This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.5334/cstp.571. This is version 2 of this Preprint.
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Abstract
Two Sustainable Development Goals are focused directly on combating the impacts of climate change on coral reef communities. These are: Goal 13 “Take urgent action to combat climate change and its impacts” and Goal 14 “Conserve and sustainably use the oceans, seas and marine resources for sustainable development”. Citizen science (CS) features prominently in a range of programs that have been developed to address these goals. One such program is Virtual Reef Diver, which is designed to help monitor the health of the Great Barrier Reef in Australia. This program engages citizen scientists in two ways. Scuba-divers are asked to take geo-coded underwater images of the reef and upload them to an online virtual reef. Members of the public across the world are then asked to classify these images with respect to key reef indicators such as coral. Through the lens of a Virtual Reef Diver event held as part of 2021 Australia’s National Science Week, we describe important features of this program that positively address common concerns about CS data, including the scientific trustworthiness of the data, the ability to incorporate these data with other more traditional data sources, and the quantifiable improvement in information about reef health using these data for management decisions. This demonstrates the important role that citizen science can play in achieving SDGs by supporting the development of global policies for coral reef conservation.
DOI
https://doi.org/10.32942/X2W012
Subjects
Life Sciences
Keywords
citizen science, sustainable development goals, Great Barrier Reef, Reef heatlh, Disturbances, management
Dates
Published: 2023-01-27 13:32
Last Updated: 2023-03-07 14:44
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License
CC-BY Attribution-NonCommercial 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data and Code Availability Statement:
Model outputs and codes are accessible online (https://www.virtualreef.org.au/resources/model-predictions/ and https://github.com/EdgarSantos-Fernandez/reef_misclassification)
Language:
English
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