Autonomous temporal pseudo-labeling for fish detection

The first major step in training an object detection model to different classes from the available datasets is the gathering of meaningful and properly annotated data. This recurring task will determine the length of any project, and, more importantly, the quality of the resulting models. This obstacle is amplified when the data available for the new classes are scarce or incompatible, as in the case of fish detection in the open sea. This issue was tackled using a mixed and reversed approach: a network is initiated with a noisy dataset of the same species as our classes (fish), although in different scenarios and conditions (fish from Australian marine fauna), and we gathered the target footage (fish from Portuguese marine fauna; Atlantic Ocean) for the application without annotations. Using the temporal information of the detected objects and augmented techniques during later training, it was possible to generate highly accurate labels from our targeted footage. Furthermore, the data selection method retained the samples of each unique situation, filtering repetitive data, which would bias the training process. The obtained results validate the proposed method of automating the labeling processing, resorting directly to the final application as the source of training data. The presented method achieved a mean average precision of 93.11% on our own data, and 73.61% on unseen data, an increase of 24.65% and 25.53% over the baseline of the noisy dataset, respectively.info:eu-repo/semantics/publishedVersio

Co-design of a marine protected area zoning and the lessons learned from it

Marine Protected Areas (MPAs) are a tool to safeguard marine natural systems, yet their effectiveness depends on how well they are integrated into the existing socioeconomic context. Stakeholder engagement in MPA design can contribute to increasing integration. This study focuses on the co-design of an MPA between researchers, public administration, the private sector, and non-governmental organizations. The proposed MPA is in Portugal and includes an area that is a hotspot for biodiversity and economic activities. This is the first MPA proposal in mainland Portugal co-designed using a participatory approach. This study highlights the steps of the zoning process and synthesizes the eight main lessons learned, useful for other cases, particularly for relatively small coastal MPAs with multiple socioeconomic activities. Three zoning proposals were developed and discussed within the participatory process. The proposals considered the best scientific and local knowledge available and were defined using ecological, socioeconomic, and shape-area guiding principles. In an iterative manner and following a participatory approach, compromises with stakeholders were achieved, and a final proposal, scientifically sound and socially accepted by most stakeholders, was delivered to the government. The final zoning plan will achieve ambitious conservation goals, including the largest fully protected area to be declared in mainland Portugal, while minimizing the impacts on the existing economic activities and promoting its sustainability. This process resulted in valuable lessons that may be applied elsewhere and guide future MPA implementation or rezoning of existing ones. These transdisciplinary and participatory processes can be time and resource-consuming but are vital for ensuring MPA effectiveness.Fundação para a Ciência e Tecnologia - FCTinfo:eu-repo/semantics/publishedVersio

Setting performance indicators for coastal marine protected areas: An expert-based methodology

Marine Protected Areas (MPAs) require effective indicators to assess their performance, in compliance with the goals of relevant national and international commitments. Achieving and prioritizing shortlists of multidisciplinary indicators demands a significant effort from specialists to depict the multiple conservation and socioeconomic interests, and the large complexity of natural systems. The present paper describes a structured expert-based methodology (process and outputs) to co-define a list of multidisciplinary MPA performance indicators. This work was promoted by the management authority of coastal MPAs in mainland Portugal to gather a consensual and feasible list of indicators that would guide the design of a future national monitoring program. Hence, Portuguese coastal MPAs served as a case study to develop such a process between 2019 and 2020. In the end, participants (1) agreed on a shortlist of prioritized indicators (i.e., environmental, governance, and socioeconomic indicators) and (2) defined minimum monitoring frequencies for the indicators in this list, compatible with the potential replicability of the associated survey methods. The present approach recommends that management plans incorporate monitoring procedures and survey methods, with a validated list of indicators and associated monitoring periodicity, agreed among researchers, MPA managers and governance experts. The proposed methodology, and the lessons learned from it, can support future processes aiming to define and prioritize MPA performance indicatorsFundação para a Ciência e Tecnologia - FCT, European Maritime and Fisheries Fund (EMFF)info:eu-repo/semantics/publishedVersio