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Depth learning - Using machine learning to estimate vertical zonation in a submarine canyon in Northern Skagerrak

by Christian Nilsson, University of Gothenburg

Vertical zonation in marine environments occurs when sessile species are primarily found at specific depth intervals, dividing the habitat into distinct horizontal layers. The community assemblage and size of these different zones is determined by environmental conditions as well as interactions between organisms. This phenomenon has primarily been studied in intertidal waters, but also occurs at greater depths, beneath the halocline. Here, low spatiotemporal variation in environmental conditions suggest increased ecosystem sensitivity to recent climate change. However, subtidal environments and their zonation patterns have been understudied historically due to technical limitations. Therefore, in this study we apply machine learning based object detection software to ROV footage to estimate and quantify vertical zonation and community structure along the sides of the Koster submarine canyon. We also plan to investigate possible changes in zonation structure as well as any possible correlations to changing environmental conditions over the past 30 years. For more information - have a look at this conference poster.

Studying the impact from of small-scale aquacultures on local biodiversity using video technology

by Xhoni Dalipi, University of Gothenburg

The recent emergence of aquacultures has gained significant attention in recent years due to its potential to address food security and environmental concerns. Seaweed and shellfish cultivation offer advantages such as providing a sustainable source of protein, reducing pressure on wild fisheries, and contributing to nutrient uptake in marine environments. However, these practices also raise concerns about their impact on marine biodiversity. Alterations to local ecosystems and potential habitat modification are some of the challenges that need to be addressed. This study will provide a comprehensive understanding of the relationship between small-scale aquaculture and benthic biodiversity, by recording biological communities across the farming season in small aquacultures on the Swedish West coast. The findings of this research can potentially contribute to the design of sustainable and nature-positive aquacultures in the future.

Monitoring sharks in marine protected areas

by Frida Persson, University of Gothenburg

In this project our student went to South Africa to sample shark observations and population density data, together with the Sharklife Conservation Group. We now have the first models trained to detect up to six shark species in the marine footage recorded with baited remote underwater video systems (BRUVS). The models may be used in the future to discover new and continuously monitor existing elasmobranch hotspots that need special protection from fisheries. The full report is available under Publications

Ecological relations between invasive and native fish

by Leon Green, University of Gothenburg

Scientists at the University of Gothenburg are investigating the interaction between invasive and native fish on the Swedish west coast. A large part of the data collection takes place through underwater video recording and will be used to streamline the analysis of the many hours of video recordings. "Invasions from alien species are expected to increase in the future, so it is absolutely critical that we learn how to use such new image analysis services" says Leon Green who studies how biodiversity can limit the spread of alien species. He continues: "...especially the combination big data methods and citizen science can become an important toolkit for mapping the distribution and population growth of invasive fish.”

Reef effects on marine biodiversity in offshore wind parks

by Saga Alsterlind, University of Gothenburg

As the global demand for green energy continues to rise, so does the market for offshore wind farms (OWF). The implementation of the submerged OWF foundations introduces new hard substrates on which marine organisms begin to colonize, also known as the “reef effect”. OWF's therefore have great potential to increase marine biodiversity by elevating habitat value. This project aims to develop a method for quantifying and monitoring changes of sessile biodiversity in relation to OWF's, utilizing machine-learning to perform segmentation detection on still imagery. This project is a collaboration between University of Gothenburg and the renewable energy company OX2.

Trawling impact on soft bottom fauna

by Rasmus Torslund, University of Gothenburg

Sea pens are coral animals that live on soft bottoms and act as important habitat builders when they grow dense. Such sea pen aggregations create shelter for fish and shellfish. Previous studies have shown that sea pen habitats are in decline due to harmful fishing methods such as bottom trawling but also from other threats. By gaining an understanding of the distribution and abundance of sea pens and how this abundance relates to trawling activities we hope to provide insight into the status and changes of soft bottom ecosystems in the Kattegat region. For more information - have a look at the report under Publications.

Applications of machine learning models for studying long term changes of benthic fauna in the Kosterhavets National Park

by Joel Hjärne Kokk, University of Gothenburg

In this project we investigated the efficiency and reliability of the machine learning (ML) approach compared to manual counting of habitat building species. We trained and tested the performance of a object detection model including three species: Desmophyllum pertusum (cold water coral), Bolocera tuediae (deplete sea anemone) and Geodia barretti (football sponge). We then used the model to see whether the distribution of these three species had changed over the last twenty years in one of the reef areas of Kosterhavet National Park. The results highlight the potential of ML models as an analytical tool, but also identify issues that needs to be addressed to make the system applicable for large-scale studies on deep water fauna such as better standardization of subsea imagery. The mapping tool developed during the project is available here.

Remotely Operated Vehicles and Citizen Scientists to monitor California Marine Protected Areas

by Victor Anton,

California’s marine protected areas (MPAs) are ocean and coastal areas with special protections to help conserve and protect marine ecosystems and wildlife. As MPAs are predominantly underwater, monitoring them and their effects can be challenging. By leveraging the power of community scientists and machine learning technology this project aims to identify and extract classified images of organisms from underwater videos for contribution to biodiversity databases. Ultimately, these observations will integrate with ongoing efforts by the California Academy of Sciences and MPA managing agencies to use community science data to better understand and monitor biodiversity across California’s coast and MPAs. You can engage with the project here.

Exploring the potential of synthetic data for detection of rare species in subsea imagery

by Sarah Al-Khateeb and Lisa Bodlak

Large and diverse data is crucial to train object detection models properly and achieve satisfactory prediction performance. However, in some cases, for example when developing models for detecting rare species data will always be limited resulting in overfitting and poor model performance. Furthermore, underwater images can often be of poor quality, with colour distortion and blurriness. In this study we explored methods to both increase and enhance training data for object classes with little training data and thereby improve detection accuracy. We experimented with several Generative Adversarial Networks (GANs) to enhance and increase the training data. The results prepared for publication and the synthetic images are published here.

Monitoring fish abundance and diversity in New Zealand marine reserves

by Victor Anton,

Marine reserves are the highest form of protection for Aotearoa New Zealand’s marine environment, facilitating the recovery of exploited species. To ensure their effectiveness, the New Zealand Department of Conservation monitors the state and trend of exploited species using baited underwater videos. Baited underwater videos are a versatile underwater survey method to compare the abundance of carnivorous and scavenger fishes inside and outside marine reserves. The team is using SUBSIM tools to process the videos from the 44 marine reserves. Read the latest news here.