Internal Cycle of Seminars at IMEDEA (CISI) consist on a cycle of seminar presentations given mainly by doctoral students, masters and junior postdocs, although it is not closed to other staff, such as visitors and staff, that take place every Friday from 4:00 p.m. to 4:30 p.m in the seminar room os IMEDEA.

This represents a great opportunity to learn more about the research carried out at the Institute and to bring those with less experience , the chance of increasing their presentation and public speaking skills. Afterwards, there will be soft drinks and beers for all attendees 😉 We strongly encourage you to participate. Join us!

Do you want to participate with a presentation? Please contact the organising team:

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Featured Seminars
Internal Cycle of Seminars IMEDEA - Amaya Álvarez- «Deep Learning inside the fish market»
  Abstract In this presentation, we will explore the various tasks undertaken by the Fish Ecology Lab at the Palma Fish Market since 2018. Our focus lies in automating the processes employed for extracting fish length measurements. The dynamic distribution of fish lengths plays a crucial role, not only in making informed short-term operational decisions within a fishery co-management framework but also in providing input for traditional fishery models that illuminate mid- and long-term trends in exploited stocks. Traditionally, the estimation of fish length in most fisheries has been a manual endeavor, resulting in precise measurements at the individual fish level. However, due to the high cost and inefficiency associated with supervised sampling, the sample size tends to be limited. Consequently, the precision of population-level estimates often falls short, and biases may arise, especially when adequately stratified sampling programs are economically unfeasible. Conversely, the application of machine learning and artificial intelligence in fisheries science presents a promising avenue for large-scale, unbiased sampling of fish catches. The Fish Ecology Lab has been working with the daily images recived from the auction of the fish market to extract information on various commercial species such as hake, dolphinfish, and red shrimp. This presentation will specifically focus into the deep learning techniques employed for each of these cases.  

Previous Seminars

Internal Cycle of Seminars IMEDEA - Elena Allegri - «Embracing Nature-based Solutions to face climate-induced water quality alteration in marine coastal environments»



Climate change (CC) and environmental degradation are severely affecting marine and coastal systems and the ecosystem goods and services on which people rely. As a result, biodiversity loss and reductions in ecosystem functioning have been recorded across marine and terrestrial systems. A transformative change in the way we adapt to CC is needed, centered around preserving and restoring nature.

Nature-based Solutions (NbS) offer the opportunity to improve ecosystem resilience and biodiversity, transforming the management of nature while providing environmental and societal benefits, from individual to collective level. NbS, and their benefits, are well-known and largely implemented in terrestrial and urban environments, while less is known on the potential of NbS capacity in reducing water quality (WQ) deterioration due to climate and human-induced pressures in marine-coastal areas. The H2020 MaCoBioS project aims to respond to these needs, developing modelling approaches and analytical frameworks to facilitate the adoption of evidence informed NbS responding to environmental and restoration targets as posed by relevant EU acquis (e.g., EU Restoration law, MSFD) and specific marine and coastal archetypes. Within MaCoBioS project, a harmonized modelling framework has been created, which brings together risk assessment approaches, NbS suitability mapping and a decision-support system guiding the selection of the most appropriate NBS in marine-coastal ecosystems.

To explore the dynamic processes and interactions among climate-induced and human-made pressures driving marine WQ alteration, and to identify suitable NbS able to reduce environmental impacts on marine coastal environments, a Bayesian Network (BN) model integrated with GIS-based techniques supporting the spatial modelling and appraisal of multi-risks scenarios is developed. The designed BN spatio-temporal multi-risk model will be able to detect and unravel impacts induced by this complex interplay on ecosystem services capacity and flow and to test the effectiveness of different Nature-based management solutions to face up with the identified impacts.

The model will focus on the land-sea interface of the Apulia region (Southern Italy). Finally, the designed multi-risk model will be used for the scenario analysis, simulating multiple “what-if” scenarios, representing different climate conditions (e.g., by simulating changes on sea surface temperature, building on climate models’ input) and adaptation measures.


Link to the video here