The active involvement of teenagers in the design of interactive technologies for museums is lacking further development. Adopting a user-driven innovation framework along with cooperative inquiry, we report and discuss a case study that has been designed to involve users in the ideation of interpretive experiences for a local museum. Working in collaboration with the Natural History Museum of Funchal, this contribution will present and discuss co-design sessions that were aimed at participants with ages 15 to 17 and where they were asked to ideate an interactive museum experience. As a result of the co-design sessions, we have found several design patterns. We have grouped these patterns into four categories that express the interests of a teenage audience; these categories are: “interactions”, “gaming”, “localization” and “social media”. Our findings suggest that teenagers value interactive technologies when visiting museums and that user-driven innovation plays an important role when involving this specific audience in the design of user experiences for museums.

Monitoring marine contamination by floating litter can be particularly challenging since debris are continuously moving over a large spatial extent pushed by currents, waves, and winds. Floating litter contamination have mostly relied on opportunistic surveys from vessels, modeling and, more recently, remote sensing with spectral analysis. This study explores how a low-cost commercial unmanned aircraft system equipped with a high-resolution RGB camera can be used as an alternative to conduct floating litter surveys in coastal waters or from vessels. The study compares different processing and analytical strategies and discusses operational constraints. Collected UAS images were analyzed using three different approaches: (i) manual counting (MC), using visual inspection and image annotation with object counts as a baseline; (ii) pixel-based detection, an automated color analysis process to assess overall contamination; and (iii) machine learning (ML), automated object detection and identification using state-of-the-art convolutional neural network (CNNs). Our findings illustrate that MC still remains the most precise method for classifying different floating objects. ML still has a heterogeneous performance in correctly identifying different classes of floating litter; however, it demonstrates promising results in detecting floating items, which can be leveraged to scale up monitoring efforts and be used in automated analysis of large sets of imagery to assess relative floating litter contamination.

Current trends in the global climate facilitate the displacement of numerous marine species from their native distribution ranges to higher latitudes when facing warming conditions. In this work, we analyzed occurrences of a circumtropical reef fish, the spotfin burrfish, Chilomycterus reticulatus (Linnaeus, 1958), in the Madeira Archipelago (NE Atlantic) between 1898 and 2021. In addition to available data sources, we performed an online survey to assess the distribution and presence of this species in the Madeira Archipelago, along with other relevant information, such as size class and year of the first sighting. In total, 28 valid participants responded to the online survey, georeferencing 119 C. reticulatus sightings and confirming its presence in all archipelago islands. The invasiveness of the species was screened using the Aquatic Species Invasiveness Screening Kit. Five assessments rated the fish as being of medium risk of establishing a local population and becoming invasive. Current temperature trends might have facilitated multiple sightings of this thermophilic species in the Madeira Archipelago. The present study indicates an increase in C. reticulatus sightings in the region. This underlines the need for updated comprehensive information on species diversity and distribution to support informed management and decisions. The spread of yet another thermophilic species in Madeiran waters provides further evidence of an ongoing tropicalization, emphasizing the need for monitoring programs and the potential of citizen science in complementing such programs.