Upwell: Utilizing Citizen Science for Sea Turtle Research

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Collaborating with traditional fishermen posed ⁣a meaningful obstacle for me​ due to language barriers, my role as a woman in ⁢a predominantly male-dominated industry, and our diverse cultural‌ backgrounds. Firstly,⁤ requesting fishermen to report sightings of sea turtles​ adds an extra​ burden to their already demanding tasks. secondly,asking them to report any accidental capture ⁤of sea turtles requires a ‌high level of trust,as it involves discussing a​ controversial topic that could potentially bring scrutiny to their practices. Additionally, the process is time-consuming and‌ takes away from their primary focus: maximizing catch within limited⁣ time frames in order to maximize both quality‌ and economic returns, especially⁣ since they reside in economically disadvantaged⁣ communities.

Q: Do you have specific methods for collecting or filtering citizen ⁢science⁣ data compared to othre⁢ types of data?

A: processing citizen science data presents unique challenges as it comes from various sources ⁢that are not standardized such as social ‍media platforms, messaging apps, and ​iNaturalist. Such as, converting GPS coordinates into consistent formats or reconciling ambiguous location names like ⁤”Punta Arena,” which may exist⁢ in multiple places can be arduous. This is especially common with fishermen who often do not use GPS and have their own names for fishing spots. To address this issue, we had fishermen mark maps with a grid system, indicating each⁣ box where they fish or have ⁣seen turtles. While this type‌ of ⁢data cannot be cross-referenced with specific dates, it helped us identify the location of fishing spots and provide a geographic reference for their next report.

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