Periodic Reporting for period 1 - MuFFIN (MuFFIN - Modelling Foraging Fitness in Marine predators)
Reporting period: 2021-01-01 to 2022-12-31
Climate change poses a serious threat to the Earth's ecosystems, both on land and at sea. In particular, the impact of climate change on sensitive systems or those in extreme climatic conditions (e.g. polar and high mountain regions) is occurring earlier and with greater intensity. In recent years, rapid advances in automatic sensing technologies have revolutionised the way ecological information is collected. Examples of these innovations are the use of devices attached to animals (bio-logging) and remote sensing systems, used to monitor animal movements and environmental features. However, to date, it is not yet known how species interact with their environment and respond to environmental changes. This information is crucial when assessing the status of populations and providing guidelines for monitoring and conservation. The species studied in this project are considered 'sentinels of ecosystem changes'. As marine predators at the top of the food chain, their ecology, behaviour and population trends tell us about the health of marine ecosystems. Successful monitoring and conservation projects rely on long-term data sets and robust analytical tools to provide insights into the state of ecosystems, contributing to the goals of (i) understanding and mitigating the impact of human activities on ecosystems, (ii) maintain species diversity, (iii) providing societal benefits and opportunities for education, and (iv) meeting European and global directives on good environmental status.
Using long term bio-logging and remote sensing datasets we can now answer questions related to how individual animals move in space and time, how they interact with their immediate surroundings and how wild populations respond to changes in environmental variability. This research project aimed at bridging the gap between individual movements and population dynamics and hence, inform conservation efforts. In MuFFIN (Modelling Foraging Fitness in Marine Predators) I made use of, and contributed to, data collected via long term species monitoring programs hosted by the Centre d’Etudes Biologiques de Chizé (CEBC), France. I focused my research on three species of marine top predators: Little penguins (Eudyptula minor), southern elephant seals (Mirounga leonina) and Adélie penguins (Pygoscelis adeliae) for which the longest high resolution bio-logging datasets exist. I aimed at quantifying the variation of foraging behaviour across spatio-temporal scales, highlighting long-term consequences on habitat use, foraging plasticity and fitness, linking the movement of individuals to population processes.
Using long term bio-logging and remote sensing datasets we can now answer questions related to how individual animals move in space and time, how they interact with their immediate surroundings and how wild populations respond to changes in environmental variability. This research project aimed at bridging the gap between individual movements and population dynamics and hence, inform conservation efforts. In MuFFIN (Modelling Foraging Fitness in Marine Predators) I made use of, and contributed to, data collected via long term species monitoring programs hosted by the Centre d’Etudes Biologiques de Chizé (CEBC), France. I focused my research on three species of marine top predators: Little penguins (Eudyptula minor), southern elephant seals (Mirounga leonina) and Adélie penguins (Pygoscelis adeliae) for which the longest high resolution bio-logging datasets exist. I aimed at quantifying the variation of foraging behaviour across spatio-temporal scales, highlighting long-term consequences on habitat use, foraging plasticity and fitness, linking the movement of individuals to population processes.
Bio-logging devices can record spatio-temporal information on animal movements and activities at different resolutions, from twice a day to over 10,000 times in a few seconds. Also, environmental data generated with remote sensing techniques are becoming increasingly accurate in capturing the complex dynamic of the heterogeneous environments in which animals live. Researchers in this field are in a position where the automatic collection of detailed datasets is becoming commonplace, but extracting knowledge from them is a daunting task, mainly due to the lack of accessible analytical tools. Novel methodological frameworks for the analysis of large, high-resolution bio-logging data, collected by researchers working at the host institute, were developed and implemented during this project. The work undertaken for the first working package led to the development of interdisciplinary collaborations and knowledge exchange with CEBC, L3i (Laboratoire Informatique, Image and Interaction) of La Rochelle University, Phillip Island Nature Parks, Australia. The work also involved the supervision of master students as well as PhD students and led to work published in a peer-reviewed international journal as well as two additional publications in preparation. Specifically, flexible methodologies using AI approaches were developed to detect types of activities and movements performed by marine predators while foraging, infer behaviours on long term bio-logging data and produce hotspot foraging maps. The work undertaken at this stage involved also filtering, cleaning, and summarizing the information obtained from the different bio-logging devices (animal geographical location and activity). The relevant environmental variables allowing to understand how marine species select environmental features when foraging, were obtained by sourcing from open-source datasets available from the Copernicus Marine Environment Monitoring Service (https://www.copernicus.eu/en/copernicus-services/marine). This also led to a new collaboration with the Institut Pluridisciplinaire Hubert Curien – IPHC at CNRS, Strasbourg. Results on the population of Little penguins’ population, for example, show why and where these animals forage the most, taking advantage of highly productive, shallow areas nearby their breeding colony. Bio-logging data were merged with the long-term population monitoring data to link foraging information with population dynamics. Results show how the variation in foraging behaviours is linked to variations in individual body weights and on how well an individual reproduces during the breeding season.
Working with national and international teams, I received training in the biology of top marine predators, data collection, bio-logging techniques, statistical analysis and how to disseminate and communicate results to a non-scientific audience. Working in collaboration with scientists from CEBC and the Philip Island Nature Parks, I discussed how the datasets used in this project could be used for marine spatial planning. Despite the pandemic of COVID-19, I received regular online training from international collaborators. Furthermore, during the last 3 months of the fellowship (September - November 2022), I was able to participate in the fieldwork and public engagement activities planned in Australia for WP1. By participating in fieldwork activities at the Philip Island Nature Parks Penguin Parade (https://penguins.org.au/attractions/penguin-parade/) I had the daily opportunity to talk to the public who come to visit the site. Through the collaborations and research exchanges established and the opportunity for supervision, this project provided the means to strengthen my position of professional maturity and independence.
Workshops on bio-logging, the use of artificial intelligence techniques and broader collaborations with CNRS Strasbourg and Philip Island Nature Parks were organised during this project. I was also the organiser of the workshop "Global patterns of energetic expenditure: how do behavioural-bioenergetics relationships link to life-history strategies across taxa?" at the Global Collaboration Week - 7th Bio-Logging Symposium 18-22 October 2021, which was held online due to Covid-19 travel restrictions.
Working with national and international teams, I received training in the biology of top marine predators, data collection, bio-logging techniques, statistical analysis and how to disseminate and communicate results to a non-scientific audience. Working in collaboration with scientists from CEBC and the Philip Island Nature Parks, I discussed how the datasets used in this project could be used for marine spatial planning. Despite the pandemic of COVID-19, I received regular online training from international collaborators. Furthermore, during the last 3 months of the fellowship (September - November 2022), I was able to participate in the fieldwork and public engagement activities planned in Australia for WP1. By participating in fieldwork activities at the Philip Island Nature Parks Penguin Parade (https://penguins.org.au/attractions/penguin-parade/) I had the daily opportunity to talk to the public who come to visit the site. Through the collaborations and research exchanges established and the opportunity for supervision, this project provided the means to strengthen my position of professional maturity and independence.
Workshops on bio-logging, the use of artificial intelligence techniques and broader collaborations with CNRS Strasbourg and Philip Island Nature Parks were organised during this project. I was also the organiser of the workshop "Global patterns of energetic expenditure: how do behavioural-bioenergetics relationships link to life-history strategies across taxa?" at the Global Collaboration Week - 7th Bio-Logging Symposium 18-22 October 2021, which was held online due to Covid-19 travel restrictions.
This project generated source codes to be used for species with bio-logging devices within the wider ecological community. It has devoted time to training the younger generation of scientists and educational activities with the general public, resulting in a return to society. Finally, current and future research based on scientific advances produced during this project will be used for the development of marine spatial planning.