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- Dalby, Oliver, et al.
(author)
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Citizen Science Driven Big Data Collection Requires Improved and Inclusive Societal Engagement
- 2021
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In: Frontiers in Marine Science. - : Frontiers Media SA. - 2296-7745. ; 8
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Journal article (peer-reviewed)abstract
- Marine ecosystems are in a state of crisis worldwide due to anthropogenic stressors, exacerbated by generally diminished ocean literacy. In other sectors, big data and technological advances are opening our horizons towards improved knowledge and understanding. In the marine environment the opportunities afforded by big data and new technologies are limited by a lack of available empirical data on habitats, species, and their ecology. This limits our ability to manage these systems due to poor understanding of the processes driving loss and recovery. For improved chances of achieving sustainable marine systems, detailed local data is required that can be connected regionally and globally. Citizen Science (CS) is a potential tool for monitoring and conserving marine ecosystems, particularly in the case of shallow nearshore habitats, however, limited understanding exists as to the effectiveness of CS programmes in engaging the general public or their capacity to collect marine big data. This study aims to understand and identify pathways for improved engagement of citizen scientists. We investigated the motivations and barriers to engagement of participants in CS using two major global seagrass CS programmes. Programme participants were primarily researchers in seagrass science or similar fields which speak to a more general problem of exclusivity across CS. Altruistic motivations were demonstrated, whilst deterrence was associated with poor project organisation and a lack of awareness of specified systems and associated CS projects. Knowledge of seagrass ecosystems from existing participants was high and gains because of participation consequently minimal. For marine CS projects to support big data, we need to expand and diversify their current user base. We suggest enhanced outreach to stakeholders using cooperatively identified ecological questions, for example situated within the context of maintaining local ecosystem services. Dissemination of information should be completed with a variety of media types and should stress the potential for knowledge transfer, novel social interactions, and stewardship of local environments. Although our research confirms the potential for CS to foster enhanced collection of big data for improved marine conservation and management, we illustrate the need to improve and expand approaches to user engagement to reach required data targets.
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| 2. |
- Jones, Benjamin L., et al.
(author)
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Seagrass Structural Traits Drive Fish Assemblages in Small-Scale Fisheries
- 2021
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In: Frontiers in Marine Science. - : Frontiers Media SA. - 2296-7745. ; 8
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Journal article (peer-reviewed)abstract
- Seagrasses - a group of foundation species in coastal ecosystems - provide key habitat for diverse and abundant faunal assemblages and support numerous ecosystem functions and services. However, whether the habitat role of seagrasses is influenced by seagrass diversity, by dominant species or both, remains unclear. To that end, we sought to investigate the specific seagrass characteristics (e.g., species diversity, seagrass traits) that influence tropical fish assemblages, and place this in the context of small-scale fishery use. We surveyed seagrass variables at 55 plots, nested within 12 sites around Zanzibar (Tanzania) in the Western Indian Ocean, and used Baited Remote Underwater Video (BRUV) systems to assess fish assemblages across plots. Using linear mixed models, we reveal that seagrass structural complexity and depth were the best predictors of fish abundance, with higher abundance occurring in deeper meadows or meadows with high canopy, leaf length and number of leaves per shoot. Moreover, an interaction between seagrass cover and land-use was the best predictor of fish species richness, where sites closer to human impacts were less affected by cover than sites with lower human impact. Overall, models with seagrass species richness or functional diversity as predictors poorly explained fish assemblages. Fish taxa that were important for small-scale fishery sectors (e.g., emperors, snappers, rabbitfish, and parrotfish) were primarily driven by seagrass structural complexity. Our results provide a unique analysis of the relationship between seagrass habitat and its associated fish assemblages in that we show that seagrass species diversity had little effect on seagrass fish assemblages, which instead appear driven by specific seagrass traits and seagrass cover. If conserving high value species that support adjacent fisheries is the priority for protecting seagrass meadows, then seagrass areas should be chosen with high cover and structural complexity that are in deeper waters. Any conservation measures also need to balance the needs of fishers that use the resources supported by seagrasses.
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