The Earth has been blessed with a magnificent biodiversity, so rich and vast that there are species that still remain undiscovered. The sad reality of today, however, is that many species are being threatened due to human activities, becoming extinct quicker nowadays than ever before. According to the WWF’s Living Planet Report 2020, there has been an average 68% drop in global population sizes of amphibians, birds, fish mammals and reptiles between 1970 and 2016. This depletion of the diverse ecosystems that co-inhabit our planet, poses as much of a threat to life on Earth as climate change.

The United Nation’s ‘Convention on Biological Diversity’, the international legal instrument for the conservation of biological diversity, is aimed at encouraging actions which will lead to a sustainable future. It is in the spirit of carrying out coordinated and concerted efforts that citizen scientists and conservationists contribute in their individual capacities as shareholders of a common future. Yes, we have committed a colossal mistake, perhaps the greatest ever, but natural historian Sir David Attenborough has a message of hope. In his documentary ‘A Life On Our Planet’, he says: “If we act now, we can yet put it right.”

When citizen engagement blends with the power of technology, we get actionable solutions to some of world’s biggest challenges; biodiversity conservation is no exception. Citizen science for biodiversity — engaging the public in research — has proven a creative endeavour in conservation efforts, particularly when coupled with automated machine learning efforts. Here are some examples.

• eMammal: This is a data management system and archive for camera trap research projects. This platform makes wildlife photography accessible, opening the door for citizen scientists to contribute their own images to environmental research efforts. It uses ML to categorise its massive library and guide contributors to record more accurate results. Wildlife researchers and organisations can then access these images to gain a better understanding of wildlife populations and answer critical questions about animal behaviour, reproduction, ecology, genetics, migration, and conservation sustainability. 
• Wild Me: It develops open-source platforms for identifying and tracking wildlife, combining the strengths of AI and citizen scientists to fight extinction. It uses computer vision and deep learning algorithms to create a platform called Wildbook, which scans millions of crowdsourced wildlife images at scale. Wildbook can identify the species as well as the individual animal, and the public can follow the movements of their favorite animals. The aggregated data is used by scientists to help inform conservation decisions.
• Zooniverse: It is the world’s largest platform that engages people in science with crowd-based research projects. Researchers upload their images, videos, or audio files — like camera trap images of wild animals or satellite imagery of a star — and then Zooniverse’s global community of over two million volunteers tag, annotate, or transcribe the file to aid classification. Contributions from many individuals are combined, relying on the ‘wisdom of crowds’ to generate reliable and accurate data. By creating consensus-based classifications, researchers can produce reliable results.
• iNaturalist: It is a platform that allows citizen scientists to contribute wildlife observations to environmental science research, using AI to accelerate the identification of thousands of species. It shares the findings and observations of its members with scientific data repositories like the Global Biodiversity Information Facility to help scientists find and use this crowd-funded data. Members can engage amongst each other by talking with fellow naturalists or hold a bioblitz event where people try to find as many species as possible.

Image by Sergio Cerrato from Pixabay