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  • Tama No Te Tairoto screenshot 1
  • Tama No Te Tairoto screenshot 2
  • Tama No Te Tairoto screenshot 3
  • Tama No Te Tairoto screenshot 4

About Tama No Te Tairoto

The Tama No Te Tairoto app is an innovative citizen science tool designed to improve the collection and diffusion of data related to the reproductive events of marine animals, particularly in the lagoonal reef ecosystems of French Polynesia. Developed by the Polynesian association Tama No Te Tairoto, meaning "Children of the Lagoon" this app aims to meet the growing need for collecting and sharing data on these reproductive phenomena. Reproductive events are crucial for understanding the life cycles of coral reefs and their resilience in the face of climate change. The Tama No Te Tairoto project was launched as part of the study of the synchronized spawning of the Porites rus coral, a rare and little-known phenomenon. Since 2021, the association has established a network of observers in French Polynesia and internationally to observe and better understand the reproduction of Porites rus coral.  However, with the rapid expansion of this network and the significant increase in the amount of data collected, managing this information has become increasingly complex. Until now, observations were collected through free tools and traditional channels such as emails and social media. While these methods have been effective on a small scale, they have become inadequate for handling the growing volume of data, requiring extensive human resources for management. In response to this, the Tama No Te Tairoto app has emerged as an essential solution for centralizing and automating data collection. Its goal is to provide observers with an intuitive and accessible tool that allows them to report their observations in real time. The app offers specific features such as: - Access to practical information for observers: observation protocols, predicted spawning dates and times, recommended observation sites, and species identification keys. - Simplified transmission of observations: users can submit detailed information such as the exact time of spawning, weather conditions, precise location, photos, and more. - Real-time tracking of other observations: participants can view the observations submitted by other members of the network, creating a collaborative and interactive dynamic.  Beyond coral, the app is designed to include observations of other marine species, such as fish, clams, sea cucumbers, and sea urchins, whose reproductive cycles are equally crucial for the sustainable management of ecosystems. It would also allow the collection of data on opportunistic observations, for example, from fishermen or divers, which until now have not been systematically shared or centralized. With the app, this information can be analyzed on a seasonal, monthly, or even hourly scale, providing a better understanding of the reproductive cycles of marine species. The Tama No Te Tairoto app will also have a significant impact on the management of marine resources in French Polynesia. The data collected can contribute to the implementation of conservation strategies, such as the creation of Regulated Fishing Zones (RFZ) or other types of protection, which are essential to protect species during their reproductive periods. In summary, the Tama No Te Tairoto app is an essential tool for the preservation of lagoonal reef ecosystems, providing both citizens and scientists with an effective way to collaborate and share data on marine animal reproductive events.

What’s new

Version 1.0.3 · Updated December 15, 2024

Minor changes related to the starting screen.

App privacy

The developer, ISI.PF, reported these privacy practices to Apple.

Data Linked to You

The following data, which may be collected and linked to your identity, may be used for the following purposes:

  • Contact Info: Email Address

Used for: App Functionality

Data Not Linked to You

The following data, which may be collected but is not linked to your identity, may be used for the following purposes:

  • Usage Data: Product Interaction

Used for: Analytics

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