allows us to accurately and efficiently count and categorize fragments of plastic pollution, like those collected from the shearwater birds on Lord Howe Island, measuring the size, shape, and colour of hundreds of pieces of plastic at once..
‘We hope in time this analysis, which can pick up more subtle colour and size differences than the human eye, will allow us to work out how long some plastics have been in the ocean as well as if certain colours or shapes are favoured for ingestion by marine life.’
Through standardising the methods used to study plastic fragments, the team hopes to inform interventions for the conservation of marine ecosystems and vulnerable species affected by plastic pollution.
Dr Razzell Hollis adds, ‘Though this method we may eventually discover that certain coloured plastics are more attractive to certain species. Such findings could inform on the type of plastics we use or how we dispose of them in the future to minimise their impact on the environment.’
These insights serve as critical evidence of the extent and nature of marine plastic pollution affecting these seabirds. It is clear that as plastic pollution continues to affect both wildlife and human health, we must strive to reduce and remove it from the environment to create a future where both people and planet thrive.
The Paper Quantitative Photography for Rapid, Reliable Measurement of Marine Macro-Plastic Pollution is published in Methods in Ecology & Evolution.
Notes to editors
Natural History Media contact: Tel: +44 (0)20 7942 5654 / 07799690151 Email: press@nhm.ac.uk
Images are available on the NHM Data Portal here.
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