Innovating Wildlife Conservation using data: Saving the Planet!
1. Introduction
This Earth is home to trillions of different life forms, including plants and animals. They can be found everywhere, either in lakes, rivers, oceans, or land and air. And as we all know, we need to live in harmony with nature to maintain the balance of the ecosystem. But, due to recent human activities and other natural forces, we have seen a significant threat to the existence of wildlife. With many already extinct, more than 40,000 species are threatened with extinction (IUCNRedList, 2021). Many organisations like The World Wildlife Fund (WWF), International Union for Conservation of Nature (IUCN), Birdlife International, The Nature Conservancy, etc., are working day and night to protect these animals. The WWF, which was established in 1961, alone has more than 6,000 employees across the globe, and it raised $377 million from private and public donors in FY21 (WorldWildLife, 2021). Millions of volunteer workers and NGOs also support these organisations. All these organisations are also taking new initiatives and implementing new ideas as much as possible.
Even after so many people are involved, these organisations face complex challenges that make the whole conservation system unable to support adequate wildlife protection (Ronald R. Swaisgood et al., 2020). Here we will discuss three of these challenges in detail. The world is changing faster with the upcoming technologies, and as the age of data is emerging everywhere, we hope to solve these issues with the help of Data Science & Innovation.
Challenges Faced by these Organisations and Opportunities for Innovations from Data Science
2.1a Poaching: The Illegal Wildlife Trade
Hunting and poaching are among the most significant challenges these organisations face trying to save these endangered animals from extinction. It is also one of the leading factors of biodiversity loss. The greatest threat here is to mammals, birds, and some other species groups. For example, the population of whales, rhinos and elephants declined drastically over the 20th century due to hunting: the infamous species of Blue Whale and the northern white rhino was plunged into extinction, losing 99% of their numbers, and many others are facing the same fate. The risk of hunting is also compounded by growing market demands for wildlife trade, i.e., skins & horns, luxury foods, pets, and medicinal remedies (Hannah Ritchie et al., 2021). According to a meta-analysis that included 176 studies published in the journal Science, the bird and mammal abundances declined by 58% and 83% in hunted compared with unhunted areas, respectively. Bird and mammal populations were depleted within 7 and 40 kilometres of range from hunters’ access points (Benítez-López et al., 2017). Thus, tracking these animals, their behaviours, conditions, etc., is challenging. Also, the poachers sneaking in when the rangers are not there or in the middle of the night creates a colossal issue.
2.1b Opportunities: How to Make a Difference!
The answer to this critical challenge is simple, camera traps and their data. Many ecologists and researchers are also implementing this idea. (The Nature Conservancy, 2020). All the thousands of photographs taken from the remote cameras currently deployed throughout the forests can be used to track the animals and the poachers. The issue with this is from thousands of images; it is almost impossible to go through all the images with naked eyes and detect animals and humans. So, AI comes to the rescue here; we could collect all the movement data from the pictures and train a model to catch any animal or human movement in seconds. Then, we could also pinpoint various locations where poachers usually go hunting and inform the rangers about their pattern and approach. We could also deploy stealth drones camouflaged as birds, insects, or rocks to collect data. It will prevent the animals from finding out any unfavourable objects in their territory along with tricking the poachers so that they won’t be able to damage any devices.
2.2a Migration: From wings to the Land
As birds can fly, they migrate a lot and are threatened with extinction. According to a journal published in Cambridge, it is estimated that 19% of the world’s 9,856 present bird species are migratory, including some 1,600 species of land- and waterbirds. In 2008 alone, 11% of nomadic land- and waterbirds were classified as threatened or near-threatened on the IUCN Red List (Jeff S. Kirby et al., 2008). The factors include climate change, unfavourable landscapes, deforestation, land-use change owing to agriculture etc., including other severe threats like over-harvesting and ill-treatment, especially at crucial migration locations. Infrastructure developments that are at great heights like wind turbines, electric supply cables, telephone towers, and masts can also threaten. The conservation of these birds requires a multitude of approaches. Many of these needs effective management of their binding sites. Important Bird Areas (IBAs) provide an essential foundation for such action; however, to function effectively, IBAs need to be protected, and the consistency of the network requires orderly reviews. They are in good numbers at the start of their journey, but very few of them are left as they reach their last destination. This happens seasonally or almost every year while they migrate. Many reasons remain unaddressed as there is no way to track the path that the migratory species take so that we can find out where the decline in the flock is exactly happening.
2.2b Opportunities: How to Make a Difference!
The challenge here could be tackled with intense tracking of the migratory species, especially birds, with the help of satellite imaging or the ordinary public. The people could just report the sightings of a flock to online databases or websites. The satellite could also track different flocks of birds and spot specific areas across the globe. Then that data can be used by professionals to create a prediction model that will predict the flock’s path and their stops, destinations, roosting patterns, etc. This will provide more accurate intelligence for topographical planning and management and allow necessary preparations for areas prone to bird gatherings. There is only one online database that is large enough to be considered and currently active, and that only collects data from people through an app named eBird (ebird.org, 2022).
2.3a Pollution: A Threat to the Planet
The impact of pollution is listed among the major perceived threats to biodiversity, especially to marine life. It is a cause of particular concern because of its increase at an alarming rate, abundance, durability, and persistence in the marine environment. In comparison to the IUCN Red List, it was highlighted that at least 17% of species affected by entanglement and ingestion were listed as threatened or near-threatened (S.C.Gall et al., 2015). All the aquatic species, including different fishes, crustaceans, coral reefs, are in great danger. Around 80 per cent of marine litter originates from land sources, including waste from riverbanks, beaches, dumpsites, activities of the fishing industry, etc. (Chassignet et al., 2021). There is almost no way to keep a check on the wastes by tracking their origin or keeping adequate records of these wastes or debris so that they can be cleared by the ocean clean-up or beach clean-up programs/organisations.
2.3b Opportunities: How to Make a Difference!
This challenge is not only faced by these organisations but almost any industry. Pollution has become a significant issue for nature, especially created by things made of plastic. It is the most abundant type of marine debris and is found in all of the world’s water bodies, even in remote areas far from human activities. It is of significant concern because plastics decompose very slowly with time, affecting marine life and threatening human health to a great extent. Thus, tracking the movement of waste is crucial; many floats away too far away and thus, the sources are also unguessable. To confront this problem, we need to deploy drones (both in air and underwater) and take litter and waste data from the people around us, especially those who visit beaches, riverbanks, or scuba divers. Then, we can use the data to map it across the globe and cut it from their sources so that they are stopped even before entering the ocean. We could also track the type of waste, for example, cigarette buts, plastic bags, food packaging, bottles, gloves, etc., to directly focus on initiatives for that specific industry generating a significant amount of waste, to create awareness for reducing waste. There are few early adopters also who are using data in some manner to confront waste problems. A few examples are the “Marine Debris Tracker” by Southeast Atlantic Marine Debris Initiative (National Geographic, 2021) or the “Australian Marine Debris Initiative app” launched by an environmental group called “Tangaroa Blue Foundation” (Kate Stephens, 2018).
3. Implementation Considerations
These are some great opportunities for data science to bring revolutionary changes in the domain of wildlife conservation. But there are also many hiccups in implementing these ideas at a large scale. For example, setting up a good amount of high-quality wildlife cameras will put a financial burden on the organisations. Even to put an excess on that, many cameras are destroyed by the wild animals, thus needing frequent replacements. Also, we will have to train the models manually to detect the movement of animals and humans and filter out unnecessary movements of leaves by wind or anything else. As for tracking migratory birds, satellite imaging will be a substantial initial investment to dedicate specific satellites for the purpose. People also are not much aware of different bird species, and there are very few bird watchers across the globe to get that much data to predict the flock’s path or their roosting patterns. Therefore, the observational data are sparse and difficult to analyse and predict. This lack of data also follows the organisations trying to face the concern of pollution. The water bodies on this planet are so big that it is almost impossible to track all the pollutants and forget about the remote areas. Moreover, we need more awareness and volunteers who are ready to contribute their time in reporting different waste locations and data. All these hiccups create a considerable demerit for data-driven organisations trying to face the predicament of the wildlife going towards extinction.
4. Conclusion
The impact of losing so essential wildlife species that help maintain our ecological system around the globe is severe. As described in the three challenges discussed here, it is highly anticipated that wildlife conservation will continue to require many more transdisciplinary solutions for the substantial amount of challenges it faces. It will take versatile & extensive efforts from all of us, along with specific inputs from researchers, experts, and volunteer groups. To facilitate conservation, research must be applied to come over an obstacle. We must move beyond the barriers and put more energy into testing conservation applications. Some of this will fail, but as we adapt, new ideas are tested, outcomes evaluated, and new knowledge is applied to reduce uncertainty. And while the data science innovations discussed here present inspiring opportunities to support wildlife conservation, there is still a long road ahead to achieve the expedition of saving the endangered species from extinction.
5. References
International Union for Conservation of Nature. (n.d.). IUCN Red List of Threatened Species. Retrieved 2022, from ‘https://www.iucnredlist.org/'
Swaisgood RR (2020). Grand Challenges in Animal Conservation. Front. Conserv. Sci. 1:602856. doi: 10.3389/fcosc.2020.602856
Hannah Ritchie and Max Roser (2021). Poaching and Wildlife Trade “Biodiversity”. Published online at OurWorldInData.org. Retrieved from: ‘https://ourworldindata.org/poaching-and-wildlife-trade' [Online Resource]
Benítez-López, A., Alkemade, R., Schipper, A. M., Ingram, D. J., Verweij, P. A., Eikelboom, J. A. J., & Huijbregts, M. A. J. (2017). The impact of hunting on tropical mammal and bird populations. Science, 356(6334), 180–183. doi: 10.1126/science.aaj1891
Data Science for Wildlife Conservation. The Nature Conservancy. (2020). Retrieved 2022, from “https://www.nature.org/en-us/about-us/where-we-work/united-states/massachusetts/stories-in-massachusetts/data-science-wildlife-photos/"
Rethinking camera traps. The Nature Conservancy. (n.d.). Retrieved 2022, from “https://www.nature.org/en-us/about-us/where-we-work/united-states/north-carolina/stories-in-north-carolina/rethinking-camera-traps/"
Kirby, J., Stattersfield, A., Butchart, S., Evans, M., Grimmett, R., Jones, V., . . . Newton, I. (2008). Key conservation issues for migratory land- and waterbird species on the world’s major flyways. Bird Conservation International, 18(S1), S49-S73. doi:10.1017/S0959270908000439
About Ebird. eBird. (n.d.). Retrieved 2022, from “https://ebird.org/about"
Gall, S. and Thompson, R., 2015. The impact of debris on marine life. Marine Pollution Bulletin, 92(1–2), pp.170–179. doi:10.1016/j.marpolbul.2014.12.041
Chassignet, E., Xu, X. and Zavala-Romero, O., 2021. Tracking Marine Litter With a Global Ocean Model: Where Does It Go? Where Does It Come From?. Frontiers in Marine Science, 8. doi:10.3389/fmars.2021.667591
Society, N. G. (n.d.). Debris tracker. National Geographic Society. Retrieved 2022, from “https://www.nationalgeographic.org/education/programs/debris-tracker/"
Stephens, K. (2018, July 18). Clean-up crews tracking tide of rubbish back to the source. ABC News. Retrieved 2022, from “https://www.abc.net.au/news/2018-07-19/app-helps-track-marine-pollution-across-australian-beaches/10009832"
