Abstract

Globally, fishing has undergone significant transformations in recent decades, with further changes projected in response to social and environmental challenges. This study uses Q method analysis to explore the prioritization of various local and global management measures aimed at ensuring the future sustainability of fisheries within the Llevant de Mallorca – Cala Ratjada Marine Protected Area (MPA), a marine reserve located in the northeastern part of Mallorca Island. We identify and evaluate the primary discourses among key stakeholders, revealing three distinct perspectives encompassing different views on issues such as eliminating illegal practices, adapting European Union fisheries policies to local realities, increasing restrictions on trawling, promoting local consumption, and the significance of co-management. Furthermore, two points of consensus emerge across the discourses: (i) the necessity of decarbonizing the sector, and (ii) the importance of increasing public funding to support the employment of young fishers. However, both measures are perceived as low priorities. This study contributes to the literature by demonstrating how Q method can be applied to assess local and global priorities in the context of potential MPA evolution, offering valuable insights for the development of integrative priority assessments. It underscores the diversity of perspectives within small fishing communities and highlights the critical need for democratic governance structures to ensure this diversity is represented and accounted for in public policy development.

Abstract

From simple rule-based systems to cutting-edge large language models (LLM) like ChatGPT, Artificial Intelligence (AI) has made remarkable steps. This seminar will introduce the basic concepts of AI highlighting how machines learn to recognize patterns, make decisions, and generate text before exploring the quest for truly general intelligence. By looking to nature, where ecosystems balance cooperation, adaptation, and resilience, we gain fresh ideas for designing AI systems that are more efficient and flexible.

In parallel, we will see how AI can illuminate our understanding of the physics and biology of our planet. Through data analysis and predictive modeling, AI offers powerful tools for tracking species movement, identifying and predicting environmental changes, and guiding conservation efforts. By merging lessons from nature with the latest AI techniques, we can advance both technological innovation and marine research, ultimately leading the way toward a deeper understanding of intelligence both artificial and natural.

Abstract

Pollination is an essential process for maintaining biodiversity and ecosystem functioning, as 87.5% of the flowering plants and one third of the human diet depend on it. However, this essential ecosystem service is severely threatened by pollinator losses, raising important challenges for biodiversity conservation and crop production. Among the many threats to wild pollinators today, land-use changes have been identified as one of the main causes of pollinator declines, and this effect is expected to be accentuated in the following decades as human population increases. I will present the studies conducted in my group to understand how landscape modifications related to land-use changes affect plant and pollinator communities, the structure of plant-pollinator interactions and the provision of pollination services to crops and wild plants. The results of these studies have important implications for the sustainability of anthropized landscapes and for the conservation of pollinators as a key ecosystem service.